** I will have some exciting news to share shortly. A nasty little tease, I know. Forgive me. Patience, my parents have told me, is a virtue. **

In the meantime, I wanted to share a story that crossed my path recently and got me thinking. How much of success is rooted in effective communication?

Every sport has coaches — and often an entire organizational infrastructure — built around its players. In sports, unlike in business, we can see communication play out before us. Cameras flash to the moments of highest intensity, the dramatic tension, when emotional arguments spill forth on the sidelines or in the dugouts.

What appears to be a breakdown in communication might, given the right environment, be healthy — and even beneficial.

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A recent article in the Harvard Business Review by an Olympic performance coach JP Pawliw highlights what he feels is becoming a barrier to team success, both on the field and in the boardroom:

An inability or unwillingness to have tough conversations.

Pawliw’s team surveyed 34,000 workers about risks they encounter in the normal course of fulfilling their job. They identified a notable gap between the risks they do take and the ones they feel they should. The results showed, for example, that people leave out or avoid approximately 7.56% of what they want to say in a difficult work conversation.

In other words, they will share ~92% of their feelings, but when they get to the more challenging parts, they will back down from having the full discussion.

Pawliw calls this retreat the fundamental conflict of performance. Risk-taking goes against our biology, which rewards self-preservation. But successful organizations have risk-takers that fulfill that last 8% and complete those sometimes-tough assessments. It’s vital to the ability to outmaneuver competitors and shake up the status quo. Think Billy Beane and the “Moneyball” Oakland As.

Pawliw identifies the characteristics of organizations that foster this type of risk-taking — and those that don’t. I thought the results were illuminating for a broad number of domains, both within sports and beyond.

Pawliw said that the largest percentage of respondents to his surveys identified as belonging to teams with a “family culture,” which on the surface sounds enviable. Indeed, many teams strive to create a “family culture” — and it would seem more beneficial to cultivating risk-taking than a “fear-based culture.”

But in a family culture, Pawliw suggests, people may “sugarcoat communication,” breeding resistance to making touch decisions or pointing out “inconvenient truths.” That still leaves the last 8% void unfilled and may be responsible for struggles to reach a team’s true potential.

Alternatively, in a “transactional culture,” there is more risk-taking among employees, but the benefits aren’t generally sustainable. Managers may not be afraid to hold back on going the full 100% with their feedback, but the team culture isn’t there as support, creating a situation more susceptible to employee burn out and withdrawal.

“The last 8% culture” is, as you might expect, a healthy mix of “both high culture and high connection.” The environment is “feedback-rich,” which enables people to take risks, but accountability is delivered “with high care.” It is a culture that fosters innovation because employees know where they stand. The drive for results is counterbalanced by deep concern about relationships.

It’s food for thought as we continue our journey trying to understand some of the hidden “it” factors underlying skill, performance, and success in any domain.

I hope, whatever you are doing, you feel emboldened to go the last 8% and supported in whatever comes from it.

‘Til next time,

Zach

Links

Is marathon running linked to colon cancer? … Gatorade: We want to see women sweat … The performance benefits from spitting … MLB players return from injury faster if their contract is expiring … What sports rivalries can tell us about motivation … The latest nutrition fad in cycling: broccoli juice … First of its kind project to investigate the impact of sleep on peak performance in female athletes … College football’s $1 million strength coach … The world’s first robot games were a clumsy mess

A few weeks ago, John Clayton, having finally emerged out of the woods and mountains of the Shenandoah Valley in Virginia, jogged toward a banner strung between two poles in a clearing and stopped, approximately 28 hours and 41 minutes after he’d started.

His wife, Jaimie, and two kids were there; his hand was bleeding; his feet were blistered. But he had made it 100.6 miles on his own two legs, up and down enormous hills, mountains skittered with rocks, through streams, over boulders, running, running, all day and through the night.

One of the driving forces of this newsletter is to celebrate human performance and explore what we can about how such mastery is achieved. Most of the time our focus is on the professional athletes whose brilliance (or stumbles) we all can witness. But just as often I know we can find inspiration if we choose to look off the beaten trail.

There, probably, you will see John running.

I’ve known John a long time — roughly (gulp) 20 years since we went to college together and worked at the same college newspaper. In fact, I’d seen him a few weeks earlier at a wedding and talked about work and kids. He didn’t mention the epic race he’d been preparing for.

That’s just John, as humble as they come. But when I heard what he had done, I knew I had to speak with him about it. He was gracious enough to allow me to record our conversation to post in this newsletter.

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I’ve had the good fortune to interview numerous endurance athletes in my career, including world-class marathon runners & triathletes, long-distance swimmers, and even a guy who paddle-boarded up the East Coast.

I know rarely are these athletes driven by money or fame, because if they are, well, they’ve chosen the wrong pursuits. But what exactly is driving them is harder to answer, which is why talking to John helped (to me, at least) clarify the steps of evolving from a semi-habitual road-runner in college into an extreme ultra-marathoner in his 30s.

John is also not a protein-hawking runfluencer. He has no Red Bull endorsement (that I know of). He’s a lawyer in D.C. with two young kids. He is constrained by the same career and family responsibilities I know too well. Still he summons the energy and determination to meet and conquer a demand like the Massanutten Mountain Trails 100. It’s one of the most impressive and inspiring things I can imagine.

My interview with him about how he did it is below, or you can watch the video above.

Q: I don’t imagine you just wake up and say you’re going to run a 100-mile race. What are the steps to conceiving that this is a reality for you?

A: Just as, like, a little bit of background, I have run on and off since college undergrad, and I did road marathons. I took a few years off here and there, when I went to law school. And then it was really when I moved out to Colorado in 2021 that a friend of mine, Alec Saslow from Syracuse, got me into trail running. He had done ultra marathons. I hate that name, because it sounds so cheesy, but it’s a catch-all term for anything that's over 26 miles. And I started, I did a 50k and then a 50-miler with him in Colorado, and then I did a couple other longer races. And then it just kind of got to the point where, like, you know, 100 miles was kind of like the next distance. I had originally some reticence. Fifty miles is hard enough. But there's something to 100 miles, just saying it, it sounds like such an amazing challenge. And there will be a period of time when I won't be able to do this. So while I am young(ish) and healthy(ish), I just wanted to give it a try.

Q: You had set this particular race as a target, or was it just the milestone of 100 miles that you had set out to reach?

A: I actually signed up for two other 100 milers before this, one in 2023 and then another in 2024, and both times in the process of training, I got injured and just wasn't able to make it to the starting line. Probably about a year ago, I decided that I wanted to give it another try. I picked this race, the Massanutten Mountain Trail 100 as the one that just seemed like the most interesting, challenging.

Q: What appeals to you about ultra-endurance events?

A: I'm a little bit of a Type A person. I feel like I need that challenge and that thing that's out there on the horizon that I'm striving toward. I also think my relationship with running in general has evolved a lot. When I started running marathons, it was all geared toward, ‘I want to run this time,’ and I got a little burnt out with that. When I started doing more trail running, that's just a totally different vibe. It's way less about how fast are you running, and it's more about the adventure and just being out in nature and exploring a new place, or just enjoying the peace and quiet of being in the woods or in the mountains. Once I kind of reframed running, runs are like an adventure. I'm still a Type A person, and I still want to do my best. But it just kind of like became more about the experience.

Q: You're a busy guy with a job and two young kids. How are you training for an event like this?

A: I worked with a running coach. This was after the second time I had signed up for and gotten injured trying to run 100 miles, and it was totally a game-changer for me. Dr. Jamie Blumentritt (Physical Therapy On The Run), I have to give her a shout out. She set out a training schedule for me and helps me correct some of the training errors that had led to my getting injured previously. But to more directly answer your question, the checkpoints are you have to run a lot, obviously, but it's just not like you can go out and run 50 miles every weekend. A) there's no time, and B) It's just not good for your body. So the peak training weeks were, you would do back-to-back long runs on the weekends, meaning like two 20-mile runs, one Saturday and one Sunday, and then additional 5- to 10-mile runs during the week. I always took a day off somewhere in there once a week, which was usually Monday for me. You're just constantly trying to toe the line between pushing further and building up time on your feet and mileage, but without getting injured, which is the balance that I had gotten wrong before.

Q: Race Day. You’re there, you're setting foot on the starting line. What's going through your head?

A: My race morning was a calamity, of my own making. (laughs)

I have a vest that I wear for carrying food and water, and I have these two bottles that go in the vest — which I left in the fridge of the Airbnb. Which I only realized when we pulled into the camp where the race started. Luckily I had a third soft, like glass bottle, and then a bottle I just brought in the car to sip on the way there. It does not fit very well in a running vest, so I was like, ‘Well, I guess I'm just going to carry this in my hand for the first, you know, 30 miles.’” I had my my wife and my wife's parents were helping to crew me, and I was going to see them at like mile 33 so I knew they would have my my bottles at mile 33.

I had been told enough times that something's always gonna go wrong. Not like you're going to be an idiot and leave your water bottles in the fridge, but anyway, that was my first thing that happened. What are you going to do? Just kind of roll with it. Try not to turn it into something bigger than it is.

Q: Besides the missing bottles, what else is going through your head?

A: I thought I would have a moment before the race started where I would just be like, ‘Okay, this is awesome. I made it here. I'm just going to take a moment to appreciate this.’ But because it turned out to be kind of a calamity with the water bottles, and I was rushing around to get water into the water bottles and get things situated. And then, they were counting down. But honestly, it probably wasn't a bad thing. I had 28 hours to overthink everything from that point forward.

Q: How does the race actually work? You mentioned there are checkpoints throughout. Are there places where you stop to sleep? Are there places to sit down and eat and rest?

A: There's no sleeping. Some people do, but usually, if you are sleeping, then that means that something has gone wrong. You just kind of power through the night into the next day. There are aid stations. One of the reasons I chose this race is it's been around for almost 30 years. It's really, really, well run and has amazing volunteers. The aid stations, the spread at these places is great. They’ve got, like, peanut butter and jelly sandwiches, and bacon and tater tots. You're not always feeling good enough to eat it. But you were never more than, like, nine or 10 miles from an aid station where there was going to be food and water. I was lucky enough to have my wife and her parents crewing for me, so they met me at three places along the course and had everything from medical supplies to a change of shoes. You can also use drop bags to pack stuff into, and they'll take that to a designated aid station so you can access it.

One of the cool thing about these types of races is the volunteers. These are people who are some, in some cases, out in a tent, basically, in the woods the entire night, and they're just there for you. They're not getting paid to do that. They're just doing it out of the goodness of their heart. It’s this really awesome community of people who are excited to help. It’s very genuine. The amount of times where I would come into an aid station feeling really beat up and feeling defeated, and have someone ask me how I'm doing. ‘What can I get for you?’ ‘It's just five more miles to the next aid station you're doing great.’ It makes an incredible difference.

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Q: Are you allowed to have a cell phone?

A: I did have a cell phone, yes.

Q: And as you're running at night, do you have a headlamp on?

A: Yes. That part was interesting — I mean, I've run at night, or more often super early in the morning, which is when I do a lot of my training. I have two kids, and a job that can be somewhat demanding. So my window to train was usually like 5am, sometimes earlier than that. I had been accustomed to running in the dark. It's a little different, though, when you're in place that’s pretty remote, there's often not much cell reception, and you're just by yourself in the woods and whatever else lives in those woods. I thought I would be a little on edge, but it ended up being quite peaceful in a lot of ways. It's just you and the little cone of light in front of you.

Q: Are you listening to music?

A: I did listen to music a little bit, but not that much, in part because I didn’t want my phone to die.

And when I'm in the woods, I just want to be aware of anything that's around me. When it's like 3am and you've been running for like 20-something hours, things get a little loopy. So I’d be just like singing randomly (laughs). If I heard rustling in the bushes, I would just start talking, ‘Oh, hey, just me. Just coming through.’ If I could’ve seen myself, I’m sure I would have looked like an absolute crazy person.

Q: What was the hardest or most challenging moment in the race for you?

A: Well, adding to the difficulty of the course was they got like six inches of rain a couple days prior. The conditions were very difficult, very wet. There was a lot of standing water in places on the course. Times you'd be hiking up a steep hill and there would just be a stream of water coming down the trail. My feet were wet the whole time. And when you're running in wet shoes, wet socks, you can get a lot of blister issues. And that definitely happened to me. At one point it was in like, the 16s somewhere in the 16s, where my feet were really, really hurting because of blisters. I had a moment where I was like, ‘I think I can push through this, but this is going to be very difficult.’ Thankfully, I got to the next aid station, there was this woman who, they called her the foot doctor. I don't know if she was an actual physician, but she was amazing. Just volunteering her time. And she helped patch up my feet so that bought me, like, 10 miles, until my feet got soaked again, and then it was like the same thing all over.

Then the last big climb of the race was just crazy. I was so tired and it was just never ending. I had been warned that this was coming. But there's a section of the last climb that becomes like hiking through a stream, going uphill. You're just like, ‘I don't even know how I'm supposed to get 20 feet from here.’ You're looking for the trail. And I was just so tired. And my legs are so tired, and mentally, I was tired. That was really hard. But then, once you were through that, it was like they were kind enough to give us five or six fairly easy downhill miles to the finish line. But in the moment, it was one of the lower moments of any race that I’ve ever had.

Q: And what was the most peaceful or sublime moment in the race, excluding the the finish, which, I think we can all imagine, was sublime.

A: There were a lot of little moments where you're in the mountains, it's beautiful. It stopped raining fairly quickly into the race, and so it turned out to be a decently nice day. And it's just like, ‘How lucky are we to be here and able to do this?’ Those are my favorite moments of any race where you just have that feeling of gratitude.

Then, right after that last climb, when you have like five miles left to go, and it was all gravel roads, and it was like, ‘Okay, I'm gonna finish.’ Barring, you know, I get struck by lightning, or attacked by a bear or something, I’m going to finish.

Q: Now, how long has it taken for you to recover? Are you running again?

A: It’s not the most healthy thing to do for your body. My sleep has been kind’ve all over the place. I’m definitely getting there. I’m feeling a lot better than I did, I don’t know, 5 or 6 days ago. But it is for sure a process. But I also say that it’s all relative. I’m fine. I can go to work. I live life. But also through this whole experience, I know when my body feels fatigued, and so I can feel that I’m just not fully at my peak where I was heading into the race.

Q: What’s next on the to-do list?

A: I want to do more of these for as long as I’m able to. Who knows? The window could be short. But there are also people who ran this race in their 60s and 70s. It’s incredible. I couldn’t believe it. I think that’s so cool. I’m not saying that’s going to be me, but I would like to do this for as long as I’m able. I don’t know if it will always be 100-milers. But I love running, I love the—I hate to use the word ‘journey’—but the experience of training for a race and the discipline that that takes. I think there are a lot of things from that that translate into other parts of my life. I’d love to be able to run races with my kids someday, that’s my dream.

Links

How elite athletes train their eyes to see the world in slow motion … Do nasals strips enhance athletic performance? … Female-first footwear: How tech, sports science are reducing injuries, increasing longevity … Tom Brady dives into the physics of football … Research reveals advice for women athletes is not supported by science … Are female experts more credible? … How data science is changing football scouting … New research shows endurance athletes need as much protein as weight lifters … Cold plunges might actually undo recovery … RIP John Brenkus

I talk to myself all the time.

Usually I’m rehearsing things I want to say during a meeting or I’m reminding myself about the million things going on in the waning days of my kid’s school year.

But sometimes I’ll adopt a strategy increasingly used by elite performers: I’ll tell myself how great I am.

This isn’t meant to be hubristic. Self-talk is a motivational tactic. It’s like turning up the volume of the pump-up anthem in your brain. In many cases, it is used to drown out the negative thoughts that can more easily creep in.

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It’s not uncommon today to see top athletes muttering to themselves in the heat of competition. Roger Federer, in the fifth set of the 2018 Australian Open semifinal, was caught on camera self-talking so loudly that the chair umpire thought Federer was talking to him.

No, Federer was only talking to himself.

According to a study from Queen’s University in Canada, humans on average have around 6.5 thoughts per minute, or about 6,000 per day (a widely cited figure places the number at 60,000 per day, but that has never been verified). It’s a lot of thoughts. It’s unclear what portion of these running thoughts are negative (again, a widely cited but not-verified figure says it’s as much as 90 percent). But it is safer to say we reflexively give more importance to negative thoughts or experiences, which tend to stick in our memory. Psychologists refer to this as our negativity bias.

For some people, there is a real, quantifiable benefit to overcoming the negativity bias with positive self-talk.

I recently read a study published in the Journal of Sport and Exercise Psychology that tested 126 professional Spanish soccer players on how self-talk might influence their performance in a physical task. The athletes were asked to write down and then verbally repeat three positive self-statements (“I can do this”) and three negative ones (“I always stink at this”) before completing a test of their vertical jump.

As predicted, athletes produced higher leaps and greater jumping power following positive self-talk than when they had been self-critical.

A notable qualifier in the study suggests self-talk can’t just be empty self-platitudes, however. Individuals experienced better results if they were actively thinking about and engaging with their directed verbalizations. The athletes who spent less cognitive energy on the self-talk experienced very little benefit from it. So if you’re going to talk to yourself, really listen to what you have to say.

Another way to see better results from self-talk is to get out of the habit of referring to yourself in the first person. People who motivate themselves with second-person pronouns (“You can do this”) or third-person pronouns (“Come on, Roger”) have been shown to perform better at stressful tasks.

This is thought to be because of what psychologists call “emotional distancing,” or “othering” oneself, which can help manage anxiety and distress. One study in 2017 used neuroimaging techniques and found that individuals who silently talked to themselves in the third person were better at harnessing their emotions in stressful settings than those who self-talked with first-person pronouns.

