Applied Sports Science newsletter – June 23, 2017

Applied Sports Science news articles, blog posts and research papers for June 23, 2017

 

The soccer world without Lionel Messi

ESPN FC, Chris Jones from

… On Saturday, Messi will turn 30. He made his professional debut in October 2004, when he was 17 years, 3 months and 22 days old, the second-youngest player to dress for Barcelona’s senior side. Somehow, that was almost 13 years ago. There are teenagers who know life only with Messi in it.

The math is easy, except that it isn’t. Messi will not be playing football when he is 43. His career is more than half over. It is probably three-quarters gone. Whatever the number of games that remain for him to play, and so for us to watch, it will be far less than he, and we, have already enjoyed.

It is almost painful to see film of him from the start of things. He played differently then. He was unblinking, like a child.

 

Here are the kinds of technology and data Sue Bird wants to see come to the WNBA

GeekWire, Nat Levy from

Technology and data are revolutionizing basketball, from the style of play to how players train and workout.

But some of the big innovations in data that are driving more conversations and interest in the NBA and men’s basketball haven’t made their way to the women’s game. Sue Bird wants that to change.

At the 2017 GeekWire Sports Tech Summit, the WNBA legend and Seattle Storm star said the volume of stats available for fans and players of the WNBA just doesn’t stack up to the NBA. Bird wants to see the same level of statistics available for past and present WNBA players as well. That way, a fan can compare between legends like Cheryl Miller and current stars like Breanna Stewart.

 

Yes, You Need to Learn How to Run

Outside Online, Martin Fritz Huber from

Learn to walk before you learn to run” used to be just a figure of speech. These days, walking is something you can learn, or at least learn to do better, since poor walking mechanics have been linked to a host of other issues, from hip, knee, and back pain to neck problems and headaches. Likewise, there’s been an increased impetus for runners to focus on improving their form, both for performance purposes and injury prevention.

Increasing running efficiency is among the purported benefits of MovNat, “a physical education and fitness system” founded by the French paleo evangelist Erwan Le Corre. Outdoor living and training is crucial to the MovNat ethos, as evidenced by this popular YouTube video featuring Le Corre scampering around the forest. While a running coach might advise on things like optimizing foot strike or arm swing, MovNat is more concerned with ensuring that basic “natural human movement skills” are executed the way they should be. These, according to MovNat’s philosophy, form the building blocks for more complex “level 2” movements like running or climbing.

“We work on running efficiency and adaptability, but we also work on the underpinnings of the foundational movements that help create it,” says Danny Clark, a former elite-level wrestler and grappler who is the performance director at MovNat.

 

Sleep to Win 2. Evidence-based sleep management to support your performance and wellbeing

Supporting Champions blog, Kevin Morgan and Luke Gupta from

… Here are the first of our Top 10 principles for managing sleep during training periods, and in the run-up to competitions.

1. Recognise your own sleep need. Don’t base your personal sleep duration targets on the self-reported sleep quantities of other athletes (however successful they may be). Individual sleep needs differ, and you really don’t want to introduce unrealistic and unachievable goals into your personal routines. Rather, aim to sleep enough to minimise daytime fatigue and optimise the experience of restoration. This can vary by an hour or more per night among similarly aged healthy people.

 

If You Want to Get Better, Focus on What Really Matters

Brad Stulberg and Steve Magness, Peak Performance blog from

… What are the evidence-based interventions that promote a high-performance lifestyle, reduce burnout, and support mental health?

Do Deep-Focus, Undistracted Work: Multi-tasking is an illusion. If anything, it ought to be called “half-tasking.” Research shows that when people multi-task, they are constantly switching their attention between tasks. Even though this occurs at the scale of milliseconds, it adds up. The American Psychological Association reports that when you multitask, though you think you’re getting twice as much done, you’re actually getting close to only half as much done!

 

Soccer Academies Train African Players for U.S. Teams

The Atlantic, Alexander Wooley from

Ema Twumasi’s first ever collegiate goal was a spectacular bicycle kick against California Polytechnic State University in August 2016. The 19-year-old Ghanaian’s timely scoring during the remainder of the season propelled his team, Wake Forest University in North Carolina, to the NCAA championship game last December, where it lost to Stanford on penalty kicks.

