Applied Sports Science newsletter – February 16, 2016

… For the most part, though, there is an obvious spring in Rooney’s step, even in these dog days of winter. He is living a “dream life”, he says, made even better by the birth of his son, Jack, last August – in the same week he won a world championship bronze. Then there is his training, which is going “10 times” better than this time last year as he builds towards Rio 2016 this summer. “I’m doing things that I didn’t think I could do at any time of my life, and I’m doing it in January of an Olympic year,” he says, lightly touching the bench he is sitting on. Yet all that is tempered by the frustrations of watching the sport he loves fall deeper in the mire.

… Will the former Oregon superstar, coached by another Duck and American distance running icon, Alberto Salazar, attempt in Rio de Janeiro something that hasn’t been accomplished since the 1968 Olympic Games in Mexico City — win medals in the 10,000 and marathon?

“Definitely,” Salazar said shortly after Rupp’s victory Saturday, “because the 10s early on so he can recover and then run the marathon.”

The desire to reach peak physical condition and be at their very best for competition is something that drives athletes to push themselves to the limit in training. In a world where fractions of seconds or inches can make the difference between glory and despair, it is no wonder that athletes put themselves through very challenging routines day after day. However, this determination to improve performance can have its negative side as we all know that doing too much training can in fact have the opposite of the desired effect. Pushing too hard in training can lead to fatigue, burn-out and injury, while it is also a significant issue for young athletes as they have the added factor of being more susceptible to injury during periods of growth. However, while it is accepted that over-training can lead to such problems, the big question trying to identify when training becomes too much.

You might have noticed that I felt quite passionate about the topic of overtraining syndrome (OTS) in last week’s blog. The reason for this is that I suffered with bouts of non-functional overreaching (NFO) and OTS throughout my career. I believe it stunted my progression within sport, at least for a period of 18 months, and it really was a miserable time for me. I’m eager to prevent other athletes from going through what I did, so here is my story.

Traditional force and pressure measurements systems are almost exclusively reserved for the laboratory setting. With the recent introduction of the Moticon OpenGo insole system, this is no longer the case. We can now capture real-world force and pressure data on athletes in the real world. Why is this a big deal? So many reasons, but the clear and simple explanation is that no matter how accurate or precise our lab instruments are, we are still making a ton of compromises in our data collection. We cannot fully replicate practice or game-play in a lab, period. With OpenGo, coaches and trainers can put the measurement system into the shoes or cleats of an athlete and perform real-time analysis on that athete’s gait or power production. Measure left vs. right forces over time, and let technology assist in critical decision making.

A couple of weeks ago I wrote a piece borne out of frustration with the current crop of optical heart rate sensors. After we reviewed the Garmin Vivosmart HR, Forerunner 235 and Polar A360, it wasn’t a surprise that they weren’t as accurate as chest straps – but I felt brands weren’t being upfront about the shortcomings of sensors.

Once the article was published, a host of companies got in touch wanting to add their two cents to the issue. And I was interested to find out from the experts whether wrist monitors could ever be accurate, whether the data from them is really junk, and if people are being misled?

I caught up with three industry experts, including the inventor of the optical heart rate sensor, to get their take on the matter.

As elite athletes are faced with increasingly demanding schedules, the balance of load and recovery is more critical than ever to ensuring optimal performance and welfare. As clubs battle to keep athletes fit and in form, sports science and medical staff are constantly trying to enhance the ways in which they monitor health and performance.

Prozone has developed the KINETIC athlete monitoring platform to support clubs and organisations with the management of training load and injury mitigation. Designed to maximise the analysis of player movement demands, KINETIC synthesises data from multiple tracking technologies across training and matchday situations to deliver practical performance insights.

… Using touchscreen technology, any member of the Raptors staff can easily observe how a certain player is performing at any moment, backed by real time data.

It looks like this will be most helpful as the Raptors are evaluating trades and draft picks. The IBM Sports Insight Central can automatically quantify the financial and performance impact of a player on the current team. With this deal, the Raptors are buying into a system that should make searching through potential draft picks quicker than ever before.

“This pioneering work and extensive collaboration with MLSE and the Toronto Raptors to design this solution will provide the Toronto Raptors, and eventually other professional sports franchises, with a faster means to share, visualize and drive time-critical decisions,” said Jim Rushton, Global Leader, IBM Sports and Entertainment Practice.

If you could take a genetic test to find out if you had an elevated risk of a deadly disease, would you? Should you? And if you did, how would you deal with the results?

Those are questions that genetic counselors and patient advocates deal with all the time. A new poll from STAT and the Harvard T.H. Chan School of Public Health found that about half of respondents would consider such a test if it would signal their risk of cancer or Alzheimer’s disease.

Here’s how two experts who work with patients and potential patients handle questions about genetic testing.

… As a result of this boom in demand for sports information, researchers are also recognizing the need to provide such data. Kristamarie Pratt, a PhD Candidate in Biokinesiology at the University of Southern California, is working with USC’s Human Performance Lab to develop an objective method for quantifying knee loading asymmetries (differences in the weight a patient puts on their injured knee versus their uninjured knee). At the Human Performance Lab, Pratt and other USC researchers use an advanced 3-D motion capture system coupled with force plates and body markers to measure knee-loading asymmetries.