When are the times that self-talk works best for you? And are there certain mantras or expressions that you consistently come back to? Let me know in comments or privately via email.

And, as usual, if you liked this post, please share it by talking about it — or clicking the “share” button.

Talk to you (and myself) soon,

Zach

Links

The secret sauce to a 4 OT hockey game is mustard … Does micro-dosing make you a better athlete? … FIFA-funded study to investigate whether menstrual cycles could be contributing to rise in knee injuries in women's soccer … The Kenyan runner trying to become first woman to break 4-minute mile … How Plant Sciences Research Is Helping BYU Football … The story of a 77-year-old marathoner being studied for the science of aging … The rapid rise of “illegal” running shoes … Decision by Texas high-school football to allow players to use wearable devices could radically transform America’s favorite sport … What it’s like to drink coffee like Dan Campbell for a day

References

Horcajo, Javier, and Rafael Mateos. "The effects of positive versus negative self-talk on vertical jump in soccer players: The moderating role of need for cognition." Journal of Sport and Exercise Psychology 46.2 (2024): 73-83.

Moser, Jason S., et al. "Third-person self-talk facilitates emotion regulation without engaging cognitive control: Converging evidence from ERP and fMRI." Scientific reports 7.1 (2017): 4519.

When a colleague showed Phil Evans an article about the Yankees’ ingenious “torpedo” bats on Monday, he had to chuckle.

“I can think of some things they could even do better,” Evans said.

Evans, a professor of wood science at the University of British Columbia, in Vancouver, appears to have been ahead of the curve when he published a study on baseball bat optimization with his student, Sadegh Mazloomi, in 2021. Four years later, baseball is just catching up.

Over the weekend, the New York Yankees made nationwide headlines after the YES Network’s cameras showed that several players were using oddly shaped bats this season — bats that seemed to taper at the very end with the meatier “sweet spot” closer to the handle. Their look was likened to a torpedo or a bowling pin.

They were apparently the brainchild of a former University of Michigan physics professor who worked in the team’s analytics department. He noticed that different players were more likely to connect with the ball at different points along the barrel. He customized each bat to place more mass where it would receive the ball more frequently.

The results (so far) have been striking. The Yankees slugged a record-tying 15 home runs over the weekend, with the torpedo-bat wielders enjoying the most success.

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They’re a great spin on conventional bat design. But… are they as good as they could be?

Evans doesn’t think so.

When I called him this week, I found out he’s been testing out bat optimization techniques since at least 2014. Now nearing retirement, he wishes someone would have called him sooner.

“There have been so many advancements in pitching,” Evans said, “the hitters need help.”

Baseball fans and players are familiar with the term “sweet spot,” which generally refers to the impact point at which vibrations are least felt in the hands upon collision with the ball. When a ball hits the “sweet spot,” the hitter barely feels the collision. And, more importantly, no energy is lost — it all goes into the ball.

Mazloomi said there are actually two locations on the bat where this occurs—and maybe more. One is the “center of percussion” (COP), which is roughly at the center of the bat’s mass, and generally closer to the handle than the midpoint on the barrel.

There are also nodal vibration points along the bat that do something similar. Bat designers usually try to ensure that the nodes are in places where the barrel is thickest.

Using computer modeling, Mazloomi and Evans decided to see what could happen if they brought the COP and the nodal points together.

“We optimized the geometry of the bat by redistributing the mass to bring the nodal points and COP closer to each other,” Mazloomi said.

The result, in theory, would be much higher ball rebound velocities, less vibration, and better performance — like a supercharged sweet spot.

Call it the “OptiBat.”

Their conceptual design looks strikingly different. It has a barrel with a “hitting side” that is circular and a “non-hitting side” that is flatter, not unlike a cricket bat — except reversed. The weight, length, and other properties of the bat all stayed the same. But they were able to cut the distance between the COP and nodal points more than 300 percent.

Evans said the flat-backed design is fun-looking but probably wouldn’t have to stick.

“That’s just what proved to be the most optimal, because there's a hitting side to the baseball bat, and we shifted the mass in that way,” he said. “That would have been easy to do with the traditional bat, as with any other shape. So, yeah, we could certainly optimize it.”

They may not even have to. Baseball rule 3.02 states that “[a] bat shall be a smooth, round stick not more than 2.61 inches in diameter at the thickest part and not more than 42 inches in length. The bat shall be one piece of solid wood.”

Evans thinks there’s wiggle room beneath that definition, noting that the “axe handle” bats that have become popular already transgress the “round” regulation.

“For a mathematician interested in geometry, well, define a circle,” Evans joked.

Evans said it makes sense that the Yankees shifted the mass in their torpedo bats to create a sweet spot tailored for a hitter’s swing. But he’s not sure, by the looks of it, whether the COP and vibrational nodes are aligned as optimally as they could be.

“They could shift it from some of it from the other end too, because that's not really where you hit it either,” Evans said. “It’s a fairly simple concept that they've employed. Now, obviously you don't want to shift too much or the handle breaks, so it's kind of a balancing act there.”

Now that the cat is out of the bag on the torpedo look, other teams are already sizing up their own players’ configurations. But if they want to truly optimize their bats’ performance, they may want to call Phil Evans.

And hurry up. Because he’s ready to begin his retirement.

Talk soon,

Zach

References

Mazloomi, M.S.; Evans, P.D. Shape Optimization of a Wooden Baseball Bat Using Parametric Modeling and Genetic Algorithms. AI 2021, 2, 381-393. https://doi.org/10.3390/ai2030024

What can your choice of words say about you?

This week, I saw an intriguing research paper out of the MIT Sloan Sports Analytics conference in Boston, an event I have been to before. It suggests that the frequency of certain word choices used by collegiate basketball players can forecast a successful future in the NBA.

On the surface, this sounds kinda bonkers. But the fact that the co-author was a highly regarded social psychologist, James W. Pennebaker, a pioneering figure in linguistics and trauma, gives it some heft.

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Before we jump into the methodology, let’s start with the motivation. Traditional NBA scouting has primarily rested on physiological metrics (such as from the combine) and performance metrics (from box scores). More recently, an effort is underway to better evaluate the mental side of performance, too.

One way is to look at how certain choices are made. Sports psychologists (and journalists) often do that by asking athletes, after the fact, why they made that pass here or took that shot there. What often separates great athletes, however, is that they make the right decisions without thinking, either because of heavy training and scripted sets or some other instinctual je ne sais quoi.

Another issue with self-reporting is that people tend to mold their answers to fit what they think an interviewer wants to hear. This is especially true when the interviewer represents an NBA team to which a prospective collegiate player is hoping to be drafted.

Access to the subconscious decision-making apparatus in athletes, then, would offer a more authentic picture of the person and how he or she thinks. This is where language comes in.

Language studies have found that how you say something can be a lot more revealing than what you say. We tend to think about the content of our language as we are speaking. But it’s the filler words that actually form the meatiest bits of our psychological profile, because they are harder to manipulate consciously.

Pennebaker has an umbrella term for them. He calls them “function words.” They include pronouns, articles, prepositions, and a small number of other common words. Pennebaker is the author of the book The Secret Life of Pronouns, and his theory is that these words offer clues about feelings and thought-processes.

So…

Can “function words” carry over to the NBA?

In the Sloan paper, the researchers analyzed the transcripts of more than 25,800 postgame interviews conducted by NCAA men’s basketball players between 1995 and 2023. They found that, using a language psychology model called LIWC (Language Inquiry and Word Count), they could predict with 63 percent accuracy which athletes will successfully make it on to an NBA roster. LIWC was also successful at predicting which of those players will be able to last in the league beyond a four-year rookie contract.

Let’s look at one of the examples brought up by lead author Sean Farrell, a data scientist from Australia. He pointed to this excerpt from a postgame interview with Jayson Tatum, then at Duke, in 2017:

You will notice, if you are looking closely, there are 12 conjunctions in this selection of 100 words (conjunctions, for those reaching back into their old English class studies, are connective words like and or because). Conjunctions add complexity to a simple sentence. Psychologists consider the use of conjunctions to be a signifier of deeper analytical thinking and slower decision making.

There are also four present focus words, such as “realize,” “we’re,” and “is.” Present focus words, the researchers said, is a stand-in for mindfulness, a good trait for top performers.

“Those who are more likely to not make it into the NBA use more complicated language and ruminate more on the past than look to the future,” the researchers said.

One example the researchers gave was Khris Middleton, a late-second round pick whose college resume and physical attributes didn’t exactly scream future NBA All-Star. But his linguistic score told a different story.

Compare that with Craig Brackins, the 21st overall selection in the 2010 NBA draft, who was a dominant big man in college. His mindset metrics, however, were badly off the mark. His NBA career lasted only 17 games.

When discussing the results, Farrell makes an interesting point. The language analysis shouldn’t be confused with a reflection on intelligence. In fact, the researchers are strictly avoiding the content of the remarks. Their focus was on the function words, the little fillers that can be greatly revealing about mindset and decisiveness.

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There are certainly flaws in the picture provided here. The dataset was based off published ASAP transcripts from postgame press conferences at major events like the NCAA tournament. If your team didn’t make it to the Dance, your words probably never made it into this study.

That also means that great superstars like LeBron James and Kobe Bryant, who never played in college, were also not reflected in this study.

As a former sports reporter, I might also quibble with the choice of tournament postgame press conferences, which are often big, bright, intense, heavily scrutinized events that might not be perfectly reflective of an athlete’s truer character in a more relaxed, normal setting.

All that being said, I loved the unconventional effort being made to access subconscious decision-making. It has also inspired me to choose my words wisely — even the little ones.

Talk soon,

Zach

Links

The paradox of hard work … How family background can help lead to athletic success … How competitive athletes develop grit … How WhatsApp is helping football learn from AI … Experimental new golf ball coating rolls consistently on wet or dry grass … Is playing tennis the secret to living longer? … The elite figure skater who rewired her brain to respond to pressure ... A behind-the-scenes look at the England rugby camp … Is the VERT system in volleyball actually accurate? … Sneeze smarter, not louder

References

Beyond the Box Score: Using Psychological Metrics to Forecast NBA Success

Anyone who has spent much time reporting on the brain sciences is familiar with the name Eleanor Maguire. She was a psychologist at University College of London studying memory. Like all good researchers, she noticed something that seemed extraordinary and asked, How?

What she saw, so the story goes, was a semi-forgotten TV film from the 1970s that was re-airing in London in the mid-1990s called “The Knowledge.” It was about the drivers aiming to pass the test that earns them the “green badge” license for London’s famous black cabs.

The movie explains that candidates need what is essentially a photographic memory of roughly 25,000 streets and 20,000 different landmarks along hundreds of different routes throughout London’s central city. Many observers have called it “the hardest test in the world.”

A story in The New York Times Magazine in 2014 found that drivers must automatically know “anywhere a passenger might ask to be taken,” including clubs, restaurants, stadiums, courts, hospitals, and other places of interest. And the examiners are ruthless. “Test-takers have been asked to name the whereabouts of flower stands, of laundromats, of commemorative plaques,” according to the Times.

Drivers aren’t allowed to consult maps when they are performing their duties. GPS? Don’t even think about it. To prepare, candidates are issued a textbook with 320 routes. Studying usually requires practicing each of the runs, timing out shortcuts, over and over and over again, for years.

One driver logged 50,000 miles on foot and on a motorbike over more than three years. He memorized 40,000 flash cards.

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Maguire passed away in January at age 54 after a battle with cancer, so I thought it would be appropriate the share her enormous contributions to the fields of neuroscience and psychology — and computer science, which we’ll get to later.

After watching the movie, she brought dozens of experienced cab drivers into the lab and scanned their brains to understand what may be behind their extraordinary ability to recall so many destinations. Sure enough, Maguire discovered that a brain region called the hippocampus in drivers was physically larger compared with non-drivers — even larger than London bus drivers, who only need to know a handful of routes.

This alone was an earth-shifting discovery: London cabbies have bigger hippocampi than normies. But Maguire still was not satisfied with that. Were the cab drivers born with a different brain structure that selectively steered them in the direction of driving? Or did their brains develop and change over time?

Four years after the original study, she brought the same drivers back into the lab and measured even more growth in the hippocampus among those who were still driving, and no growth from those who had stopped. It told her that the brain was changing as drivers continued to practice their craft. Just like a professional pitcher would have a stronger arm than most people, London cab drivers had developed brains that were adapted by their training.

Maguire did not technically discover what we now know as “neuroplasticity.” That is a concept that goes as far back as psychologist William James at the turn of the 20th century. (“The brain-matter is plastic,” James wrote.)

But until her studies with cab drivers, the popular view about the brain was that it became essentially “fixed” upon entering early adulthood. There are “critical periods” of development early in life, but once we reach a certain age, those windows are shut.

Maguire showed that adult brains, in fact, can change quite dramatically — if pushed or pulled in meaningful directions. It is responsive to lifelong learning. Even something like memory, long thought to be primarily inherited, can be trained over the course of one’s experience.

Maguire’s findings have been hugely influential for studies on aging, neuro-rehabilitation, and recovery after traumatic brain injuries. And the science of memory continues to build off the work that Maguire started more than two decades ago.

Just last month, a new study published in the Proceedings of the National Academy of Sciences argues that London cabbies should change how we think about training artificial intelligence.

Researchers profiled drivers and found an astonishing trait: Without a map or a GPS, they were able to call out the names and turns on any route between any destination in the entire city of London.

They had, in essence, memorized the entire map of the city and could retrieve select pieces of it at any moment.

When GPS or other algorithmic systems attempt to do this, it requires a mind-boggling number of steps in order to produce turn-by-turn directions. They run through hundreds or even millions of possible routes in order to find the one that is most optimized. That they can do this in a matter of seconds is remarkable, but it requires an enormous amount of energy and computing power.

Conversely, the researchers found that the thought process of the London drivers was much more efficient. They mentally mapped out their routes in order of complexity, spending more time thinking through the trickiest junctions and less-common streets they predict they might encounter and filling in the rest of the details later.

The researchers were shocked by this approach and how their extraordinary knowledge of the city seemed to grant them a unique kind of intuition about navigation. Their brains didn’t behave like computers at all. They were far more flexible and efficient. This granted them expertise over their given domain.

We should be training algorithms to do something similar, the researchers suggested. Eleanor Maguire’s initial epiphany to study cab drivers after watching a TV movie continues to pay dividends.

Until next time,

Zach

Links

How streaks keep you productive … Why palm-cooling devices are all over the sidelines … The NFL thinks Aaron Rodgers is washed up. Science thinks he is a bargain … How AI is helping Chelsea fill its roster … Handstands, aquatic cardio, and... speed chess? How Victor Wembanyama trains … Triathletes don’t sleep enough … The “cuboid” might be the most important bone in golf … How to throw the longest drives in disc golf … The Science Behind Why Footballers Spit on the Field … Getting JAKed (h/t ) … The risks of relative energy deficiency while training … Twitch streamer hired by professional soccer club thanks to success managing virtual teams … RIP Richard Morgan

References

Decoding the Knowledge: How Taxi Drivers Think Differently From AI

NYT Magazine on The Knowledge

Eleanor Maguire obituary

Warm regards from frozen New Jersey. Researchers at Brigham and Women’s Hospital in Boston have landed on something interesting in a recent study on surgeons: When the surgeons’ stress levels went up in the initial minutes of an operation, the end result had fewer complications.

Usually, we associate stress with a lot of negative things. This goes for health, workplace performance, and elite athletics. When archers in the 2020 Olympic Games were outfitted with heart monitors, those with the lowest heart rate (one indicator of stress) scored better.

But don’t stress too much about too much stress. There’s a wealth of newer research on the positive benefits of getting a dose of stress — particularly for performance.

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It sounds counterintuitive. But most of this derives from the work of Canadian psychologist Hans Selye, who coined the term “eustress” in the 1970s (eu meaning “good” in Greek) to describe what he called “healthy” or positive stress.

Eustress isn’t a syndrome; it is defined primarily by how someone perceives a particular stressor. A popular example is someone heading up a roller coaster ride. For some, a roller coaster is a stressful ride that is perceived positively — in fact, thrill-seekers want to engage with that type of stress. For others, it produces a negative reaction. Eustress for some can be dis-stress for others, with harmful outcomes.

“Good” stress isn’t just reserved for certain cohorts of people, though. It’s arguably a requirement for anyone to reach peak performance.

Speaking of roller coasters, the classic depiction of the relationship between stress and performance is actually an inverted U-curve.

To get to that performance apex, a substantial level of arousal is required. Some of this is biological. Encountering a stressful situation triggers the sympathetic nervous system, the “fight or flight” mechanism, and gets adrenaline pumping, glucose flowing, and blood pressure rising. This can make you more alert and reactive, sharpen your senses, and activate cognitive activity.

While prior research has looked into how surgeons react to stressful situations that crop up in the middle of a procedure, the Boston researchers this time opted to measure heart-rate variability1 in 38 attending surgeons during the first 5 minutes of an operation. This was to ensure that the surgeons’ stress level was self-induced and not influenced by how the procedure was going.

They saw, across the board, some big jumps in stress levels, regardless of their experience. However, the stress didn’t make the surgeons worse. They worked better under pressure.

Not surprisingly, the study’s authors said they were inspired by research on elite athletes, who constantly have to make decisions and face challenging circumstances. An entire industry of mental coaching has arisen in the past two decades to offer motivational and/or coping methods to reach peak performance without cracking under pressure.