Twumasi probably wouldn’t have made it this far were it not for Ghana’s Right to Dream academy, set up by the former Manchester United scout Tom Vernon almost 20 years ago.

Right to Dream (RtD) is one of a growing number of educational charities that have built a trans-Atlantic pipeline, sending young African soccer players to the U.S. to meet the demand of talent-hungry Division I collegiate programs.

 

Changing the Game with Dr. Fergus Connolly

SimpliFaster Blog, John Weatherly and Fergus Connolly from

John T. Weatherly: Data collection and analysis has increased dramatically. How do coaches and organizations stay on top of this without being overwhelmed?

Dr. Fergus Connolly: Well, let us take a step back first. Far too many teams collect data for the sake of it, but with no real plan. They actually create noise, or what is referred to as “global” or “external” noise, and miss any signal. Do not confuse data with knowledge. Collecting data is easy; gaining knowledge from data is more difficult. There are teams that falsely assume information is power. It is not. Knowledge is power. Data is, well … just data.

Some people will suggest there is no problem with collecting as much data as possible, but this is a fool’s errand. Collecting as much data as possible does three very dangerous things for any organization. First, it wastes resources, money, expertise, and time. Second, it serves to create noise and only muddies the water. And third, and most critically and gravely, it gives teams and coaches the illusion of having knowledge. This illusion is devastating, because when the illusion becomes apparent, it is too late and coaches see suddenly that it was just a myth.

A far more efficient approach is to collect information with a specific problem in mind.

 

The science is in — EPA, end the debate on turf safety

TheHill, Dan Bond, Art Dodge and Rom Reddy from

… As the multi-agency study drags along — likely to take two more years at the least — parents and school officials nationwide await clarity, and in many cases are altering, delaying and even cancelling planned field projects. This is despite the fact that the credible science has overwhelmingly shown exposure to any chemicals present in recycled rubber is not meaningfully different from exposure to urban or rural soil. What’s more, this ongoing regulatory uncertainty is costing American jobs.

Troublingly, the EPA admitted in July that, “Due to time and resources constraints, we are not able, within this study, to investigate other types of fields (e.g. natural grass, synthetic fields with natural product infill, synthetic fields with EPDM or TPE infill) with sufficient sample sizes and statistical power” and also added, “(I)t is important to recognize that chemicals are present in other types of fields, including natural grass fields.”

In other words, they are evaluating recycled rubber in a vacuum without benchmarking findings against the relative safety of natural grass. This calls into question the basic usefulness of this study at all, which is why we have repeatedly asked EPA to use a benchmark.

 

Sensor makers speak out on the increasing commoditization of hardware

MobiHealthNews, Jonah Comstock from

In the connected health space, hardware is becoming less and less important as sensors become commodified, according to two panelists at HXRefactored, a conference held in Boston this week. Instead, companies should focus on software, user experience, algorithms, and data analysis.

“Dare to be a software company,” Propeller Health CTO Greg Tracy said, offering advice to other startups. “At the end of the day, most of those sensors are becoming commodities. Bluetooth is ubiquitous, it’s all over the place, everything is getting instrumented. It’s more important to find insight in all of that data, rather than obsess over sensors themselves.”

 

Plotting a Moore’s Law for Flexible Electronics

IEEE Spectrum, Rachel Courtland from

At a meeting in midtown Manhattan, Kris Myny picks up what looks like an ordinary paper business card and, with little fanfare, holds it to his smartphone. The details of the card appear almost immediately on the screen inside a custom app.

It’s a simple demonstration, but Myny thinks it heralds an exciting future for flexible circuitry. In January, he began a five-year project at the nanoelectronics research institute Imec in Leuven, Belgium, to demonstrate that thin-film electronics has significant potential outside the realm of display electronics. In fact, he hopes that the project, funded with a €1.5 million grant from the European Research Council (ERC), could demonstrate that there is a path for the mass production of denser and denser flexible circuits—in other words, a Moore’s Law for bendable ICs.

