Applied Sports Science newsletter – August 11, 2016

As we have said on many occasions, it is the little things that can often prove to be the difference between success and failure for an athlete. The undoubted talent may have been complemented by the perfect training schedule and preparation, yet when it comes to the big day, the athlete is unable to produce their best. At times it can appear almost inexplicable as to why the combination of all these factors didn’t result in the success that was anticipated, and in some cases the reason comes down to the question of anxiety. We are all aware of stories of an athlete who looks to be in perfect condition in training but appears out of sorts when it comes to competition. We have also seen athletes getting themselves into a winning position, whether that is in golf, tennis or on the track, only to ‘choke’ the crucial moment and see their chance of glory disappear.

When runner Alexi Pappas toes the starting line of the 10,000-meter race at this year’s Olympics, there’s a good chance she won’t be relaxed. But nerves, and even pre-race nightmares, she’s written, “should not be feared.” Rather, “they should be embraced as a friendly indication that we care very much about the challenge ahead. Nervous is a cousin to excited.”

Pappas isn’t alone. Nearly all the great performers I’ve had the privilege to speak with for Outside’s Fitness Coach column—from triathletes to climbers to downhill skiers—have expressed similar sentiments. It’s not that elite athletes don’t feel pre-race nerves; it’s that they know how to manage them. So the next time you feel anxious prior to a big event —be it a summit push, 5K race, or even a high-stakes presentation at work—use these tactics, practiced by the best and backed by new science.

Winning doesn’t matter, we’re told, but something deep inside suggests otherwise. “Our society” creates the urge to win, we’re taught, yet monkeys have been trying to one-up each other for fifty million years. Natural selection built a brain that rewards you with a good feeling when you come out on top. Serotonin is that good feeling. This was discovered in the 1980s, but it is still unmentionable in polite society. [A good summary of the research is The Biochemistry of Status and the Function of Mood States.]

The facts of our natural competitiveness have been submerged by a warm and fuzzy view of nature. Perhaps good intentions are behind this, but the benefits of knowing the inconvenient truth have been overlooked. We are already challenged to manage a brain that strives for social dominance. Understanding that impulse can help us enhance this skill, and to stimulate more good serotonin feelings with less conflict.

For the first time in his NFL career, Bud Dupree had an offseason.

No such thing exists for rookies. They spend the second January through April in Draft preparation, which means carving off or building up their bodies toward measurable figures, like weight and 40 times, that scouts find ideal. May means rookie minicamp, then organized team activities (OTAs) before minicamp in June, a few weeks off, training camp and the longest season of their careers to date.

Late in the year, Dupree said, he hit a wall.

“From being in my first year, not knowing what to expect,” Dupree said. “In college there’s not that many games.”

Safety concerns and CBA restrictions have forced NFL teams to rethink how they approach training camp. But with seemingly every squad opting for a different form of practice, will the regular season change?

You snooze… you win?

That’s the dream for Canada’s women’s eight rowing team.

They recently finished a “night-time sleep extension intervention,” and they’re hoping for a noticeable boost when they take to the waters in Rio Wednesday morning at 6:50 a.m. MT.

The study, spearheaded by University of Calgary researcher Amy Bender, asked the athletes to sport blue light-blocking glasses and shut off electronic devices at least an hour before bedtime, take daily 20-minute afternoon naps and spend at least one extra hour in bed each night.

Facial recognition already posed serious problems for privacy advocates. Used by everyone from law enforcement to churches, the privacy concerns with facial recognition are very real, and they’re about to get a lot worse.

The ability to identify anyone just by analyzing an image of their face creates a severe imbalance of power from the common citizen to the people in charge. The ability to identify those whose faces are blurred or otherwise obstructed kills that balance entirely. Yet that’s exactly what algorithms like the ‘Faceless Recognition System’ (FRS) are aiming to do.

FRS was a creation by researchers at the Max Planck Institute in Saarbrücken, Germany. The idea was to create a method of identifying individuals through use of imperfect — blurry or otherwise obscured — images. The system trains a neural network on a set of photos containing obscured and unobscured images before using that training to spot similarities from a target’s head and body.

Carolina Panthers coach Ron Rivera believes too much technology may wind up hurting the NFL game.

Other coaches are more welcoming to even more hi-tech changes.

For the second straight year, the NFL will experiment in the preseason with allowing coaches and players to use Microsoft Surface tablets on the sidelines to view video replays during the game — instead of just still pictures — and utilize that information to adjust strategy.

The league discussed using the technology in the regular season, but the idea has been tabled until next offseason.

Rivera, for one, hopes it stays on the table — forever.