The tipping point at which one cracks and begins to slide down the backside of the inverted U is an area that needs further research. But, again, successful elite athletes can offer instructive examples. Phrases like “pressure creates diamonds” and “pressure is a privilege” are common mantras that are employed to reinforce the notion that stress can be good for performance, taking the negativity around it and flipping it on its head.

Admittedly, I’d be a little nervous if my surgeon walked in hyping himself up and wearing eye black. But here is a way sports psychology can have a lot to offer us — and maybe even improve our health. The researchers hope their study will lead to more uptake of HRV in operating rooms as a stress monitor, just as high-level athletes use wearables and train to be skilled at intentionally bringing stress levels down or up, depending on where they are at.

The lessons shared by athletes about stress and performance can benefit professionals in almost any setting, whether it’s a writer trying to finish a story on deadline (gulp), a student facing midterms, or a CEO pitching to investors.

As we embark on a new year, try not to only think of stress as a negative. It could be your best springboard toward success.

I hope if you find this helpful you will consider sharing it either via email, social media, or simply using the Share button below.

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Keep an eye out for more free newsletters coming soon. And reach out to let me know if there are topics you feel would be worth exploring. Cheers

Links

Anatomy of a Sport Climber … Are Americans Doing Fitness Wrong? … First patients scanned in new advanced MRI study investigating traumatic brain injury in young athletes … Fingerprick blood test tracks recovery in elite athletes … Does Vitamin D improve your strength? … Short-Term Supplementation of Sauerkraut Induces Favorable Changes in the Gut Microbiota of Active Athletes … VC firms are recruiting college athletes … S.H.I.T. recovery … Shit helps

References

Awtry J, Skinner S, Polazzi S, et al. (2025) Association Between Surgeon Stress and Major Surgical Complications. JAMA Surg.

Happy new year everyone,

The annual Consumer Electronics Show recently concluded in Las Vegas, and, in addition to walking robot vacuums, electric salt spoons, and stretchable TVs, there were several eye-catching sports-tech innovations as well.

I wanted to highlight a few of them here, and also point out a pattern I noticed in reviewing the event.

It’s one that would make me a bit nervous if I was a coach or trainer.

There’s no question that AI has made an impact in data-gathering and assessment for sports teams. What we’re seeing now is its integration into wearables and sports-training apps.

In the near future (if not here already), wearable technology will collect biometric data through sensors and cameras (some of it previously undetectable) —> their connected apps digest it all —> and artificial intelligence can then analyze it and offer personalized suggestions or corrections to maximize each and every swing or stride.

It begs the question: With such tools, who needs coaches?

Here are a few examples:

The G-Grip

Swing coaches, head’s up. Claiming to be “the world’s first intelligence golf club,” the G-Grip from Korea’s SGLab Inc. has loaded its irons with so many sensors that it can record preferred metrics like tempo, angle, swing path, etc., as well as some valuable newer things, like grip pressure. Artificial intelligence instantly analyzes all the data and gives you a readout via app on what you did wrong or right on every swing. The AI also gives the club information to provide haptic feedback to correct your motions. That’s impressive. It’s designed by a PGA professional, and you won’t need a backpack full of other cameras and equipment to get the training advice you’re looking for.

PuttingView

A screw-on cap for your putter plays the role of a caddy, giving you an approximate distance to the hole and the optimal angle that the putter head should be at impact to sink every putt. It uses AI to quickly analyze green elements and your swing motion, and the precise coaching information pops up right on the cap, so you don’t need to dig through your pockets for an app.

Smart Shoes

How would you like a running coach who knows the condition of all your muscles and joints, is available 24/7, is highly professional, and talks to you like an old friend? That’s the promise of WearM.AI, a one-year-old Dutch company, which introduced a wearable sensor that can be clipped onto your shoelaces to register muscle loads on each step. The sensors are equipped with a small camera facing upward to capture images of your full body posture as you move. Among the insights it can deliver are knee contact forces that were previously accessible only in research labs. The app summarizes the data and provides coach-like feedback on how to train better and smarter — and avoid joint injuries. “Our mission is to create a digital sports coach that everyone can have,” CEO Huawei Wang said in an interview with Startup Magazine. “It’s affordable, always available, and provides very professional suggestions.”

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Haptic Suit

Infinity Football XR last week introduced a full-body suit—plus shin guards, cleats, and gloves—that provide tactile sensations to wearers while they are playing a virtual game against real opponents elsewhere. The tactile feedback lets players touch the ball, hit opponents, and even get goosebumps from scoring a goal. The suits are equipped with biometric sensors monitoring various fitness parameters. Get many of the real benefits of soccer practice without having to leave your living room.

AI home gym

The Amp Fitness machine looks like a fence post. Its minimalist design has just one adjustable arm pulley. But its digital app acts as your '“personal trainer” that can coordinate hundreds of different resistance levels. The machine uses AI to track your performance, calibrating weights automatically to challenge you constantly and ensure you’re making progress. The system captures every rep and personal record so you don’t have to, and it uses the data to design personalized workout plans.

Smart Lacrosse Ball

It’s a lacrosse ball loaded with sensors — accelerometers and gyroscopes that can track shots at a rate of 1,000 data points per second — but that’s not all. The R1 ball from Syracuse’s Get Reps also uses machine learning to analyze all that data to understand that player’s throwing motions and offer personalized feedback. The ball and app “work together like your own private coach,” the company says, “showing you exactly what to improve after every throw, every shot, and every drill.”

Smart Yoga Mat

The YoctoMat is a yoga mat embedded with sensors that share insights into your balance and posture. It can translate your weight distribution into a visual map to help you improve your alignment in certain poses and see how your progress changes over time. The app can also connect with your smartphone camera and use AI to offer real-time feedback on your alignment as you stretch, “digitizing the work of yoga instructors.”

Indoor surfboard

An AI-powered smart surf/snow/skate board that pairs with a video game to help you train indoors. An app uses AI that crafts a personalized training program, suggesting tricks you can practice depending on your performance, and how much time you will need to practice to pull it off.

That’s just a few of the many sports- or fitness-related tech inventions on display in Las Vegas last week, which also featured panels on the future of sports-fan engagement and sports media that are worth a listen.

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The AI threat to coaching

So, what can these products suggest about the future of sports?

Firstly, I think it’s important to take these things with a grain of salt. CES is a showcase to let brands test out concepts, but many of these concepts are a long way from full-scale production. Same goes for the sports tech examples I’ve listed here. Some products can already be purchased, while others are still raising money via Kickstarter. It’s best not to get overly excited about too many of these devices (even the salt electric spoon).

That said, in general, it does appear as though companies are starting to understand how and where to employ artificial intelligence for a consumer purpose. Sports and fitness training, in particular, presents itself as ripe for disruption.

It is already a very data-heavy industry, and improved sensors and cameras supplying newer biometric data will only add to the avalanche of numbers coming in on each and every athlete at each and every moment. A system that can handle those numbers and analyze them is a huge plus. And then, where AI is getting interesting, is its potential ability to translate that information into readable advice and, as the smart shoes company says, talk to you “like an old friend.”

Of course, I would have questions about accuracy. These companies tend to think of all data as being black and white, but we all know there is a lot of nuance in the numbers, particularly in how they translate into on-field results.

An app can claim to offer “personalized” results, but how well can a computer know a person? What does it understand about her motivations? How can it know when to push you in her training or when to pull back? I’m not sure.

Still, you can understand why some aspects of this might appeal to an athlete. If a clip-on sensor can measure joint loads in real time, warding off injury based on recorded, objective, and personalized data, who would you rather trust? The computer or a coach’s eyes?

Maybe this should be a wakeup call to coaches and trainers leaning heavily on data analysis that the differentiators between them and machines are shrinking.

The mental/psychological game is where human coaches can still offer the most “personalized” coaching — by accessing an area that the computers can’t yet reach: inside the head.

Links

Pickleball adds years to your life expectancy … Static stretching has “trivial effects” on performance … The ‘red advantage’ is no longer true for Olympic combat sports … Study: Position-specific traits in football players … The art of scanning in football … Should doctors warm up? … A Minnesota limo driver invented the tech that’s changing college football … NASCAR evaluating how AI can help on-track product … The science of rotation … Can nasal breathing improve performance? … How could bio-banding change the academy experience for players? … Mental health in elite coaches

Until next time…

A few years ago, five researchers in the Netherlands wanted to better understand what characteristics might distinguish an expert in sailing.

They recruited six professional sailers and a collection of intermediate and non-sailers. A real dinghy was brought into the lab and placed in the center of an octagonal room with fans positioned at each of the eight corners. The subjects were all given noise-canceling earphones and told they had to keep their eyes closed the entire time, removing the two most obvious sensory receptors. Then they had to “sail,” or navigate the boat along a sailing simulation.

The fans clicked on and off at different intensities and different intervals to produce the effect of changing wind speeds and directions, approximating real sailing conditions on the water.

When the fans were at their highest speed, all three subject groups were able to accurately and consistently recognize the directions of the wind blowing.

Where the professional sailers distinguished themselves is when the wind speeds were at their lowest. Far better than novices or intermediates, they could perceive the most subtle shifts in wind direction. When everyone else was in the dark, the experts used their other senses to expand their performance.

The researchers called this expertise in “cutaneous perception.” They likened it to studies on blind people that perform better in tactile discrimination tasks than sighted humans. Findings there have shown that blind people don’t “touch better” because they’re blind. They touch better because they use their sense of touch more often. It is a reward of their experience, not their disability.

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In The Atlantic this week, I wrote about a 2017 study led by biomechanics expert Glenn Fleisig into the finger forces imparted on a baseball by expert pitchers. Fleisig et al. found that the last peak of force from the fingers occurs only milliseconds before the ball is released, and that peak averaged 185 Newtons of force. This, as I wrote, is enough force to heave a bowling ball 90 mph.

What Fleisig told me is that previous studies on the biomechanics of pitching never could fully decipher how pitchers throw so hard. The angular velocity of the shoulder maxes out around 90 mph. Legs and torque add some heft, but it seems the fingertips were doing a lot more for pitching than we’d known.

Fleisig found that differences in those finger forces impacted the ball’s spin, ball flight, and velocity. You hear often about pitchers late in games battling a tired arm. Perhaps they could mitigate late-inning arm fatigue with more concentration on the fingers.

The other question I think some teams should be asking is: Who is using their cutaneous perception better?

Tactile clarity

I began thinking about this thanks to my own failings as an athlete. When I played basketball growing up, I was a decent spot-up shooter. Where I struggled the most was dribbling.

I marveled at other players who could yo-yo the ball through their legs without looking or breaking stride. I’ve since come to appreciate that the ability to “feel” in dribbling is, like the sailers who can decipher subtle wind shifts, a function of experience and a lot of deliberate practice.

But is that it?

As a matter of fact, there are differences in “tactile clarity” between people. People with smaller hands, in general, test better, which helps to explain why women typically have sharper tactile clarity than men — and may help to explain why big men like Shaq more often struggle with a fine-motor task like the delicate release on a free throw.

Do we know this for sure? No. As far as I know, it’s not being tested, even though hand sizes are measured in NBA and NFL scouting combines.

Like other senses, tactile clarity also peaks at a young age and gets worse as we age. But unlike vision or hearing, there are no contact lenses or hearing aids for the skin. We don’t have any baseline (like 20/20 vision) for what good tactile clarity should be, and we don’t have examples of superior “touching” ability to show us what’s possible, like perfurmers and sommeliers who have honed their noses and palettes to perform amazing things with their sense of smell and taste.

We can point to athletes, but generally we give credit to other things besides their sense of touch. It’s a blasphemous oversight.

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A famous experiment by Roland Johansson in the 1980s offers the perfect example why. In the experiment, he asked a woman to strike a match, why she executes promptly.

He then places a tiny prick of analgesic onto the finger tips of her thumb, index, and middle fingers, numbing a few of the many thousands of sensory receptors in those regions. What happened is that the woman suddenly became unable to pick up the match or pinch it in her fingers. She fumbled for nearly a minute.

Nothing happened to her motor function. Just her tactile clarity was temporarily dulled, and it ruined her capacity for skilled movement.

You can watch the video here:

Shameless plug

You can read my story for The Atlantic for free here: A Touch Revolution Could Transform Pitching

And do follow Adam Moreau: https://x.com/FlexProGrip

Alex Fast: https://x.com/AlexFast8

Connor Lunn: https://x.com/ConnorLunn

And David Ginty: https://www.gintylab.hms.harvard.edu/

Links

Meditation can supercharge your endurance … What’s 80/20 training? … Does height matter in soccer? Yes … “Fourteen tripods circled the basket, all equipped with infrared cameras.” … Professional women’s baseball team set to launch in 2026 … Pickleball physics … NBA strikes Airbus deal for more comfortable planes to reduce athletes’ fatigue … The new science of chess … New pill mimics the effects of a 10K without moving a muscle

References

Kinoshita, Hiroshi, et al. "Finger forces in fastball baseball pitching." Human movement science 54 (2017): 172-181.

Pluijms, Joost P., et al. "Expertise effects in cutaneous wind perception." Attention, Perception, & Psychophysics 77 (2015): 2121-2133

The best story in football this season is not the quarterback down in Washington.

Nor is it the resurgence of Sam Darnold in Minnesota or the breakout of Saquon Barkley in Philadelphia.

All are good stories.

But sorry, the best, most fascinating story is without a doubt the Dallas Cowboys’ kicker.

In just his second year in the league, Brandon Aubrey has already been dubbed the “Stephen Curry of kicking” — by Tom Brady, no less. He appears to have no limit to his range. He lined up for one kick earlier this year at 71 yards, which would have broken the NFL record by 15 feet. He ended up nailing a kick from 66 yards, tying the league record, but it was waved off due to a clock violation.

It won’t be the last time, because it wasn’t the first: Aubrey hit a 66 yard kick during the preseason. He’s also hit from 65 yards this year. He had yet to miss a kick of 50-plus yards in his career (16 for 16) until sailing a 51 yarder against the Giants wide right. It was just the third miss ever for Aubrey, who had started his career 35 for 35, smashing a rookie kicking record last year.

What makes Aubrey so remarkable at kicking?

The answer may not surprise you, although I’m here to tell you why it should: He spent most of his life as a soccer player.

Growing up in Plano, Tex., Aubrey won 5 state titles as a youth soccer star from 2005-10 and was ranked as the 43rd best player in the country coming out of Plano High School in 2013. He earned a soccer scholarship to Notre Dame, became an all-American defender, and was drafted in the first round of the MLS Draft.

After two seasons, Aubrey got cut by an affiliate of the Philadelphia Union, and it seemed like his sporting days were done. He took a job as a software engineer for GM Financial (you can still find his LinkedIn profile). Reportedly, he was watching NFL RedZone one day when he saw kickers missing and got the idea to see what he might do kicking a football.

He’d had some experience playing football before. He’d just always played wide receiver.

A rare transfer

Making the switch from pro soccer to pro football sounds like a natural adjustment. But it’s actually quite rare.

Yeah, there was Jan Stenurak and Pete Gogolak and Tony Fritsch, but the list really isn’t that long. Why?

Well, some ex-futbolers have complained that the NFL football is harder and tougher than the football they’re used to, with much greater pressure, causing more stress and injury. Others have lamented the lifestyle change. Being a kicker is a quirky role, requiring an obsessive attention to detail and excellent time-management skills. It’s not for everybody.

A few, like Tony Meola, have noted a much more important reason why converting from soccer to football kicking isn’t seamless. Meola, a star goalkeeper for Team USA during the 1994 World Cup, was brought in to try out for the Jets in training camp. Meola was a NJ native and a multi-sport athlete, but he played basketball and baseball in addition to soccer. With the Jets, the award-winning soccer goalie got cut after the third preseason game.

From an article in The Guardian:

He remembers the coaches drawing a little circle on the ball, where they wanted kickers to aim. “(And it’s) the size of a 50c piece,” Meola says. “A soccer ball has a big circumference. You can hit one side or the other side and it still goes 60 yards. That’s not the case with a football.”

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So the actual skill of kicking a football is a lot different than what’s required in soccer.

Let’s talk for a moment about what it actually means to transfer one particular skill to another domain.

Skill transference

The two main concerns about skill transfer are magnitude and direction. Magnitude: Is the transfer effect strong or weak? And direction: Has it been achieved in a positive direction (better performance) or negative? You can generally apply these questions to any application of skill transfer, whether it’s riding a bike, learning the piano, or kicking a round object.

The sensible theory that transference is easiest when two situations are alike has been around since Thorndike at the turn of the last century. You would think that sports that are alike would automatically produce stronger positive transfer from one to the other, like kicking in soccer and football. But this is a dangerous assumption. Many times, it’s the activities that seem more familiar to you that are the hardest to switch into, because the differences in how the skills are executed are more subtle.

These small differences in two similar actions can easily slip into negative transfer. Negative transfer is bad. It means that your performance at the new task would be worse than if you had just started as a total novice off the street, because you’re so indebted to the skills of the initial task. It’s embarrassing.

A good example is baseball and cricket. Has anyone successfully jumped from one to the other (I’m asking; I don’t know!) A few years ago, a star professional cricketer named Kieran Powell tried to cut it in Major League Baseball but he never advanced beyond a tryout with a couple clubs. There are a lot of similarities between batting in baseball and cricket that would seem to promote strong positive transfer, but also some big dissimilarities: cricket bats are wider, cricket pitches are bounced, the baseball mound is closer, etc, etc. Negative, negative, negative. Powell may not have been worse than a novice, but he didn’t get too far.

This has been looked at in many, many different ways over the years, and the problem is generally chalked up to the skill specificity required to become an expert in certain tasks. When elite rugby players were asked to anticipate a rugby players’s next movements on a video clip, for instance, they performed far better than a novice. They were then asked to identify the type of pitch being thrown by a baseball player — a totally different skill than they have trained. At this, these elite athletes were worse (or no better) than a novice off the street.