 

What Does It Mean To Be Well?

Stanford Medicine, Scope Blog from

… The term “wellness” has become so broad that it can lack meaning. As we continue to try to define wellness, can you tell us what it actually means to be well?

We have spent a lot of time trying to understand that! In our initiative, called WELL, the Wellness Living Laboratory, we are conducting a study of more than 30,000 people over many years to identify what factors help people maintain health and wellness. We then plan to develop techniques to help people to improve their overall well-being. During the first five years, 30,000 participants — 10,000 each in China, Taiwan and the United States — will supply personal health information ranging from general health and lifestyle information to genetic and other biological markers.

 

Denial and depression: recovering from long-term injury isn’t just about the body

The Guardian, Amy Lawrence from

… All that thinking time is not necessarily beneficial to injured elite athletes. Far from it. The former Queens Park Rangers manager Chris Ramsey, who is technical director at the club’s academy overseeing all aspects of development, does not beat about the bush when he reflects on how he felt as a player who suffered injury after injury. “I had seven knee operations and three back operations and I was probably depressed for years,” he reflects. “People don’t realise with long‑term injuries you go into depression – no matter how mild it is.

“The cycle includes denial and anger before you can start recovering. Left to your own devices it can take a long time to accept what is happening. You think about where you are in your contract, where you are in your career, if a new manager might come in who doesn’t know you – will he buy someone to replace you? That’s the worst thing about it. There is so much time to think.”

 

Whoa, Gatorade Endurance Formula Now Tastes Totally Different

Competitor.com, Running, Jessie Sebor from

… As it turns out, Gatorade was listening to the grumblings and digestive rumblings. The company’s world-class nutrition scientists had long been on the case to develop a drink that better supported athletes’ efforts and worked for every tummy.

The newly improved Gatorade Endurance Formula, released today, has no artificial flavors or sweeteners, and a much lighter flavor. During a launch event last week, I had the opportunity to taste the beverage and was truly surprised by the light, refreshing taste and the much-less-sticky mouth feel. After downing a cup and heading out on the New York City streets for a run in nearly 90-degree-heat, I experienced no issues at all.

 

Does Your Company Know What to Do with All Its Data?

Harvard Business Review, Thomas C. Redman from

… In working with companies on getting more from their data, I advise managers to explore seven methods to put data to work. I also urge all leaders to initiate department- or business unit–size trials of all these methods, so they can learn how the options work and which would be best for their business.

Make better decisions. First, use better (more relevant, more accurate) data when making decisions, up and down the organization chart. I’ve not worked with or heard of a company that didn’t freely admit that it needed to make better decisions — and many push hard to improve. But incorporating more and better data into decision making can be difficult. You must learn to understand variation, to combine data from different sources, and to drive decision making to the lowest possible level. By taking the time to learn these skills, though, you can use data to reduce uncertainty, increasing the chances of making sound decisions.

 

How often does the best team win? A unified approach to understanding randomness in North American sport

arXiv, Statistics > Applications; Michael J. Lopez, Gregory J. Matthews, Benjamin S. Baumer from

Statistical applications in sports have long centered on how to best separate signal (e.g. team talent), from random noise. However, most of this work has concentrated on a single sport, and the development of meaningful cross-sport comparisons has been impeded by the difficulty of translating luck from one sport to another. In this manuscript, we develop Bayesian state-space models using betting market data that can be uniformly applied across sporting organizations to better understand the role of randomness in game outcomes. These models can be used to extract estimates of team strength, the between-season, within-season, and game-to-game variability of team strengths, as well each team’s home advantage. More generally, we use our framework to compare cumulative models fit across all weeks to sequential ones fit on all weeks prior. We implement our approach across a decade of play in each of the National Football League (NFL), National Hockey League (NHL), National Basketball Association (NBA), and Major League Baseball (MLB), finding that the NBA demonstrates both the largest dispersion in talent and the largest home advantage, while the NHL and MLB stand out for their relative randomness in game outcomes. We conclude by proposing a new metric for judging competitiveness across sports leagues. Although we focus on sports, we discuss a number of other situations in which our generalizable models might be usefully applied.

 

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