Objectives

To examine what factors influence a high school female athlete’s stated willingness to perform a lower extremity injury prevention program (IPP). A secondary aim was to examine if a participant’s stated willingness affected her compliance with an IPP.
Design

Repeated measures
Methods

We surveyed high school female field hockey, soccer and volleyball athletes before and after a season-long IPP warm-up intervention. Participants completed the Injury Prevention Program Attitude Survey (IPPAS), a paper and pencil survey utilizing Likert-style and open-ended questions. It was used to assess the athletes’ willingness to perform an IPP if the data proved the player would experience improved performance, fewer injuries and risk factors, what outside factors influence their willingness to perform an IPP, who they would feel comfortable leading their team in an IPP, and what they believe an IPP can improve.
Results

Participants responded that they were willing to perform an IPP if data proved that they would have fewer injury risk factors (p?=?<?.001) and be less likely to suffer an ACL injury (p?<?.001). Improved sport performance did not play a role in participants’ willingness to perform an IPP. Before and after the warm-up intervention, participants stated that stretching, strengthening, and cardiovascular activity should be included in an IPP. Participants’ stated willingness and beliefs prior to the intervention did not appear to affect their compliance.
Conclusions

Female adolescent athletes are willing to perform IPPs if data indicated that they would have fewer injury risk factors and suffer fewer ACL and leg injuries.

When you visit the doctor to get a diagnosis and treatment for a particular ailment, what do you think happens when the doctor leaves the room after your exam? Being a physician I will tell you most the time, the doctor will look up on a computer or device, the specific diagnosis and/or subsequent prescriptions needed to address his observations and exam.

With so much data, he/she cannot possibly remember the specific dosage of all the drugs or the ideal next steps for every single diagnosis. As more data and technology explode into sports, our ability to find significance in numbers and actually apply such information in a meaningful way also has become increasingly challenging. Yet, rather than cringe at such an influx, there are opportunities to evolve to a greater level of care for the athletes by looking at the operating procedures of these more established industries, like medicine. One of the major tools of medicine, is a decision tree.

The NFL may be dumbfounded as to the science of air pressure, but they sure love computer chips. So much so that they have chips installed in players’ shoulder pads to collect data on their physical abilities and calculate things like running distance and speed.

But just because the league is collecting all that cool data doesn’t mean they’re willing to share it. Daniel Kaplan of Sports Business Daily reported Monday that the league plans to give teams data on only their own players and does not plan to let teams access data of their opponents players.

The idea is to limit any competitive advantages that any and all teams could gain from access to player data for their opponents. If one team were to figure out better ways than others to use the data, it could create a competitive imbalance.

Quantitative evaluation of the ability of soccer players to
contribute to team offensive performance is typically based
on goals scored, assists made, and shots taken. In this paper,
we describe a novel player ranking system based entirely on
the value of passes completed. This value is derived based
on the relationship of pass locations in a possession and shot
opportunities generated. This relationship is learned by ap-
plying a supervised machine learning model to pass locations
in event data from the 2012-2013 La Liga season. Interest-
ingly, though this metric is based entirely on passes, the
derived player rankings are largely consistent with general
perceptions of offensive ability, e.g., Messi and Ronaldo are
near the top. Additionally, when used to rank midfielders, it
separates the more offensively-minded players from others. [pdf]

… critically appraising research is not just “common sense”. And not knowing the right questions to ask means that anything that sounds “sciencey” can hold the same sway, regardless of its scientific merit. While many health and science journalists do great work filtering out flawed and poor quality evidence, unfortunately plenty of bad health reporting is out there, and it can cause real damage.

For example, it can result in skewed coverage of good quality research and can legitimise unjustified claims. One way this can happen is when journalists introduce “balance” to stories, presenting opposing views. If the vast majority of scientists support a piece of good quality research and one maverick opposes it, a quote from each camp incorrectly makes it look like scientists are divided on the issue – a phenomenon dubbed “false balance”.

The moment a three point shot is launched, there is a long pause of tension whether it effortlessly drops through the basket or chaotically bounce off the rim. Everyone instantly has a feeling on whether the shot will be good. Sometimes we are right.

We seek to teach a computer to predict whether a shot would be good or a miss. The computer would learn the same way we do, by watching lots of shots. (We don’t teach the computer about acceleration, gravity, spin . . . all the factors that actually affect the motion of the ball.)

This post describes a predictive model using deep learning for basketball trajectories. [requires WebGL]

Across all sports, athletes and coaches are increasingly working with big data and analytics to squeeze every last insight out of every drop of data available. Nowhere is this more true than at the highest levels. The prospect of Olympic medals and success on the international stage mean at elite level, there is intense pressure to be on the cutting edge of analytics.

I spent some time looking into how the British Olympic rowing team – the only GB team to have won gold in every Olympics since 1984 – have increasingly ramped up their data-driven analytics with one primary aim – to make their boats go faster.

In some ways, rowing is intrinsically analytics-friendly. Most of what the athletes do can be measured – from on-water training time to sessions in the gym, in theory giving the team access to the data most likely to bear a relation to actual performance.

But it also poses particular challenges – in it’s competitive form, it will always take place outside, where variables such as weather and water conditions are not only hard to predict but difficult to assess in terms of impact.