Given this, it’s not surprising that a lifetime of soccer training would make it hard to magically jump over to football. So what makes Aubrey’s story different?

I think what gets lost in the retelling of Aubrey’s story is that he worked for two years with a private kicking coach in parks and fields until he had his routine down, which is why he didn’t become an NFL rookie until age 28. His kicking coach seemed to know what Aubrey might encounter, and so he warned him that success making the transfer was unlikely. I will make the assumption here that, in those sessions, Aubrey and his coach identified the areas likeliest to produce strong positive transfer between his soccer-kicking ability and eliminated the possible pitfalls into negative. These areas may be physical (how to reposition your body to strike a non-moving football) or perceptual (what to focus on while approaching the kick).

What they didn’t assume is that because he’s good at checkers he’d automatically be good at chess.

Links

Mobile apps can serve as an effective alternative to traditional imagery skill techniques for young athletes … New study documented the training volume and intensity of six elite Chinese rowers during a 44-week period leading up to the 2019 World Championships … Could ADHD actually be a superpower for some athletes? … Does this cooling headband actually boost performance? … Elite Athletics and the Social Nervous System … Scientists discovered the secret to one man’s 1,100 pound deadlift … Having a hobby is good for your body and brain … The science behind sports’ most popular supplements

References

Müller, Sean, et al. "Does expert perceptual anticipation transfer to a dissimilar domain?." Journal of Experimental Psychology: Human Perception and Performance 41.3 (2015): 631.

Oppici, Luca, and Derek Panchuk. "Specific and general transfer of perceptual-motor skills and learning between sports: A systematic review." Psychology of Sport and Exercise 59 (2022): 102118.

The first time I’d ever heard the term ‘flow’ was in 2016 at a human-performance conference in Santa Fe, N.M., and I remember feeling exhilarated. It seemed the perfect word to capture an almost divine hallmark of performance, something we’ve all experienced — that moment of clarity while doing something we love, when time melts away and things become effortless and easy. We all seek that flow.

The fact that there was science, evidence of biomarkers and neurochemistry, to back up the existence of these ‘flow states’ was marvelous. But eight years later, I still struggle with making the leap between the flow we might experience in our daily lives — driving to school, listening to music, typing out this newsletter, etc. — and whatever transcendent psychological state that a Stephen Curry or Roger Federer might reach while achieving their peak performance. Are they flowing like me? Or is theirs a somehow different echelon of flow?

Rather than attempt to unpack a warehouse full of conflicting studies on this, I thought I’d zero in on some very interesting applied flow work being conduced by my friend, Greg Applebaum, who heads the Human Performance Optimization lab at the University of California-San Diego.

Greg’s work recently caught my attention because of whose flow is being measured. It’s Mike Gordon, bassist for the band Phish, and Bob Weir of, you know, the Grateful Dead.

Applebaum, Gordon, and a number of colleagues have been developing what they’re calling the XenboX, a Brain Computer Musical Interface (BCMI) used for defining and promoting musical flow states. In essence, the XenboX is a “flow meter” that can be activated by the musicians themselves to indicate when they are in or out of flow.

In the clip below, which Applebaum granted me permission to share, you see Mike (left) and Bob grooving in the lab-studio, donning EEG headcaps, and tapping the XenboX foot pedals.

I called Applebaum recently to ask him about the work, which is ongoing. I’ve typed up our conversation. Hope you enjoy.

This interview has been edited for clarity.

How would you define what ‘flow’ is?

I don't have a really satisfactory definition. And part of the cool but challenging part of the science is actually getting a convergence of definitions.

In the attentional control literature, we oftentimes think about flow as 'doing an executive function that requires a lot of top down control with a lot of automaticity.' So, the analogy I give is when you're learning to drive a car. First time you get behind that wheel, you see everything, you remember everything you notice the color of the other cars. Today, when I drove I didn't pay attention to anything. My driving is automatic.

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The other important element in, I don’t want to say the definition of flow, but the value of flow, is who is doing what? Me swimming laps at the pool and feeling like I'm in a flow is not the same thing as Bob Weir at a concert or LeBron James in a basketball game. Everybody at some time feels like they have a lot of automaticity in their activities. Driving a car, for example, I may be flowing. But Mario Andretti driving a car and experiencing flow has a different value and utility for the flow state.

How is flow different from heavy concentration or focus?

For me, my kind of conceptualization of flow is that it is when heavy concentration becomes effortless. The thing that you otherwise would have to really concentrate on to do successfully becomes effortless. That involves some combination of automaticity and relaxation.

Flow also doesn't have a constant utility function over people or even within a person. It’s one thing for Steph Curry to be flowing during practice versus flowing during a game. It's a totally different thing for my son to be flowing during a high school volleyball game versus a professional athlete to be flowing during a game that has real meaning.

It still sounds like you’re hedging your definition a bit.

I think everybody has trouble putting their finger on what flow is. It's a fairly loose term. I think it's like pornography. You know when you see it.

How did this project come about?

Mike Gordon [bassist for Phish] has really been interested in flow for a while. He's a very smart guy, and he has a lot of scientific interests. He's the one who's been leading the charge.

What was your approach?

Well, a real challenge of trying to measure flow in the person who's flowing is that the realization of flow might knock you out of flow. The reporting of flow almost definitely knocks you out of flow.

Right, because you’ve lost your train of focus.

Right. So how do we get past that? Our idea was to create a foot pedal. Musicians, especially guitarists and bassists, they use their feet all the time to signal things. They thought it's very natural to signal flow with their feet with this switch. So we started doing some practice sessions, and it kind of quickly became, ‘Hey Greg, when I clicked the button, that means I was just in flow.’ Not that ‘I’m in flow now.’ It’s that, ‘I had the realization that I was in flow.’”

Retrospective reporting.

It’s a retrospective realization that I've been achieving something that's usually really, really hard for me, but I was doing it effortlessly.

All the time that this is going on, we have them wearing an EEG system [that’s monitoring brain activity]. We also have a system that’s measuring all kinds of physiology, heart rate, accelerometers, gyroscopes, blood-oxygenation.

In addition to this system all hooked up to the musicians, we also wanted to get other people's judgment of the flow. Let's us have some people in the audience rate it. We’ve found that, every time we do it, the audience has five or 10 times as much flow as the musician, because they're subjectively enjoying it.

The real ace in the hole is we're also working with their sound engineers. The sound engineer is the person who is responsible for laying down the tracks for the recordings. They're the ones who have this really trained ear, and they have a lot of experience. If an engineer works with a musician or a band for a long period of time, they have a lifetime of experience of that musician trying that really hard thing and failing and failing, and then succeeding, and then succeeding kind of effortlessly and transcending and making it even better. So we considered them to be kind of like an expert rater of flow in the musician, who could potentially clue us in to when the performer is in flow without interrupting the performer.

Why is this information of value to the musicians?

One way it’s valuable is as a kind of a training tool. It’s neurofeedback. I can signal when I'm in a flow state, so now I know what a flow state feels like. I get feedback from my own physiology, and I can kind of recreate it through the feedback.

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The other thing they’re doing is using the XenboX as a controller. So, you know the person's flowing, and now it can just act as a switch to turn on a sound effect, or turn on a light show or something. That's what they've really been doing and enjoying. In a perfect future version of this, there would be an algorithm that says, okay, the ratio of these brain activities that we think differentiate flow from non flow has crossed a threshold. The algorithm detects it, and that starts a sound effect or a light show or whatever. But what they're doing is they're just looking at it in real time, and the sound engineer is making changes, and they feel like this is fantastic, because it gives a sound engineer and the musician another lens into the performance.

Are there other ways you are trying to investigate flow in experts?

We’ve created a similar system that we’re using for measuring performance in surgeons doing robot-assisted surgery. What we’re trying to do there is link the physiology to the performance, and the performance is typically defined by errors. We consider errors to be like the opposite of flow. We're trying to look at what are the physiological indicators of when someone is performing at a high level, and when they're either about to commit an error or they’ve just committed an error.

Sounds like that information would be quite useful.

What we’re looking at is, ‘How do you find the features of performing at a higher level? How do you find the physiology associated with that?’ It may not be flow. It may just be error detection, or it may be the lack of error attention.

We're trying to discover things that people could use. In the surgery space, it could be an early warning system for error detection - that would be like the dream situation. It could be a warning signal. Everything we do now is so quantified. We have mobile monitoring of everything we're doing. So how do we use it? Like, I use my Apple Watch to remind me to go exercise more.

Will performers respond to internal feedback like a ‘flow meter’?

We're all looking for that little edge. I do believe that the insight that we can get into our own abilities helps us be better. A lot of what we do is based on external insight: Your coach telling you what you're doing. You might watch a video of yourself or listen to a recording of what you're doing. But more and more in the world now is we’re also getting an internal signal of what we're doing. We measure our physiology [through devices like the Apple Watch] and say, ‘Hey, I want that physiological state.’ I want to recreate that physiological state because I feel it associates me better with higher performance.

For more on Applebaum’s work, please visit: https://www.optilab.net/

Links

Japan halts gene research of athletes over privacy concerns … Kang “will develop and incorporate a training concept unprecedented in women’s [soccer], based on the specifics of the female body” … Athletes swear by red-light therapy, should you? … The performance-boosting effects of baking soda … Tulsky left career in science to become Hurricanes new GM … Amazon says its AI can predict blitzes … Why some say tennis is the world’s healthiest sport … Variety is the spice of learning, memory study suggests

Shameless plug

I wrote recently in the NYT about a sports memorabilia goldmine that had been hidden from the public for years in Virginia. Here’s the link:

https://www.nytimes.com/2024/09/14/business/sports-memorabilia-collection-discovery.html

References

D'Ambrosia, Christopher, et al. "The neurophysiology of intraoperative error: An EEG study of trainee surgeons during robotic-assisted surgery simulations." Frontiers in Neuroergonomics 3 (2023): 1052411.

D’Ambrosia, Christopher, et al. "The physiology of intraoperative error: using electrokardiograms to understand operator performance during robot-assisted surgery simulations." Surgical endoscopy 37.6 (2023): 4641-4650.

Man vs. Machine

It’s been 27 years since IBM’s DeepBlue supercomputer shocked the world by beating the grandmaster Garry Kasparov in chess. AI has since proven capable of outperforming humans in a lot of things, and counting. Where we still have the edge clearly - very clearly - is sports.

But is that changing? Google last week introduced DeepMind’s first “AI-powered robotic table tennis player,” and let’s get one thing out of the way to start: It’s a big step up from the ridiculous 3-point shooting robot introduced by Toyota a few years back:

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Google’s PongBot doesn’t loom menacingly — it doesn’t have any anthropomorphic traits at all. It’s an industrial robot arm that has been endowed with AI software and given a ping-pong racket. And in a study involving 29 human participants, the bot was capable of winning plenty of matches.

In fact, it didn’t lose any matches against beginning players, and it won 55 percent of its matches against intermediate opponents. It zips from side to side along the table and even adjusts itself back and forth to square each stroke before returning to the midline to await a return. According to Google, the bot struggled with extremely “fast or high balls, has difficulty reading intense spin, and shows weaker performance in backhand plays,” which is why the robot struggled to win at all against experienced or expert players. These are problems that, over time, with training and a few engineering tweaks, I would suspect that the robot could eventually overcome.

Google trained the AI by having it watch videos of a lot of ping-pong matches, and then by letting the system play real games against opponents. By the final round, the robot had learned from over 14,000 rally balls and 3,000 serves. Google says the computer performs by analyzing the game state at each moment, adapting to the opponent’s style, and choosing one of a few shots out of a repertoire it has developed, like a forehand or backhand, for each incoming ball.

In a nutshell, we do the same thing.

Fewer unforced errors

The bot has a few advantages over us. For one thing, it shouldn’t get nervous. There’s no threat of an automated table-tennis system choking under pressure or developing the yips in a tense bout. It won’t tire during a furious rally or overthink its next shot after flubbing the last. Take psychology, emotion, and fatigue out of the picture, and it’s good to be a robot athlete.

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Robots also shouldn’t have problems moving. By this, I mean a few things. They’ll need no warmup, no stretching; just turn them on, they’ll be in peak form. Absent a mechanical breakdown, they’re not susceptible to injury. And their actions also aren’t subject to the natural perturbations that we encounter in our day-to-day movements. That’s called motor noise, and it’s mostly imperceptible — until we’re trying to do repetitive, fine tasks like signing our name or reaching for a glass and you may notice slight deviations, the result of the motor signal encountering minor turbulence on its route from the brain to the muscles. If motor noise didn’t exist, we’d never have a sport called darts — it’s part of what makes physical performance unpredictable and competitive. It’s what makes us human.

So the robot would be motorically pure, which is annoying, too, because assuming its calculations are correct, then each shot should be consistent, smooth, and flawless. Not even Roger Federer could say that.

Declarative vs. Procedural

What I’ve described above sounds like an unbeatable opponent, and yet Google’s bot couldn’t win against experts. What did the experts have that AI didn’t?

In the literature on skill learning, there is a very famous story about a man named Henry Molaison. Patient H.M., as he was known, had severe anterograde amnesia that left him with no short-term memory, forgetting events sometimes as little as 30 seconds after experiencing them. But his ability to draw and trace improved over time, despite having no memory of ever performing the task each time.

H.M. received declarative instructions on how to trace. Though he might not have remembered them, his brain was encoding the necessary signals to get his muscles to move in the right fashion. In its simplest form, this is how motor learning is achieved — going from declarative to procedural so that, over time, you don’t need the declarative anymore.

Why is that important? It frees the brain up for higher-order cognition. Serena Williams doesn’t need to hear the declarative instructions on how to serve each time she takes the court. She has encoded that information into procedural memory, with access to quick retrieval of it whenever needed. And without those cognitive resources spent thinking about the declarative, she can focus on strategizing, improvising, and improving upon those skills to become an even better … Serena Williams.

Analyzing thousands of hours of video gives a robot enough declarative information to beat an amateur, but taking its game to the next level will require a lot more practice — and maybe a certain creative spark that’s uniquely human. We’ll see.

Links

Why elite athletes are harnessing their own brain waves for sporting success … The advice mental health experts give experienced Olympians … Why do women suffer more ACL injuries? … Why contrast therapy could be the next big thing in Olympic recovery … How sprinters run the perfect race … The sports where women outperform men … The world’s fastest climber trains by playing chess … Why baseball’s switch hitter is trending toward extinction … What can Olympians teach CEOs? … Public health experts want IOC to dump Coca-Cola as sponsor for the good of the planet

Athletes aren’t always great at explaining their competitive mindset or giving speeches (Lou Gehrig aside), which is what made Roger Federer’s commencement address at Dartmouth College last month all the more remarkable.

Federer is no longer the owner of the most Grand Slam titles in men’s tennis, but he is still, to many observers, the greatest men’s player to have ever competed. Always classy and dignified, albeit a little aloof, I somewhat doubt even Dartmouth’s board expected Federer to wow them with words.

But he delivered an address for the ages.

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After a few jokes about never attending college, his discomfort in a robe, and how much he likes green (i.e. Dartmouth’s colors/Wimbledon’s playing surface, ha ha), Federer got into what he really wanted to impart: How hard it is to be a champion.

“In the 1,526 singles matches I played in my career, I won almost 80 percent of those matches,” Federer said. “Now, I have a question for all of you. What percentage of the points do you think I won in those [1,526] matches?”

The answer: 54 percent.

Amazingly, this checks out. According to ATP statistics, Federer held a 1251-275 record in his lifetime, and yet he won just 54 percent of the total points that he played.

Scan the stat sheets and you’ll find similar results.

Rafael Nadal: Has won 83 percent of his career matches, but only 54.5 percent of total points.

Novak Djokovic: 83.8 percent of matches, 54.5 percent of total points.

Jimmy Connors: 81.7 percent of matches, 49.7 percent of total points.

Pete Sampras: 77.4 percent of matches, 53.5 percent of total points.

“In other words,” Federer says, “even top-ranked tennis players win barely more than half of the points they play.”

Some readers might point out here that Stephen Curry is a career 47.3 percent field-goal shooter, or that Wayne Gretzky had a career 17.6 percent shooting percentage, or that Ted Williams only hit safely in 34 percent of his career at-bats. Failure is a part of sports, and athletes have to learn to thrive within (or because of) persistent rejection. Yet I think Federer’s example is particularly striking. Tennis is an individual sport, and these individuals are persistent and dominant winners. But their margin of error is shockingly slim. If golfers only made 54 percent of their putts, from any distance, it would be far more difficult for any single competitor to emerge with any regularity.

How does a top-ranked tennis player handle this constant, bludgeoning struggle? “You learn not to dwell on every shot,” Federer said. “You teach yourself to think, ‘OK, I double-faulted. It’s only a point. … Even a great shot, an overhead smash that ends up on Sportscenter’s Top 10 playlist, that, too, is just a point.”

Just a point. You won’t hear that from a Nike ad.

It’s a terrific graduation speech pearl of wisdom, though, and one that carries a lot of implications for achieving greatness in practically any line of work where perfection isn’t necessarily expected or required (ie., a 54% success rate for a bomb disposal specialist wouldn’t get you very far). But even in areas where some performances can appear extraordinary (be it stock picking, or car sales, or cooking, or tennis), the end result can belie a lot of fickleness in the steps leading up to it.