Though Pratt’s research focuses primarily on asymmetries in patients who are post-anterior cruciate ligament (ACL) repair, she says, a “similar type of paradigm can be applied to many different lower extremity movement impairments and help change the physical therapy world” [13]. Pratt’s research is also focused on preventing re-injury in athletes, something many NBA players (see Derrick Rose, Kobe Bryant, Tracy McGrady, etc.) know about all too well. Using sensor technology will give clinicians information that can’t be seen with the naked eye and since the sensors can ideally be taken home with the patient, help guide at-home physical therapy exercises as well. According to Pratt, “If individuals are able to practice their exercises properly then they will not develop altered movement patterns that put them at risk for re-injury” [13]

Can artificial intelligence evolve as human baby does, learning about the world by seeing and interacting with its surroundings? That’s one of the questions driving a huge cognitive psychology experiment that has revealed crucial differences in how humans and computers see images.

The study has tested the limits of human and computer vision by examining each one’s ability to recognize partial or fuzzy images of objects such as airplanes, eagles, horses, cars, and eyeglasses. Unsurprisingly, human brains proved far better than computers at recognizing these “minimal” images even as they became smaller and harder to identify. But the results also offer tantalizing clues about the quirks of human vision—clues that could improve computer vision algorithms and eventually lead to artificial intelligence that learns to understand the world the way a growing toddler does.

Mobile World Congress (MWC) may be almost a week away, but we’re already gaining some insight into the kinds of products we can expect to see at the annual tech extravaganza in Barcelona.

Salted Venture, one of the first startups to be spun out of Samsung, has teased a new smart shoe aimed at helping athletes and coaches access data on an individual’s performance.

The IOFIT, which will be officially unveiled at MWC next week, has sensors embedded in each shoe to serve up real-time insights, such as the amount of force being used by an athlete on various parts of the foot — information that can help determine balance, center of gravity, and weight shift, among other things.

We have to do better. Despite a decade of head injury in the headlines, there is still much more we don’t know about concussions than what we do know. We are a long way from prevention. There is still no proven treatment. The diagnosis and return to play is very subjective. There is not even a definitive method to determine CTE (chronic traumatic encephalopathy) except for examining the brain after death.

As an example of how little we know, concussions are still all lumped together as one diagnosis. It’s like the 1960’s for knees when every injury was a sprain. There were no MRIs, very little treatment and arthroscopy didn’t exist. Doctors didn’t understand the importance or function of the ACL and a tear ended your career. Surgeons routinely removed meniscus with open incisions thinking it served no function and inadvertently created arthritis. Surely all concussions are not the same, just like all knee injuries are not the same. One day soon I hope we can categorize different types of concussions. Perhaps a temporal lobe grade 2 concussion will be treated with a different protocol than an occipital lobe grade 3 injury.

I pen this column on the flight home from attending the “celebration of life” of yet another professional athlete that has taken his own life. I have the misfortune (and fortune) of knowing three friends, all who once were at the top of their sport and now are no longer with us.

Gatorade’s efforts in innovation, and its popularity with athletes, will continue to set the brand apart from emerging competitors who try and attack the brand on price, says PepsiCo CEO Indra Nooyi.

This study aimed to compare the differences in game-to-game variability of technical and physical parameters of basketball players, according to game location and game outcome. Game data (n=712) were collated from the official box-score and player-tracking of the 2013-14 NBA regular season. The players were separated according to their court specific position. A two-step cluster analysis was performed to group players according to time played into 3 groups: short, medium, and long-time played. The coefficient of variation (CV) was calculated from game-to-game parameters. The results showed that short-time players demonstrated great CV for technical and physical statistics, long-time players displayed larger CV in losing and away games, technical indicators such free-throws revealed substantial variability in losing games and guards and centers presented high CV for some performance statistics. CV values were inversely proportional to time played, probably because playing less time decreases the probability of maintaining stable performance across games. Long-time players displayed larger CV in away and losing games, possibly due the constraints imposed by opponent teams. Free-throws seems to be the variables that best discriminate between winning and losing teams. Forward players are a very homogeneous group and mainly composed by all-round players with multiple roles.

A decade ago, the serious baseball fan – serious, as in desperately wanting to increase his or her chances of winning his or her fantasy league – had few places to turn. Bill James’s annual “Baseball Abstract” offered groundbreaking analysis through the late 1970s and ’80s, but the concepts outlined in those books — serious baseball analytics that might predict the performance of actual players – were scattered here and there across the Web. Baseball blogging was in its formative stages. Most fans still hung onto the ideas that wins for pitchers and RBIs for hitters were enormously important.

And there David Appelman sat, home from college, living in McLean with his dad, frustrated with his job. To get ahead in his fantasy league, he regularly read the analysis on a Web site called BaseballHQ.com. As he sifted through the data, he thought he could apply the skills he was using at work – graphing all manner of information for AOL – and apply it to baseball. In August of 2005, to the notice of just about no one outside of his family, he launched FanGraphs.com.