For tennis stars, Federer suggests, the key to overcoming a 46-percent fail rate on every shot has to begin with an even-keeled temperament. As fans, we hate this. We expect our athletes to live and die with each possession, refuse to accept failure, and outwardly project our own “win or else” ultimatum. Federer says this same inclination is there, internally. But his competitive nature can’t and shouldn’t be winning the power struggle against a chiller mindset.

“When you’re playing a point, it has to be the most important thing in the world,” he says. “But when it’s behind you, it’s behind you.”

Here’s the full speech:

54 percent

Federer’s 54 percent number has another historical antecedent in recent sports.

It’s exactly the figure that Seattle Mariners general manager Jerry DiPoto cited last October as being the measure of a “successful” franchise in baseball.

“If you go back and you look in a decade, those teams that win 54 percent of the time always wind up in the postseason,” Dipoto told reporters. “And they, more often than not, wind up in the World Series. So there’s your bigger-picture issue. Nobody wants to hear the goal this year is, ‘We’re going to win 54 percent of the time.’”

DiPoto got a lot of heat for his comments, which came after the Mariners had just been eliminated from postseason contender despite having won (you guessed it) 54.3 percent of their games last season. That’s still a great record, DiPoto suggests, and if extrapolated over a decade, it’s actually an achievement.

Fans mocked DiPoto’s answer and put “54 percent” on T-shirts, but he, too, is right:

Over the last 10 years (of full, 162-game seasons), only five have won more than 54 percent of their games:

Dodgers

Yankees

Cardinals

Astros

Guardians

Only the Atlanta Braves (53.2 winning percentage), Boston Red Sox (53.8), Chicago Cub (51.7), and Tampa Bay Rays (53.5) have played in more postseason games than any of those teams mentioned.

Despite what fans think, 54 percent seems like a relevant delineation point for successful teams, just as 54 percent separates fine tennis players from all-time greats.

Sports bettors often cite a related figure as being “the most important number” in their line of work: 52.4 percent.

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That’s the percentage that long-term bettors have to win to overcome the “vig” (sportsbook commission) in order to break even. Get to 52.5 percent, and you’re a profitable sports gambler. It seems like a reasonably attainable figure, but it requires about 5 percent more accuracy than the sportsbooks in picking games to make money. That’s a tough test of handicapping skill, and probably why most bettors can’t hack it in the long run. Next time you see someone claiming to be the “Federer of Sports Gambling,” know that they’re likely only right about 53 percent of the time.

The 54

What Federer doesn’t mention in his speech is that there is a secret to his success hidden beneath the 46 percent of points that he lost. Some points are more important than others.

A 2019 study in the German Journal of Exercise and Sport Research looked at 128 singles matches played by both men and women during the 2012 London Olympics. They found that, for male players, the strongest discriminators between winning and losing were the percentage of break points won, the percentage of first-serve points won, and the percentage of return points won on the first serve. Winning players won roughly 48.9 percent of their breaks, 79.5 percent of their first serve points, and 32 percent of their return points on the first serve. Losers (20.9% on breaks, 67% on first serve, 20.7% on returns) trailed considerably in those three winning variables.

[Female player success was much more heavily influenced by break points won, with winning players owning 57 percent of their break points, and losers just 32.3.]

Look at Roger Federer’s career statistics and you’ll notice some commonalities. Fed won 50.1 percent of the break points he faced, 77 percent of his first serve points, and 32 percent of his return points on the first serve.

A different study from 2023, looking at 4,669 points played during the 2021 French Open, Wimbledon, and U.S. Open, found that a successful first serve increased the chances of winning the point by roughly 17.5 percent. Statistically, the optimal route to winning a point was by delivering a strong first serve, maintaining a rally of less than five shots, and ending with the ball dropped into service zone, which usually produced an error by the opponent. Tennis fans would have to chime in here, but I’d venture a guess that Federer did that a lot.

Ten thousand hours

Moving on from cold, hard statistics, I think there is another “soft” lesson from Federer’s speech, about grit and determination.

The most universally accepted theory about the foundation of expertise is K. Anders Ericsson’s so-called Ten Thousand Hours rule, positing that a minimum of 10 years of deliberate, effortful practice is the true hallmark of expert performance. My takeaway from this research is less about the number. I’ve always been floored by the years.

Years. Years of obsessive, intensive, deliberate, effortful, practice. Practice. We’re talking about practice. Years. I played saxophone growing up; couldn’t last more than two years. Didn’t have the patience, the time, the obsessiveness to keep it going, all three of which is absolutely required to even begin a march on the path toward 10,000 Hours. Few do. That’s where the experts truly separate from the rest of us. They’re maniacs.

Federer’s example makes me marvel at the grit and bonkers tenacity of a performer whose skill only manifests a successful point at a rate just above chance.

I have to imagine that requires some psychological extremes to belong and remain in the upper echelon, including, as Federer mentions, an extraordinary ability to move on, forget the last play, and fight for the next. For years. Few have it. They’re maniacs.

But the rest of us can learn a thing or two.

Links

Faster, stronger, smarter? New research shows the importance of brain training for junior athletes … India’s newest addition to its Olympic team: a sleep expert … The secretive art and science of picking USA’s Olympic gymnasts … Engineering a fast swimming pool … Humans are built to go faster in the 50-meter freestyle and 100-meter dash than current records show … The science of Simone Biles … How to take the perfect soccer penalty kick … The number theorist teaching Olympic swimmers to swim more efficiently … Golf putter works so well “it feels like cheating” … The spray-on sneaker is gunning for gold in Paris

References

Fernández-García, Ángel Iván, et al. Differences in competition statistics between winners and losers in male and female tennis players in Olympic Games. No. ART-2019-114269. 2019.

Prieto-Lage, Iván, et al. "Match analysis and probability of winning a point in elite men’s singles tennis." Plos one 18.9 (2023): e0286076.

Culver, J. “Why 52.4% is the most important percentage in sports gambling.” Medium, 2020: https://medium.com/the-intelligent-sports-wagerer/why-52-4-is-the-most-important-percentage-in-sports-gambling-16ade8003c04

I read a lot of obituaries about the great Willie Mays over the past week. And I was struck by something that kept popping up again and again when discussing Mays’s unique and profound greatness.

A lot of people talked about his hands.

This, from Tom Boswell in The Washington Post: “Mays’s fingers were like cigars. ‘He has Wes Unseld’s hands,’ I thought. Because Unseld is 6-foot-7 and 245 pounds in the NBA record book and Mays, on my 1957 Topps card of him, is listed as 5-10, I suppose this is impossible. But myths, and memories, have their prerogatives.”

From David Schoenfeld in ESPN: He had “huge hands that gripped the bat like a toothpick.”

From the NYT obit: “His frame seemed ordinary at first glance — 5 feet 11 inches and 180 pounds or so — but he had unusually large hands.”

From Dusty Baker: “[Mays once] showed me his hands. The muscle between his thumb and his forefinger looked like a golf ball in there.”

And Bobby Valentine: “Willie's hand would engulf your hand. It gulped it up."

Get the picture? If not, well, here’s a picture:

That’s Mays shaking hands with Ty Cobb in 1958, well before photoshop or Midjourney was invented.

How about this one?

That’s a lot of baseballs fitting comfortably within a single grip.

So let’s consider — did Willie’s hand size actually matter to his greatness?

Get a grip

The NBA and NFL draft combines have for years measured hand sizes of incoming prospects as a [very] crude means of gauging a player’s ball control. Hand sizes are discussed especially frequently among quarterbacks — I remember Michael Vick’s relatively stubby paws being a topic whenever he fumbled or threw an errant pass. The largest hands among active QBs belong to Jordan Love of the Packers (10.5 inches), but there about a dozen others within a few hairs of that mark. Joe Burrow (9 inches) has some of the smallest hands in the league. He’s still pretty good.

Mays’s hands are a different matter, because they perform a different task. For a baseball hitter (I’m focusing on hitting today), the hands are used for one thing: gripping the bat. In clinical terms, this is known as the “power grip.” (Gripping a ball is called a “precision grip.”). And it’s easy to surmise that a handshake is a good indicator of how somebody might grip and swing a bat. But that’s not really how we swing a bat at all.

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Performance coach Chris Yeager says that professional baseball hitters actually don’t “swing” a bat. They “throw” a barrel.

In his view, the hands at contact are nonessential: One could completely lose his handle on the bat upon contact and it would not change the outcome of the hit. Indeed, just look at some of Ichiro Suzuki’s hitting highlights to see how this might actually bear out.

Studies on swing mechanics basically confirm this notion. Force-time signatures during a batting swing (as well as a golf swing, hockey slapshot, and tennis forehand) tend to show some commonalities. One is that the force of grip is low during the backswing and then ramps up dramatically during the acceleration/downswing phase. Grip force tightens right before impact but then reduces at impact. The peak of grip force doesn’t usually occur until after the ball has already left the bat. This is probably because the hands reflexively tighten so that the bat doesn’t fly out of the hitter’s hands.

The amount of force used to grip a bat or club is inversely proportional to wrist range of motion. In other words, as I move my wrist joints more, my grip force goes down. Why is that important to know? It implies that the timing of applied force during a swinging motion might be more important than the amount of force itself.

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The force be with you

Yet a lot of studies have looked at grip strength and its relationship to hitting. One of them just published earlier this month.

It was sent to me by my friend Greg Appelbaum at the University of California-San Diego, who co-authored the study along with Jordan Kohn and a few others.

They examined Trackman data from more than 74,000 swings during the 2022 and 2023 seasons in the Appalachian League, a high-level collegiate baseball league. Each of the 189 players surveyed had completed a performance assessment via USA Baseball’s Prospect Development Pipeline, a sort of scouting combine for baseball prospects.

The PDP conducts a whole battery of physical tests, assessing everything from vision to cognitive processing. But, Appelbaum told me, they decided to settle on three measures in particular: 30-yard sprint speed, a type of vertical jump test called “countermovement jumping ability”, and grip strength. With the scores on these three tests, they could look at all 74,000 swings to find links between test results and hitting outcomes.

Overall, the researchers found that the measures captured in the PDP assessment (plus height and weight) accounted for 50 to 55 percent of the variance in “hard hits” (in-play batted balls with an exit velocity above 95 mph) during the two seasons that were measured. That’s a very strong outcome. “I think it is pretty darn impressive that we can predict >50% of the variance in hard hit percentage from real games,” Appelbaum says.

As for grip strength, it came in fourth among contributors to “hard hits,” behind only height, weight, and countermovement jumping ability (an assessment of lower extremity strength). It was more predictive than age, sprinting speed, vertical hang time, and position. But it’s probably important not to get carried away: If you want to predict how hard a prospect is going to hit the ball, best to start at the legs.

Long drives

Other studies have poured water on suggestions that grip strength has anything to do with bat speed velocity at all. A 1997 study on expert softball hitters found that the mean grip strength in players was significantly stronger than non-players, but this isn’t a determinant of batting success. It just means that they regularly got resistance training from swinging a bat.

A 2004 study by Shawn Hughes, et al., put baseball players on a training regiment for 6 weeks to strengthen their grip to see if it would improve bat speed. At the end of the program, there was no difference between the grip trainees and controls. Hughes concludes that “grip strength and bat velocity are not significantly related.”

A swing, like most skilled movements, is at its most efficient when it is produced via a solid kinetic chain. Kinetic refers to energy, in this case derived from the ground when you plant your feet to begin the swing motion. The energy from there travels upward — in baseball hitting, usually the four prominent segments of the kinetic sequence are the pelvis, truck, forearms, and hands. Each segment accelerates and then decelerates sequentially — the hands are the last “link” in the chain receiving and then distributing that energy through the swing. It would make sense, from this standpoint, that strong hands would be less important to a swing sequence than the legs, trunk, or forearm that are responsible for the earlier sequential power generation.

I think it’s interesting, though, that golf studies have found the opposite.

Several papers (from Torres-Rhonda, 2011; Cummings, 2018) have drawn links between grip strength and faster clubhead speed, contributing to longer drives. And maybe that can be chalked up to the differences between the rotational path of a golf swing vs. the more parallel plane of a baseball swing.

However, a review by William Sheehan, Rob Bower, and Mark Watsford from Sydney, Australia, in 2019 offers a different explanation of the influence of grip strength on golf swings: It’s not really about the grip at all.

During the acceleration (downswing) phase of a tee shot, higher levels of muscle activation have been recorded in the flexor carpi ulnaris. That’s a forearm muscle that begins at the elbow … and ends right at the base of the pinkie finger. “Increased grip strength,” wrote Sheehan, et al., “may positively influence” the activation of this flexor “that occurs just before impact, which contributes to high endpoint velocity.”

Bingo.

Grip strength seems to matter, but not for the hands. For the forearm. That’s where the bulk of the acceleration appears to be generated. But it doesn’t happen without a strong grip.

I do suspect the other studies were probably correct in that doing hand-strengthening exercises at the expense of something else probably is a waste of time. Can’t imagine Mays bolstered his mitts with finger exercises; his hands probably grew, along with his legs and forearms, playing various sports and doing other physical activities from a young age.

Links

The cooling technology at the Summer Games … Could ADHD be a superpower for some athletes? … AI can read athletes’ body language … ‘Malevolent’ traits may be key to athletic success … Video games and neural plasticity: StarCraft II expertise linked to enhanced brain connectivity … Performance data has finally come to sailing … Why does Bryson DeChambeau float his golf balls in salt water? … Blood sugar goes low and stays low with exercise at this time of day … How science built the best shooter in the NBA draft … The new calculus of summer workouts … What works for golf works for life … Supershoes are reshaping distance running … AI batting buddy

References

Cronin, John, et al. "A brief review of handgrip strength and sport performance." The Journal of Strength & Conditioning Research 31.11 (2017): 3187-3217.

Hughes, Shawn S., Brian C. Lyons, and Jerry J. Mayo. "Effect of grip strength and grip strengthening exercises on instantaneous bat velocity of collegiate baseball players." The Journal of Strength & Conditioning Research 18.2 (2004): 298-301.

Kohn, Jordan N., et al. "Strength, speed, and anthropometric predictors of in-game batting performance in baseball." Journal of Sports Sciences (2024): 1-8.

Sheehan, William B., Rob G. Bower, and Mark L. Watsford. "Physical determinants of golf swing performance: A review." The Journal of Strength & Conditioning Research 36.1 (2022): 289-297.

The quiet eye

A good way to test your visual perception is to look directly at your eyes in a mirror, first the left and then the right. Then back to the left. What you’ll notice is … well, nothing. You wont actually see your eyes moving. You can try this with your spouse, though, staring deeply into their eyes, which I definitely recommend if you really want to creep them out. But also what you will see is their eyes moving. From this, we know it’s happening.

Why can’t we see our own eyes moving?

Our visual perception system doesn’t allow us to. Our eyes are actually moving pretty much constantly. In addition to regular blinking to moisten the lens (or refresh the brain - hmm), our eyes do something called saccades. These are short, rapid shifts that occur about 4 to 5 times every second. They transpire so quickly that we generally don’t notice them. In fact, we suppress noticing them.

Our eyes are constantly scanning the scenes in an environment, whether it’s the words on this page, the cars on the highway, or the receivers on a football field. It’s most likely a defense mechanism we’ve evolved with. A fancy little trick also evolved along with it. See, even as our eyes are moving and scanning, we generally perceive most scenes as stable, thanks to the brain. During a saccade, it’s been hypothesized that we are effectively blinded. It’s only for a short duration, but the brain has to fill in those saccadic gaps 4 to 5 times every second. Our vision is essentially a story the brain is telling ourself.

Saccades also happen to be quite helpful for keeping track of things in a fast-moving sport. In honor of the Stanley Cup Finals starting tomorrow night, let’s consider a hockey goalie, for instance. Hockey is an incredibly frenetic activity in a small environment played on ice. To keep track of opponents and teammates and the tiny black puck that are all zooming around the rink, it would behoove a hockey goalie to be able to make short, rapid shifts of the eyes.

But when a goalie is preparing to face a prospective slap shot from an opponent, perhaps a rapid eye shift isn’t the best formula for success. Blindness doesn’t bode well for a strong save percentage.

So what is a Sergei Bobrovsky or Stuart Skinner actually doing with his eyes?

Train your gaze

The seminal study on hockey goaltending comes from two Canadian researchers (fittingly) at the University of Calgary in 2006. Their names are Joan Vickers and Derek Panchuk, her graduate student.

Panchuk and Vickers weren’t the first to examine eye movements in hockey goalies while they faced shots in a live setting. The first (Bard & Fleury, 1981) was a bit constrained technologically, but it found that expert goalies predominantly fixated their vision on the puck, rather than the shooter, to make saves — a fairly significant finding at the time (ie., keep your eyes on the ball).

To their credit, Panchuk and Vickers point out that a lot of shots in hockey transpire in less than two-tenths of a second, faster than the visual system can process. And yet goalies still save 90 percent of their shots. Not all of this is just luck.

In their study, Panchuk and Vickers gathered eight elite goaltenders from Canadian universities around Calgary and several elite shooters to feed them wrist shots from 5m and 10m out, distances at which the puck would travel below the threshold of human visual perception. They used an innovative wireless headset that was able to track both the goalie’s eyes as well as whatever target they were looking at simultaneously.

What they found was that the most successful goalies trained their gaze directly on the puck for as long as a full second before the shot was released. This direct focus was not broken at all prior to the onset of the saving movement.

I suppose this finding may sound fairly obvious — again, we’ve all heard “keep your eyes on the ball/puck.” But when testing novice goaltenders on the same task, Vickers and Panchuk discovered that their gaze was typically … all over the place. It was saccadic chaos. Elite performance requires the opposite.

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Furthermore, Vickers and Panchuk have gone on to show that the quiet eye is critical for goalie performance even when the path of the puck can’t be predicted. More recently, they tested goalies’ gaze on shots that are deflected, putting fiberglass boards at an angle off the net to produce unexpected deviations in the puck’s flight path.

Again, they found that the goalies had the most success when they located the puck earlier and maintained their gaze on that location for longer, even for shots that they knew wouldn’t be straight. The “optimal” time to locate the puck was as much as 2 seconds before the shot’s release, and the “optimal” duration of that gaze went for 2-2.3 seconds—extending early into the shot’s flight.

That’s not to say the goalies didn’t try to follow the puck after the deflection, but most of the time their gaze simply arrived too late. But it didn’t matter. They were able to stop the shot with what’s become known as the Quiet Eye.

Origins of the Quiet Eye

By the time Vickers had started looking into hockey goaltending, she was already a monumental figure in the study of elite performance. She coined the term for what all this eye fixation business was about. She called it the Quiet Eye, and study after study going back to the early 1990s had confirmed its presence in expert putting, free-throw shooting, marksmanship, table tennis, volleyball returning, even surgical knot tying.

Before starting her PhD at the University of British Columbia, Vickers was an accomplished volleyball and basketball player, and then a coach and athletic director at several high schools and colleges. She traces her interest in sports perception back to a specific, high-pressure volleyball game in which she was serving. All she can remember is that, as the intensity grew, her focus magnified onto a specific back portion of the ball she was targeting to hit with the heel of her hand. The fine-tuning of this concentration should sound familiar to anyone who has lined up a putt, leaned in for a tennis serve, or readied a free throw.

I think there sometimes may be a tendency to conflate a Quiet Eye with focus or concentration, both of which are also necessary for performance in key moments.

Quiet eye, however, isn’t a manifestation of something psychological. It’s perceptual.

An important characteristic of this particular fixed gaze is that it is the last eye movement before the onset of the movement to block a puck or take a shot. This suggests that it plays a role in the planning of the movement. It’s not just “keep your eyes on the ball.” It’s, “keep your eyes on the ball in order to give your body the opportunity to hit it.”

Another noteworthy observation: Across Vickers’ 20+ years of research on this, she has consistently found that the Quiet Eye of elite performers is longer and started earlier than lower-skilled performers. In other words, this isn’t just about having superior vision — Vickers (to my knowledge) has never correlated an athlete’s 20/20 vision to Quiet Eye. Rather, elite performers find ways to see critical information sooner. And they fixate on that information for longer.

We are routinely dazzled by goaltenders’ cat-like reflexes and flexibility, but the movement doesn’t get initiated with a Quiet Eye locating and fixating on the puck.

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Eye for an eye

One of the nice things about the Quiet Eye theory is that it has been tested on performers who are actually performing. This wasn’t borne in a lab and tested via simulations or recreations that strain credibility, it’s been fleshed out on the ice and turf with real players wearing real equipment and battling conditions and fatigue and other realistic elements. And this is a tremendous testament to Vickers and her quest for authenticity in the pursuit of fundamental answers.

There are also those who bristle at the notion of any one “optimal” way of perceiving that’s supposed to be applied to an entire population, and I get that.

So it’s necessary to point out some that Quiet Eye has some limitations. A 2022 study by Ben Franks, et al., illustrated one, by looking at the Quiet Eye of professional soccer goalies—with a wrinkle. The researchers set up a penalty kick between one shooter and one goaltender, but they granted the shooter the freedom to dribble the ball liberally, as if taking a real in-game penalty kick.

Their findings showed that the goalies actually expressed a lot of variability in how and when each keeper manifested his Quiet Eye. There was no correlation between the duration of the Quiet Eye and the outcome of the save. And some of the goalies routinely fixated on the ball, while others fixated on the shin area of the kicking leg. (A tentative link was found between the goalies with quicker reaction times and their gaze being on the ball - perhaps because a faster goalkeeper knows he can wait longer for more information and still be able to recover).

Quiet Eye is a “useful tool,” Franks wrote, “in which to investigate how skilled performers regulate action through fixating on visual information within the immediate environment before the onset of a goal directed movement.” Beyond that, however, the sweeping generalizations about how athletes are to use Quiet Eye don’t allow for enough breathing room for individual variation.

This is true probably more so for dynamic actions like goaltending or baseball hitting in which performers have developed a host of subtle or idiosyncratic tricks and cues to prepare them for their task. There are a lot of ways to save a shot.

But an “optimal” duration of Quiet Eye probably can be more convincingly pinned down in more static actions, like golf putting or free-throw shooting. Here are at least two findings that support it:

Evidence from quiet eye training

The next time you do find yourself standing over a putt, here’s a tip based on a Quiet Eye study from Sam Vine, Lee Moore, and Mark Wilson in 2011:

1. Assume your stance and align the club so that your gaze is on the back of the ball.

2. After setting up over the ball, fix your gaze on the hole. Fixations toward the hole should be made no more than 3 times.

3. The final fixation should be a Quiet Eye on the back of the ball. The onset of the Quiet Eye should occur before the stroke begins and last for 2 to 3 seconds.

4. No gaze should be directed to the clubhead during the backswing or foreswing.

5. The Quiet Eye should remain on the green for 200 to 300 ms after the club contacts the ball.

After following this protocol in the laboratory, expert putters not only performed better putting in the lab. They took the lessons from this training and saw improvements on the course, improving the amount of holed putts within 10 feet by 5 percent over the course of the next 11 rounds!

“The findings suggest that QE training may provide a useful psychological technique,” the researchers wrote, “as part of a pre-performance routine, to aid performance under pressure and improve performance in competitive environments.”

There are many other examples like this. One of the most convincing recently was work by Daniel Laby, a sports vision researcher in New York, who used eye-tracking goggles with NBA players for free-throw shooting. The heat maps below show where their gaze was focused, and you can see the differences for yourself:

Exponential Athlete podcast

In other news, I was asked to be on Ken Jee’s excellent Exponential Athlete podcast recently. It was great! I highly recommend following him, and I hope you’ll give our conversation a watch/listen:

Links

Neuroscience is becoming a gamechanger in football … Pupillometry as a new window to player fatigue? A glimpse inside the eyes of a Euro Cup Women’s Basketball team … Why triathletes can’t sleep … Brain scans of jazz musicians reveal how to reach a ‘flow’ state … 1 in 5 young athletes meet criteria for pre-hypertension … Female athletes perform better on their period … Olympian embraces brain training in preparation for Winter Games … Urban athlete superpowers … How climate change is changing sports

References

Franks, Benjamin, et al. "A descriptive case study of skilled football goalkeepers during 1 v 1 dyads: a case for adaptive variability in the quiet eye." Frontiers in Psychology 13 (2022): 908123.

Laby, Daniel. "Visual fixation in NBA free-throws and the relationship to on-court performance." Journal of Sports and Performance Vision 2.1 (2020): e1-e7

Panchuk, Derek, and Joan N. Vickers. "Gaze behaviors of goaltenders under spatial–temporal constraints." Human movement science 25.6 (2006): 733-752.

Panchuk, Derek, Joan N. Vickers, and Will G. Hopkins. "Quiet eye predicts goaltender success in deflected ice hockey shots." European journal of sport science 17.1 (2017): 93-99.

Vine, Samuel J., Lee J. Moore, and Mark R. Wilson. "Quiet eye training facilitates competitive putting performance in elite golfers." Frontiers in psychology 2 (2011): 8.

A few years ago, there was a pitcher in the Yankees organization named Pat Venditte.

Readers of this newsletter might remember Pat Venditte. It’s hard to forget about him, considering his unique ability. He was the only pitcher in professional baseball who threw with both arms.

Venditte touched the upper 80s with a slider and a curveball with his right arm, his naturally dominant arm. With his left, he threw sidearm in the mid-80s with a slider as well. I recall he used a custom, six-fingered glove that could be worn with either hand, although MLB would later adopt a rule (the “Pat Venditte Rule”) requiring that ambidextrous pitchers must not switch throwing arms in the middle of an at-bat. The back-and-forth with a switch hitter was delaying the game.

A general manager’s dream: Two pitchers for the price of one.

Venditte was a unique attraction, and a fascinating case study, but he struggled to get beyond the gimmick. His velocity was pedestrian; any advantage he gained by being able to face same-handed hitters was negated by ultimately mediocre stuff. It was a shame, too, because being the only professional pitcher doing it, Venditte seemed to represent the “ceiling” of what a switch pitcher could offer.

Until now.

There’s a pitcher for the Mississippi State baseball team named Jurrangelo Cijntje who throws 99 MPH with his right AND throws 95 MPH with his left arm. He has an 8-1 record and a 3.48 ERA in 14 starts this season for the Bulldogs, who are ranked 14th in America.

According to MLB.com, Cijntje (pronounced SAIN-je) grew up in Curacao, where he started playing baseball with both hands at age 6. He is naturally left-handed but says he writes with his right arm and often eats with his left. For a while, he pitched primarily as a righty, because he also played catcher and shortstop — two positions that favor right-handedness. In high school, when it was discovered how strong and accurately he could still throw with his natural arm, coaches began to work with him on throwing with both.

With all due respect to Shohei Ohtani, I’m more impressed by a switch pitcher who can dominate hitters with either arm. And here’s why.

Handedness

The origins of human handedness trace back 7 million years or so, and all the theories about why are understandably fuzzy. The story I like most is almost certainly apocryphal. In the early days of our bipedal existence, females did most of the work (some things haven’t changed). They were the principal hunters of the group, and they were often toting babies around, too. Because females carried the babies in their left arms, cradling the head against the woman’s chest and heartbeat, it freed up the right arm for throwing projectiles at prey. Over time, right-arm throwing accuracy conveyed a competitive advantage, producing more right-arm dominant offspring. Eventually, one of these offspring would turn into Nolan Ryan.

I don’t know! It’s a nice theory, and it does help to explain one thing: why humans are the only species to express a strong affinity for one arm vs. the other.

This affinity runs deep. A study of the wear patterns of Neanderthal teeth suggested that 88 percent were right-handed. A survey of cave-dwelling artwork dating back 5,000 years showed a clear preference for the right hand. Babies almost always suck the thumb on their right hand in the womb. As I wrote about in my book, in the early 20th century in London there was an Ambidextral Culture Society that formed as a progressive rejection of handedness and an effort to promote “balance” and “flexibility.” Members learned to play piano with one hand and write with the other. But eventually, the whole thing grew tiresome.

That’s not to say handedness cannot be acquired. There is considerable debate about how much of handedness is actually inherited. About a quarter of monozygotic twins — those who share the same genes — actually differ in their handedness. That fits with a 2020 meta-analysis (a study that collects research from a multitude of other studies) on human handedness led by Marietta Papadatou-Pastou, which placed the heritability of handedness at about 24 percent.

Handedness may also be a reflection of our environment, and the societal pressures that force us (directly or indirectly) to choose one side or the other. Papadatou-Pastou notes that left-handedness is much less common in Asia; specifically, less than 1 percent of children in China are left-handed. “This is most likely due to differential cultural pressures,” she wrote.

Chris McManus, who wrote the book, “Right Hand, Left Hand,” based off decades of his own handedness research, has found that the prevalence of left-handedness in society has experienced profound ebbs and flows over the years, dipping below 4 percent in the 1890s and early 1900s and surging above 10 percent in the late 1940s and 1950s. McManus ascribes these historical shifts to social influences that then lead to genetic differences. At certain times — such as during the Victorian era — left-handers were bullied or ostracized or forced to conform to the more “dignified” right-handed ways (a lot of mythology associated lefties with the devil - “sinister” means left in Latin). This might have made left-handers less likely to marry and produce offspring to continue their left-handed lineage.

Indeed, at the end of the nineteenth century, McManus found that left-handed couples had fewer children than right-handers. Nurture influenced nature.

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Hook and lateral

The brain is divided into two hemispheres, the left and the right, and their responsibilities are generally believed to run contralaterally: i.e. the left brain controls the right hand. You’ve probably heard folklore about the polarization of the brain and which side is more “analytical” vs. “creative,” but I’m going to sidestep that rabbit hole (other than to say that the myths and simplifications tend to stray from neurological facts).

Brain lateralization, however, might be able to help explain one question that often comes up in sports: Why are more athletes left-handed?

The Papadatou-Pastou meta-analysis found that 15 percent of “sporting elites” were left-handed, compared to 10 percent of the general population. I honestly don’t know what she included as a “sporting elite,” but anecdotally there seems no question regarding the prevalence of left-handers, particularly in sports like baseball and hockey. The most common explanation is that being left-handed wields a tactical advantage: lefties get more opportunities to practice against right-handers than right-handers get against lefties.

Consider someone like Jalen Brunson, the crafty guard who dazzled for the Knicks this postseason. His left-handed shooting motion may well endow him with a split-second advantage over defenders more accustomed to blocking shots from the opposite side. The majority of NHL players actually shoot left-handed, primarily because Canadian players were taught that way to better control the stick (more Canadian golfers also swing left-handed - but it doesn’t actually mean they are natural lefties).

And perhaps there is something else going on. A study by Florian Loffing in 2017 took a closer look at the data. It’s not just that lefties are more prevalent in elite sports. But they are far more overrepresented in time-pressure sports, such as baseball, cricket, and table tennis. In these activities, the percentage of left-handers increased to more than 30 percent. Left-handedness is more common in table tennis than in all the other racket sports (tennis, badminton, and squash) combined. “Achievement may depend to a larger extent on basic physiological and psychological aspects (e.g. agility, concentration, emotion regulation) irrespective of an opponent's laterality,” Loffing wrote.

What “physiological and psychological aspects”? Well, the right brain has been linked to visuospatial processing and deemed by some to be more “visually intelligent” than its counterpart. Numerous studies on elite athletes have noted differences in activations and grey matter in brain regions like the right insula, right fusiform gyrus, right cerebellum, right hippocampus, and others.

Whether or not any of these findings can be neurologically linked to better time-pressure performance in sports with the left hand, I don’t know. I’ve yet to come across a study that explores this. But Loffing’s data would suggest something is going on.

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It almost goes without saying that ambidextricity is easier to impress upon a child who is still developing, much like it’s easier for a kid to learn a new language than an adult. Their brains are still forming; their neuroplasticity, to use the technical term, is much more robust. It’s not a surprise that the pitcher Cijntje started using both hands at age 6. Whether “switch pitching” confers an advantage for him, or not, remains to be seen.

Lefties and righties

Regardless, we are more bimanual than we often think.

In the 1980s, French psychologist Yves Guiard looked closely at handedness and concluded that performance asymmetries were probably overstated. In most tasks, even writing and eating, we may have one arm that we use repeatedly, but that doesn’t mean the other one is useless. While writing, Guiard showed, the nondominant hand often plays a covert role adjusting the paper in anticipation of the other hand’s pen movements.

“If we think of a violinist,” Guiard wrote, “it is rather obvious that neither of his or her hands is dominant in any clear sense: Each of the two manual roles (grossly speaking, manipulating the violin, manipulating the bow) is crucial and difficult.”

As I type this, I’m coordinating both sets of fingers simultaneously. Driving occupies two hands (hopefully). But even in tasks involving a dominant hand, Giuard observed, the nondominant hand is almost always involved in “framing” or “stabilizing” the activity. Think of cooking or cutting with a sharp knife. This stabilizing action actually typically begins “before the action of the other member of the pair,” Guiard wrote. In this sense, the hands work as a partnership. Said Guiard: “The left hand knows what the right hand is planning, and the right hand knows what the left hand just did.”

Work by neuroscientists Fred Dick and Joern Diedrichsen at the University College London confirms this theory — and goes even further. In one study, the researchers took a group of expert violinists from the Royal Academy of Music and had them play the instrument inside an fMRI scanner. Except the instrument they were asked to use was the exact opposite of what they’d been trained on. A righty, for instance, was given a reverse violin that required that the bow be swung with the left and the strings to be manipulated with the right.

The violinists initially reacted quite angrily, the researchers told me. “They said, ‘No, I cannot possibly do that!’”

As it happened, though, they actually could. In fact, after a little bit of time, they could play their opposing instrument quite well — even faster than novice violinists using their correct hands. It seems that, from all those years of practice, the brain was soaking up a lot of information about what both hands were doing. When pressed to perform, it was able to transfer that information across the neural hemispheres without a huge gap in ability. [The study by Dick and Diedrichsen got held up after Diedrichsen left UCL, but hopefully they can publish it someday]

Another (possibly apocryphal) story before wrapping this up. Larry Bird was coaching the Indiana Pacers when they drafted a high-school phenom named Jonathan Bender. Bender - being a young hotshot - wasn’t familiar with Bird’s legend, so he challenged him to a game of one-on-one. Bird, even in retirement, won easily.

Afterwards, Bender said to Bird. “Damn, I didn’t know you were a lefty.”

Bird shrugged and winked.

Links

NBA teams’ performance shifts with time zones … Lessons from Sports Psychology Research … Players of the NBA G League donned wearable technology daily during training to conduct biomechanical, kinematic and force-producing assessments … Elite runners live longer … 6 Olympic athletes reveal how they’re preparing for the Paris Games … The most lavish ultra-marathon ever … How to motivate mentally well athletes … How do the world’s best athletes handle pressure? … A high velocity usage tax: A proposal to protect pitchers … Cold plunges may reduce muscle growth … Mouth rinsing carbs may improve performance in Romanian deadlift … Olympic Dodgeball

References

Corballis MC. Left brain, right brain: facts and fantasies. PLoS Biol. 2014 Jan;12(1):e1001767. doi: 10.1371/journal.pbio.1001767. Epub 2014 Jan 21. PMID: 24465175; PMCID: PMC3897366.

Guiard, Yves. "Asymmetric division of labor in human skilled bimanual action: The kinematic chain as a model." Journal of motor behavior 19.4 (1987): 486-517.

Loffing, Florian. "Left-handedness and time pressure in elite interactive ball games." Biology letters 13.11 (2017): 20170446.

McManus, Ian Christopher. "The history and geography of human handedness." Language lateralization and psychosis (2009): 37-57.

Papadatou-Pastou, Marietta, et al. "Human handedness: A meta-analysis." Psychological bulletin 146.6 (2020): 481.

What’s in the brain of an expert umpire?

If you’re Yankees manager Aaron Boone, you’d probably say “nothing.” Kidding! Well, but it does seem that, for whatever reason, there’s been more scrutiny on umpiring in the early days of this Major League Baseball season than in other seasons in recent memory. I don’t know why! Everyone just seems … testier.

But I think it’s helpful to know why umpiring is not — and might never be — as perfect as fans and players and managers often expect. In this week’s newsletter, I’m going to offer three science-based reasons why. One is grounded in neuroscience, another behavioral psychology, and the third is … well … climate change.

I’m not here to dunk on umpires. To the contrary, I hope this offers some perspective as to why umpiring is so hard — or, at least, what umpires are up against. Some (but not all of it) is out of their control.

A number of studies, for example, have circled around one umpiring blind spot: Left-handed pitchers.

Here, I’ll give umps a pass. In general, left-handedness bestows a slight advantage to performers in many sports because left handers are less common, therefore making them harder for opponents to visually anticipate. Umpires, it seems, are just as fallible. A review of PitchF/x data from the 2010-2013 seasons found that, on average, umpires shifted their strike zone by several inches to the left during matches between a left-handed pitcher and a right-handed hitter.

A recent study done by researchers in Taiwan recruited 16 professional umpires from the Chinese Taipei Baseball Association to undergo a brain scan while being asked to call balls and strikes from inside the bore of an fMRI machine. Sure enough, behaviorally, even expert umpires were less accurate judging pitches thrown by a left-handed pitcher than a right-handed pitcher. What’s interesting is what the fMRI scans revealed about why that might be the case.

An umpire’s blindspot

The brains of the expert umpires responded differently to pitches thrown by a lefty vs. a righty. When a right-hander threw, there was “substantial engagement” of brain regions known as the Action Observation Network (AON), cerebellum, and dorsal striatum (caudate) — all areas involved in decision-making and the perceptual processing of visual information. When judging pitches from a southpaw, “these activations were weaker,” the researchers observed. The suggestion here is that seeing pitches from a lefty did not trigger the same forceful and decisive judgments as pitches from a righty.

There was also noticeably lower activity in a region known as the premotor cortex, an area shown to be heavily involved in predicting dynamic events — and thus preparing the body to move. That implies that umpires weren’t just having more difficulty processing what they were seeing as it was unfolding. They were less able to predict the trajectory of a ball or strike thrown by a left-handed pitcher, which caused them to be less decisive about what the pitch actually was.

The evidence that handedness seems to deceive umpires’ brains helps to understand why it might seep into their pitch-calling behavior. The study was a small sample size, and an experienced ump should be comfortable enough seeing left-handed pitchers to be able to mitigate (or compensate) for any perceptual lags.

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The Umpire’s Fallacy

But the neural underpinnings of an umpire’s decision-making only explains so much.

Umpiring is also a mind game. There’s pressure, stress, fatigue, ego — all hallmarks of a competitive athlete. Except that fans aren’t paying to watch you perform. In fact, they hate it when you get in the way.

One of the most fascinating studies on umpiring was published in 2016 by economists Daniel Chen, Tobias Moskowitz, and Kelly Shue that examined a phenomenon known as the “gambler’s fallacy,” a term first coined by Daniel Kahneman and Amos Tversky in the 1970s.

The “gambler’s fallacy” is the well-documented tendency for people to assume that, if something has occurred more frequently than expected, it is less likely to occur in the future. A gambler at the roulette wheel, for instance, might expect that the ball will land on a Black number following a streak of Red numbers, even though the odds of it happening are unchanged. It’s the age-old misconception that something is “due.” And the economists found that this bias against streaks can easily creep into our decision-making.

They highlighted three examples. A review of more than 150,000 U.S. asylum court decisions by 357 different judges found that they were less likely to grant asylum if they had just approved the previous applicant. They became even less likely to grant asylum if they had approved the previous two applicants. It’s an incredible finding.

It matches what they found about loan officers who make decisions on underwriting enterprise loans: They’re more apt to deny the current loan application if the previous one just got the green light. Ouch.

And so you might already guess where this is going with baseball umpires. Indeed, they are less likely to call a pitch a strike if the two most recently called pitches were also strikes. The effect was even bigger if the third pitch in the sequence was a “borderline” strike — pitchers are not going to get that call.

Let’s pause for a second to soak in the implication of this. An umpire has an implicit strike zone. He has a brain that can visually process and make decisions on whether a pitch falls within that strike zone. And yet, 2-5 percent of the time, he will overrule both of these concepts simply because it would seem too weird for three strikes to be thrown consecutively. Wow.

Moskowitz, et. al, analyzed 127 different Major League umpires in their dataset. Every one of them fell prey to the gambler’s fallacy.

Something in the air

We’ve talked about the neural processing of umpires, and how it may be undermined by their own psychological biases. But what about when an umpire’s decision-making on a certain day is simply … cloudy?

That was the notion behind a 2018 study in the Journal of the Association of Environmental and Resource Economists, which looked at how air quality might impact mental performance in a highly focused task—in this case, baseball umpiring. The researchers analyzed more than 623,000 pitches called by 86 umpires between 2008 and 2015 and tracked whether pollution levels in the area (as measured by the nearest monitoring station) had any influence on their accuracy.

They found that a 1 ppm increase in the amount of ambient carbon monoxide in the air around the ballpark caused an 11.5 percent increase in the propensity for umpires to make incorrect calls, or roughly 2 incorrect calls per 100 decisions. An increase in other, so-called fine particle pollutants in the ambient air likewise contributed to a tougher night behind the plate.

So the next time an ump blows a call against your favorite team, at least now you’ll have some ideas as to why.

Links

Are women better endurance athletes than men? … When is the best time to work out? … New research on why athletes shouldn’t rush back from ACL tears … The elusive “fourth dimension” of endurance … Dehydrated athletes run slower … English cricket club using AI to select lineups … Is Athletes’ Sixth Sense Real, or a Postdictive Reconstruction? … They’re young and athletic. They’re also ill with POTS … Keep winning at tennis? You “see more images” per second than others … Training strategies of 10,074 athletes from 121 countries based on human development index in early COVID-19 lockdown … Discus thrower breaks oldest track & field world record … Why cocaine is considered performance-enhancing for athletes

References

Chen, Yin‐Hua, and Shih‐Kuei Huang. "The influence of pitcher handedness on pitch‐calling behavior: Insights from fMRI study on baseball umpires." Psychophysiology 61.3 (2024): e14501.

Chen, Daniel L., Tobias J. Moskowitz, and Kelly Shue. "Decision making under the gambler’s fallacy: Evidence from asylum judges, loan officers, and baseball umpires." The Quarterly Journal of Economics 131.3 (2016): 1181-1242.

Deshpande, Sameer K. and Wyner, Abraham. "A hierarchical Bayesian model of pitch framing" Journal of Quantitative Analysis in Sports, vol. 13, no. 3, 2017, pp. 95-112. https://doi.org/10.1515/jqas-2017-0027

Archsmith, James, Anthony Heyes, and Soodeh Saberian. "Air quality and error quantity: Pollution and performance in a high-skilled, quality-focused occupation." Journal of the Association of Environmental and Resource Economists 5.4 (2018): 827-863.

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The “no practice” way

Cam Smith is a 30-year-old Australian currently playing on the LIV golf tour who is widely recognized as one of the game’s great putters.

He led the PGA Tour in fewest average putts per green in regulation two years in a row. En route to winning the Open championship in 2022, Smith rolled in 255 feet of putts in the second round alone. Do the math. That’s more than 14 feet per putt. It’s a figure that’s never been reached, anywhere, anytime, on the PGA Tour since it started keeping such stats in 2004.

Yeah, so Smith’s a remarkably good putter, which has naturally prompted a lot of inquiry into what makes him so good. There have been several articles and videos about his mechanics and his practice routines and his mental imagery. And there’s something else:

I’ll admit I am intrigued by this. I play golf, and as long as I can remember, I’d been taught that it was good, after lining up a putt, to simulate a few strokes before stepping up to the ball. It’s like taking a few cuts in the on-deck circle. Given that golf doesn’t have a clock, it never occurred to me that there may be a downside. But Smith apparently thinks there is.

“Rather than feeling through body motion, I like to just visualize it,” Smith said. “I like to take a really long look at the hole before I putt and see that ball dripping over the edge and then just hit it.” Golf.com

A TikTok video about Smith’s “secret to putting” probes a little deeper. It says that “neuroscience might explain why” Smith doesn’t take a practice stroke. Hmm.

@golf_manualShould you take a practice stroke before you putt? 🤔 Cam Smith doesn’t, Neither does Rory, and neuroscience might explain why! Do you take practice strokes before you putt? #golf #putting #shortgame #golftips #golflesson #golfmanual #golf_manual

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The video references a scientist named Izzy Justice who has supposedly “scanned 6,000 brains while putting” for a recent study. That’s, well, A LOT of brains. It’s hard to fathom that he somehow got enough volunteers to fill a minor-league baseball stadium and don EEG caps while putting. Were they human brains? It’s unclear. I couldn’t find any such study, or any previously published studies by Justice on Google Scholar or PubMed.

I reached out to Justice for more details on his findings, his methodology, and where any of his research can be found. Haven’t heard back.

So for now, let’s just say I’m dubious of the reporting that “the results found that doing a practice stroke had a negative impact on the brain 95 percent of the time” and leave it at that.

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Worse, the video goes on to explain that “putting is difficult” because “we don’t keep our eyes on the target” (?), which “means our brains have to remember where the target is.” Practice strokes “distract our brains from the target,” and then “communication from brain to muscles is scrambled, leading to missed putts.”

Sigh.

That sound you hear is me banging my head against the desk.

Listen. I know dissection of a TikTok video is uncouth and not worth the time, but if the video is suggesting that practice strokes will give you an actual stroke then something must be said. Must be said.

I don’t even know where to begin on the whole “eyes on the target” theory in there either. No, golfers do not keep their eyes trained on the hole as they putt — and this is not some unique golf phenomenon! A whole established line of scientific theory, known as the Quiet Eye as coined by Joan Vickers, is backed by study after study on high-level athletes in sports from hockey to basketball to, yes, golf — and the consistent theme throughout is that action moves too quickly for the eyes to follow, so performers focus intently on some fixed part of the ball or body in order to predict what’s going to happen. There are schools of “Quiet Eye Training” for golf that tell you to fixate on the back of the ball while putting. The brain does just find remembering where the target is. (Perhaps this is a post for another day…)

But, again, Cam Smith and others like Patrick Cantlay and Rory McIlroy have had success abandoning the practice stroke. So is a warmup swing overrated? Or, worse, detrimental?

An actual study on practice strokes

There is, in fact, an excellent study on whether practice strokes are helpful or harmful for putting that did not require the scanning of 6,000 brains.

Yumiko Hasegawa, a sports psychologist at Iwate University in Japan, and two others (Akito Mirua, and Keisuke Fujii) published a study in 2020 with the affirmative title that “practice motions” do “drive the actual motion of golf putting.” Among their findings: players are more accurate when they take a practice stroke that’s designed to mimic the stroke they’re intending to make.

While this sounds totally obvious, the researchers’ study design to reach that conclusion was actually quite elegant and fascinating. Their study included 10 professional golfers and 11 amateurs (really intermediate golfers with a median handicap of 14.5 — my kind of player). Each player took 48 putts toward a target, which was a golf-hole sized light beam projected on the ground. Before putting, they were allowed to make practice strokes toward the target they saw projected. But when they stepped up to the ball, the target disappeared. At random, it might reappear in the same spot it was before; other times, it was moved closer or farther away.

The players were given just one instruction: “Make practice strokes with the intention of hitting the presented target.” They never lost sight of the target, and there was no time limit with which they needed to hit the ball. They could also take as many practice strokes as they prefer (players averaged 2.68 practice swings per attempt). On a few trials, the players were also asked to hit without any practice strokes at all.

If these practice strokes mattered, the researchers surmised, they should improve the accuracy of the putts toward the unchanged target, since that’s the target that they were practicing to reach.

What happened?

When the target changed, accuracy dropped.

Here’s a dot plot of the putting results gathered by the researchers:

Left side are the professionals and right are the amateurs (in case you couldn’t tell from the scattering). Blue dots represent the putts when the target was consistent with the practice strokes (equal); red are when they target distance changed (confusing). Green is when practice strokes weren’t allowed (no). And the point at which the black horizontal and vertical lines cross indicates the center of the target.

Clearly, the pros are more accurate than the amateurs in any condition, but everyone was consistently more accurate when they were given a target that matched what they had seen while taking practice strokes. Even the pros had some struggles when the target was “confusing,” particularly if the distance was shorter.

But why were the amateurs so much worse? The researchers used motion-capture cameras to record the kinematics of the club heads. They found that the impact velocities of amateurs were way higher than professionals when they couldn’t rely on their practice strokes. This caused them to hit the ball harder than they should. It’s a function of motor control: professionals with a lot of practice are more adept at controlling precision forces. For amateurs, “practice strokes may function as a warm-up,” the researchers said, “that prevents excessively hard hits during actual strokes.”

So there is a function to a practice putt if you’re an amateur: It’s to prepare your motor system for the impact velocity necessary to control the distance on the putt.

This requires taking a practice stroke that accurately represents what you want the real stroke to be, and velocity here seems to be the key. If you’re lining up a 4-foot putt, try to make sure your practice swing reflects that distance. Gauging that tempo requires practice and experience. But it seems that an amateur player who doesn’t take a practice stroke will have a harder time preparing the motor system for that appropriate impact velocity.

I’ve heard this from golf coaches who advocate against practice strokes: Your practice stroke is inherently different than your stroke when making contact with a ball. This is probably true, but then why practice anything? Anything that’s simulated is inherently going to be different from the task in the field; what two shots are ever the same? Practice is about building a motor action, a “muscle memory,” that can be retrieved quickly and consistently while remaining flexible enough to handle uncertain scenarios.

But is there any benefit to practice strokes for a pro?

Well, something did strike the researchers as odd: When the target was positioned much farther away than it had been during their practice stroke, or they had no practice stroke at all, the professionals undershot the ball a lot more often, more so than even the amateurs. “It is possible an increased number of undershoots from only a few experts could have caused these results,” the researchers said, but analyzing individuals also revealed an exaggerated tendency to undershoot the target.

So, from this study, practice strokes for a professional seem to have the opposite benefit as they do for an amateur: Instead of assisting motor control, they seem to aid distance control.

The pros did exhibit a method of counteracting the “confusion” when shown a target they hadn’t just practiced for: They paused for significantly longer before taking a shot. That extra pause was because they “took longer to plan their motor execution,” the researchers speculated. They had to think harder through their shot.

Why do practice strokes matter?

I think it’s still important to unpack a little bit more about why a practice stroke might or might not be helpful.

Hasegawa et. al pretty nicely suggests there are motoric benefits to establishing the parameters of what you’re targeting — how hard or soft you want to hit it — with a practice stroke whether you’re an amateur or a pro (but especially if you’re an amateur).

Another thing to consider, though, when practicing or warming up for any skill is what am I actually practicing.

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I like to say something that sounds fairly obvious: Your brain is not there to just play golf. No one was born to play golf. Your brain has a lot of other responsibilities, such as, you know, keeping you alive! Reminding you that you should eat a snack at the turn. Making sure you don’t get run over by a golf cart as you’re walking down the fairway. This sort of thing.

And so when it is time to execute a skillful task, like a putt in a professional tour event, it may require a certain recalibration to tune itself out of “watch out for that golf cart” mode and back into “now I need to putt” mode.

This is achieved through a psychological rejiggering — ie., focus. Sure.

I tend to think it may benefit from a motoric reminder as well. To stick with golf as the example, going from walking down the fairway and pacing around the green to standing static over a ball and delivering a delicate stroke toward a distant target is, well, a lot to ask of your motor system.

For pros, and amateurs, a practice stroke on the putting green might not just be for distance control or motor control. It’s a motor reminder.

Different strokes for different folks

I know there are going to be people emailing me or commenting with the counterargument: If it works for Cam, why fix it?

I recognize that many performers are creatures of habit (and superstition), and pre-shot routines and confidence make up a big part of enabling their “it” factor. Messing with that routine or habit, and thereby shaking that confidence, simply might not be worth it. So if it indeed works for Cam, there probably is no reason to fix it.

I’m simply providing a case, rooted in science, for why practice strokes on the green are beneficial for putting accuracy.

And please let me know next time you see a TikTok video saying “neuroscience explains why.”

Links

Elite athletes demonstrate higher perceptual cognitive abilities compared to non-athletes … “By mastering the art of body language, we can gain an edge, not only by enhancing our own performance but also by influencing the psychological state of those around us.” … Expert cyclists say stuffing a water bottle down their shirt gives them a critical aerodynamic edge. … Why Going on a ‘Sex Ban’ Probably Won’t Help Tiger Woods … The power of human touch: A friendly pat on the back improves basketball performance … How does weed affect a workout? … Does a more diverse team play better? … Does hand size matter in the NFL’s trenches?

References

Hasegawa, Yumiko, Akito Miura, and Keisuke Fujii. "Practice motions performed during preperformance preparation drive the actual motion of golf putting." Frontiers in Psychology 11 (2020): 518391.

Yumiko Hasegawa, Keisuke Fujii, Akito Miura, Keiko Yokoyama & Yuji Yamamoto (2019): Motor control of practice and actual strokes by professional and amateur golfers differ but feature a distance-dependent control strategy, European Journal of Sport Science, DOI: 10.1080/17461391.2019.1595159

Caitlin, Tyrese, and NOAH

Here is a clip of Caitlin Clark shooting. Her form was recently described by The Athletic as “optimal,” if not actually perfect.

Credit to The Athletic on the enjoyable compilation there.

Now, here is a clip of Tyrese Haliburton, the All-Star point guard for the Indiana Pacers. His form was recently (and generously) described by The Wall Street Journal as “unorthodox,” if not “the ugliest shot in basketball.”

It’s not pretty.

But Haliburton, before a recent shooting slump, was on pace to make 40 percent of his 3-point attempts for a fourth consecutive season, the fourth-longest streak to begin a career in NBA history. He competed in the 3-Point Contest at All-Star Weekend again this year after reaching the finals in the contest a year ago.

He can shoot, okay. It just might not look like it.

Aesthetically, Clark’s and Haliburton’s form appears quite different. And I’m here to tell you: That’s okay.

Physics of jump shooting

In 2008, two mechanical and aerospace engineers at North Carolina State University, Larry Silverberg and Chau Tran, analyzed hundreds of thousands of shot trajectories from NBA shooters using a computer simulation. They were looking specifically at free-throw shots, which are the simplest to objectify, but they landed on what they considered to be a few keys for “optimal release conditions” that could apply to any jumper.

1. Shooters should launch the shot with about 3 hertz of back spin, or with the goal that the ball makes three complete backspin revolutions before reaching the hoop.

2. Aiming for the center of the basket decreases the probability of a successful shot by almost 3 percent. Aim, therefore, for the back of the rim.

3. The proper “launch angle” on the shot should be 52 degrees. Roughly speaking, it means that the shot at its highest point is less than 2 inches below the top of the backboard.

4. Release the ball “as high above the ground as possible” along a straight imaginary line between the player and the basket

5. Maintain as smooth a body motion as possible to get a consistent release speed.

“A little bit of physics and and a lot of practice can make every a better shooter,” the authors wrote, adding: “You know who you are, Shaquille O’Neal and Ben Wallace.”

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Now, I have no idea if Caitlin Clark’s typical launch angle on a jump shot is precisely 52 degrees! But the University of Iowa probably does. It also utilizes what’s called the NOAH Basketball system, which tracks how shots enter the rim from a camera positioned above the hoop — similar, in a sense, to what the TracMan does for golf or baseball.

NOAH says that, after witnessing millions of shots, too, it has “cracked the equation” for perfect shooting metrics. Its philosophy is that the ball should enter the rim at a 45-degree angle, which represents the precise amount of arc while reducing the largest amount of variance in depth. As for the depth, the center of the ball should be 11 inches past the front of the rim. (A rim is 18 inches in diameter, so toward the back half — confirming the NC State findings).

45/11. That’s become the NOAH slogan.

Repetition without repetition

What NOAH and the NC State professors are giving you is a lot of numbers and calculations, and I’m not a numbers guy.

Which is why I want to think about what both the NC State professors and NOAH Basketball are suggesting not as analytics but as constraints.

A constraint is… like an obstacle. Your goal is to get from A—>B. You have to do so by factoring in a series of obstacles, C, D, and E.

Let’s say you’re a blacksmith. Dated reference, I know, but bear with me. You’re a blacksmith and you’re hammering. Your goal is to strike an object squarely each time with a hammer. That’s A—>B. Your constraints are that the hammer is heavy, you’re growing more tired with each stroke, maybe the conditions in your workshop are breezy (I don’t know!), or there’s a fly buzzing around your head, or you just had elbow surgery. These are constraints. You have to consistently reach your goal working within these constraints.

Nikolai Bernstein, a Soviet neurophysiologist in the early 20th century, one day was watching a blacksmith do just this. And he noticed something quite interesting. The path of the blacksmith’s hammer was rarely consistent, and yet it always seemed to land squarely on the object each time.

Recordings of hammering movements (Bernstein, 1967); the arm and hammer movements are added for illustration (Sternad, 2006)

Bernstein illustrated that for any goal-directed movement, our central nervous system (CNS) is confronted with an abundance of motor options to achieve it, if you consider things like joint degrees of freedom and muscle activations. This produces, he said, “repetition without repetition,” or a lot of variance in the production of a repetitive solution to a task. We can get to B a lot of different ways starting at A. In fact, the motor system isn’t really designed to function exactly the same way over and over again. There’s stuff like motor noise, feedback, and muscular fatigue that conflicts with our ability to precisely repeat motions. Try signing your name over and over again and see how variable the signature will look. We’re not robots.

This idea has spawned a lot of other ideas about motor control. But where some (but not all) in the sports-science community have landed gets us back to constraints.

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Given that two movements aren’t exactly alike, that variance is inescapable partly because of the abundance problem for the CNS, then how we achieve a movement, frankly, well, doesn’t matter.

What matters about the movement is whether it achieves its goal within the constraints of the task.

Sorry for the jargon! Let’s get back to jump shooting for a moment. And I’m not referring to free-throw shooting here. Shooting within the context of a basketball game. The constraints are the physics of basketball, i.e. that the ball should be launched at a certain angle (52 degrees), and enter the rim at a certain angle (45 degrees), and that it shouldn’t be too far left or right, etc. But there are also constraints like fatigue, sweat on the fingertips, whether a defender’s arm is blocking the path of the ball, and how the CNS executes its motor control.

Clark’s “perfect” shot certainly seems to conform to the physics of basketball, but other constraints are more subjective. If your perfect shooting form doesn’t consistently get over the outstretched hand of a defender, then it doesn’t matter how good it looks. You’re going to need to change it.

Haliburton’s “ugly” shot seems to both conform to the physics of basketball and the subjective constraints that fit his CNS and other physical properties. I can’t imagine how many “shooting gurus” over the years told him to fix his mechanics to create a shot that’s more aesthetically pleasing. I’m glad he didn’t listen. Repetition without repetition.

Fundamentals vs. Constraints

We’ve talked before about the building blocks of skill learning, but I often wonder about the “fundamentals” of any skilled task — how have they been derived? Is it with consideration for the constraints of the task? Or is it to fit some aesthetic ideal of how it should look?

Mechanics are important, yes, but they become superfluous the further they get from the task’s constraints. That is both the physics of how the objective can be optimally achieved and the subjective constraints of the performer.

Coaches generally teach how they’ve been taught, so if they’ve been taught to shoot a basketball with a certain form, that’s probably the form they’re going to teach. Maybe that involves the right hand cradling the ball with the elbow precisely parallel to the ground. Maybe that grants most shooters the best stability to reach the preferred launch angle while initiating the most backspin on the ball.

All good! Then a Tyrese Haliburton comes along, and, well, his body is just different. He’s lankier and twitchier and whatever-ier, and so his route to achieving proper backspin and launch angle is a little different, a little quirky. If he tried to conform to the Caitlin Clark-ideal of a jump shot, he’s then adding constraints to his technique because it’s unnatural, it’s inauthentic. Not what you want. Better to give his CNS the freedom to get him from A—>B.

Apply this thinking in other activities. A golf swing is perhaps the most mechanized action we experience in recreation. Think about all the mechanics you’re told to think about to consistently hit the ball. Some of them are dictated by constraints such as physics or fatigue, but are all of them?

Would some golfers be better off if they were trained simply to think: What’s the goal? What are the obstacles? And how can your movement consistently achieve that goal given those parameters?

Ultimately, that’s what you want. Right?

People often ask, why doesn’t anybody shoot like Larry Bird? Why aren’t there any batting stances like Gary Sheffield or Rod Carew? Why doesn’t anyone throw like Randy Johnson or swing like Jim Furyk? It seemed to work for them! I suspect the answer is that we’ve been coached away from quirkiness, in pursuit of a one-size-fits-all ideal of what the mechanics should look like.

That may appeal to the constraints of physics, but it might fail to account for the theory of “repetition without repetition,” that no two bodies are alike and no two movements can be the same. I suspect it has cost sports a lot of colorful and memorable characters. That’s a shame.

What’s the downside to being perfect? It’s sorta, kinda dull.

Links

Do baseball scouts have a future? … First ECG study of WNBA players finds lower rates of abnormalities than men … “Boxer is Using Science to Track Her Brain Health” … How Do Olympic Athletes Sleep? Not well … Popular Supplement Nitrate Only Boosts Men's Athletic Performance … Smart rings’ ultra-precise movement tracking takes wearable technology to the next level … Quantifying Change of Direction Movement Demands in Professional Tennis Matchplay … Is massage therapy for runners worth the hype? … Inside the mind of Roger Federer

References

Tran, Chau M., and Larry M. Silverberg. "Optimal release conditions for the free throw in men's basketball." Journal of sports sciences 26.11 (2008): 1147-1155.

Sternad, Dagmar. "Stability and variability in skilled rhythmic action—A dynamical analysis of rhythmic ball bouncing." Motor control and learning. Boston, MA: Springer US, 2006. 55-62.

In March 2017, a Dutch behavioral economist named Thomas Buser began a two-year experiment, conducted in two phases. In the first phase, he sent out a survey to a representative sample of 5,255 working-age people in the Netherlands with a questionnaire consisting of a single question: “How competitive do you consider yourself to be?” Respondents were told to choose a value between 0 (”not competitive at all”) and 10 (“very competitive”)

In the second phase, Buser sent out another questionnaire to the same group a year later asking if they’d like to participate in a simple math tournament. They could choose to be paid for their participation by a basic hourly fee. Or, they could opt to collect a larger sum if and only their score was better than another randomly selected participant.

Only 27 percent of the participants chose the tournament-style compensation. But there were some noteworthy characteristics among those who did:

• They were more than twice as likely to be in the highest quintile of income compared to the other participants, and much less likely to be in the lowest two.

• They were more highly educated on average, and more than twice as likely to have graduated from one of the highest paying majors (medicine or STEM).

• Their responses to the first questionnaire were also strongly correlated to their incentivized responses to the second. For both men and women, the individuals who considered themselves to be competitive were much more likely to have graduated from a university, chosen a lucrative major, and earned a high-paying job. Competitive people were more likely to have chosen to work in medicine, business, or law.

On their surface, these results probably aren’t exactly shocking or illuminating. And, on the surface, the design of the study seems deserving of some scrutiny. What characterizes somebody as competitive vs. simply somebody who likes taking risks? Surely we all know people who might be competitive in some ways but risk-averse in others (like gambling).

But subsequent research by Ernesto Reuben and Lina Lozano at NYU Abu Dhabi has found that, among the subjects they tested, individuals could exhibit a strong tendency toward competitiveness irrespective of their attitudes toward risk. Work done by Linda Kamas at Santa Clara University and Anne Preston at Haverford College has explored gender differences in competitiveness and found that working-age women “who exhibit a taste for competition” earn, on average, 7 percent more than other women.

And so over the past decade it seems that the field of behavioral economics is at least beginning to chip away at the question of “intangible” traits and whether they can be predictive of success in the labor market, an important question as we grapple with the question of whether college is useful and how to close the racial and gender gaps in earnings.

And it was only a matter of time before somebody adopted this line of inquiry and applied it to sports.

Measuring competitiveness in athletes

A paper presented at the MIT Sloan Analytics Convention earlier this month by Spanish researchers Ander and Julene Palacios-Saracho was called “Measuring Individual Competitiveness and Its Impact on Sporting Success.” It’s not a peer-reviewed paper, let’s get that out of the way first. I’m not suggesting this work is gospel.

But I was struck by a line in the piece that I couldn’t believe to be true:

“We are not aware of any empirical study in the scientific sports literature that measures and studies competitiveness.”

That’s always a good place to start.

I was also struck by Ander and Julene’s approach. Absent any comparable work in sports science, they went to where the existing research could guide them. They took their cue from the work that have economists have done on competitiveness in the labor market.

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Elite soccer stars

Here’s the other thing about this paper. It was a longitudinal study (meaning it was conducted over a long period) that involved repeatedly observing soccer players ages 10-23 from an elite soccer academy in the one of the world’s best leagues (Spain’s La Liga) over the course of a decade from 2011 to 2023.

That’s another good place to start.

Here’s how their “competitiveness” was measured.

1. First, they were told to throw a tennis ball into a bucket that is placed 3 meters away. They were each given 10 chances to score as many buckets as possible.

2. Each player is told he is randomly matched with another player who is performing exactly the same task at the same time in another room.

3. Before starting, the player can decide to receive 1 euro per successful shot regardless of the performance of the other player. Or, he can decide to receive 3 euros per successful shot if he outperforms the other player (a tie gets 1 euro per shot).

In addition to the players, the researchers also quizzed the coaches on their perceived competitiveness and their willingness to engage in a competitive situation — exactly how Buser gauged the competitiveness of working-age adults in the Netherlands. I’ll get to why this was informative in a moment.

RESULTS

First off, the players got progressively more competitive as they aged. At age 10, around 55 percent of the players chose their compensation based on competition. By age 18, its 92 percent. The steepest jump in percentages came at ages 14 to 15.

To begin with, the elite athletes even at a young age were much more likely to choose the competitive compensation than non-players of the same age from Spain and Germany, suggesting there is some selection effect that differentiates elite athletes starting as early as age 10.

There were some positional differences. Goalkeepers and defenders appeared to be more risk averse than midfielders, and midfielders were more risk averse than forwards.

And there were differences in how some players responded in the presence of a competitive coach. But these results weren’t uniform across all ages. When 13 to 15-year-old players were paired with a highly competitive coach, the player’s competitiveness would in turn also tend to spike, while the opposite was true for a low-competitive coach, suggesting a malleability in competitiveness as a direct correlate to coaching at a certain age. This didn’t happen at all with the youngest kids, and the types of coaches also appeared to be meaningless for players after they turned 16.

Lastly, as with the working-age Dutch, the same was true of Spanish soccer players: The researchers were fairly convinced that those who chose to be competitive in the bucket-toss game were more likely to reach a higher level of ability on the soccer field.

They wrote:

We have found that differences in competitiveness do help account for differences in performance and successful outcomes, that players’ preferences for competition are malleable, but only up to a certain age (more precisely, within a certain age), and that coaches may have a causal impact on this intangible (typically positive, but not always).

That’s a good place to start.

Competitiveness and the 10,000 Hours Rule

One of the many misconceptions about the famous 10,000 hours rule is that it is a rule. This would suggest that, upon practicing something deliberately for 10,000 hours, at the moment you reach that threshold you will be bestowed as an “expert,” as if earning a degree. This is ridiculous, and it also misses the point.

The point is that 10,000 hours is a really, really long time. If you practiced for five hours a day, all 365 days of the year, it would still take you 5.5 years (sportswriter math here) to accrue 10,000 hours of practice time. This might be a bigger factor in who becomes elite than just the practice: the willingness to devote this much time and deliberate focus to one pursuit at the sacrifice of almost literally everything else. Not everyone is willing to do this.

What fuels that drive to succeed is, quite often, competitiveness. I’m not saying anything earth-shifting here! But here again is an example where skill alone isn’t the end-all determinant of excellence. Expertise, in the clinical sense of the word, requires unusual drive and competitiveness, and identifying that trait early might be a better way to identify the next Kobe Bryant or Simone Biles.

We’ve also seen how malleable that trait can be, and how receptive it is to nurturing at a young age. Therein lies another lesson for coaching. Perhaps the youth coaches could dial it down just a smidge on the “just win, baby” philosophy for the 10-year-olds. There’s scant evidence that it’s making any difference. In fact, it may be detrimental.

Wait until middle school to stoke the competitive juices. By age 16, they’ll be tuning you out again. Competitiveness, at that point, is self-induced.

Measuring intangibles

My other big takeaway from this work is that sports too frequently gives up on measuring things that are considered out of reach. Analytics has come a long way — plenty of people would say it has gone too far. But that’s because it has become too granular in many cases, while leaving wide swathes of the science of skill (TM) unexplored.

We can pinpoint the spin attributes of a baseball traveling 100 mph, but we have little way of measuring the impact that motivation, pressure, stress, fatigue, or competitiveness had in also determining the ball’s eventual location. Some of this can be blamed on technological shortcomings, but I think some of it also has to do with a lack of imagination in the investigatory approach.

So kudos to Ander and Julene Palacios-Saracho for looking outside the box for a way to measure the “intangible.”

Links

Heading a soccer ball does cause brain damage … Sports psychology has an evidence problem … Ingesting sodium citrate improved sprint performance of soccer players, but also caused gastrointestinal problems … Five experts (3 data scientists, 1 video analyst, and 1 coach) preferred TacticAI’s suggested positional improvements at corner kicks … AI-powered tennis ball machine can learn your skill level and simulate live play … Cranberries can help improve performance of distance runners … The physics behind Caitlin Clark’s pure shot … Athletes likely to have higher levels of PFAS after playing on artificial turf

References

Buser, Thomas, Muriel Niederle, and Hessel Oosterbeek. Can competitiveness predict education and labor market outcomes? Evidence from incentivized choice and survey measures. No. w28916. National Bureau of Economic Research, 2021.

Kamas, Linda, and Anne Preston. "Competing with confidence: The ticket to labor market success for college-educated women." Journal of Economic Behavior & Organization 155 (2018): 231-252.

Lozano, Lina, and Ernesto Reuben. Measuring preferences for competition. No. 20220078. 2022.