Applied Sports Science newsletter – June 22, 2017

Applied Sports Science news articles, blog posts and research papers for June 22, 2017

 

History Suggests Eric Decker Should Thrive in Tennessee

The Ringer, Danny Kelly from

An NFL player on the wrong side of 30 switching teams may seem like an ominous sign, but recent history suggests wideouts like Eric Decker who do so can continue to thrive

 

From the NFL to MIT: The Double Life of John Urschel

MIT Technology Review, Peter Dizikes from

A set diagram depicts the places where different groups of objects overlap. Example: in the United States, there are about 1,700 professional football players, and thousands of people pursuing PhDs in math. In 2017, a diagram of those two sets overlaps in exactly one place.

On an overcast day in late winter, that place is the Norbert Wiener Common Room in MIT’s Department of Mathematics, where John Urschel is sitting at a table, chatting. Urschel is an offensive lineman with the NFL’s Baltimore Ravens, a three-year pro with 40 regular-­season games played and a couple of playoff starts on his football résumé. He is also a doctoral candidate in math at MIT who has passed his qualifying exams and has nine published or accepted research papers on his academic résumé.

Yes, there are plenty of bright people in the NFL, and plenty of athletic math students in America. But no one else has his combination of high-level achievement in professional sports and the seminar room.

 

When Is a Sprint a Sprint? A Review of the Analysis of Team-Sport Athlete Activity Profile | Physiology

Frontiers in Physiology from

The external load of a team-sport athlete can be measured by tracking technologies, including global positioning systems (GPS), local positioning systems (LPS), and vision-based systems. These technologies allow for the calculation of displacement, velocity and acceleration during a match or training session. The accurate quantification of these variables is critical so that meaningful changes in team-sport athlete external load can be detected. High-velocity running, including sprinting, may be important for specific team-sport match activities, including evading an opponent or creating a shot on goal. Maximal accelerations are energetically demanding and frequently occur from a low velocity during team-sport matches. Despite extensive research, conjecture exists regarding the thresholds by which to classify the high velocity and acceleration activity of a team-sport athlete. There is currently no consensus on the definition of a sprint or acceleration effort, even within a single sport. The aim of this narrative review was to examine the varying velocity and acceleration thresholds reported in athlete activity profiling. The purposes of this review were therefore to (1) identify the various thresholds used to classify high-velocity or -intensity running plus accelerations; (2) examine the impact of individualized thresholds on reported team-sport activity profile; (3) evaluate the use of thresholds for court-based team-sports and; (4) discuss potential areas for future research. The presentation of velocity thresholds as a single value, with equivocal qualitative descriptors, is confusing when data lies between two thresholds. In Australian football, sprint efforts have been defined as activity >4.00 or >4.17 m·s−1. Acceleration thresholds differ across the literature, with >1.11, 2.78, 3.00, and 4.00 m·s−2 utilized across a number of sports. It is difficult to compare literature on field-based sports due to inconsistencies in velocity and acceleration thresholds, even within a single sport. Velocity and acceleration thresholds have been determined from physical capacity tests. Limited research exists on the classification of velocity and acceleration data by female team-sport athletes. Alternatively, data mining techniques may be used to report team-sport athlete external load, without the requirement of arbitrary or physiologically defined thresholds. [full text]

 

How Much Exercise Keeps Your Cells Young?

Runner's World, Sweat Science blog, Alex Hutchinson from

… how much running do you have to do to see telomere benefits? Is this one of those cases where a little is all you need, or do you have to put it some serious miles?

Researcher Larry Tucker, of Brigham Young University, has published three recent studies on telomere length, each of which offers some interesting insights. The first, which was presented earlier this month at the American College of Sports Medicine conference and published in Preventive Medicine, tackles the question of exercise dose.

 

Alfie Mawson says England U21s have shown they can ‘hack’ Euro pressure

ESPN FC, PA Sport from

… “We could easily have crumbled when one down but we stood up to it. We stuck to the task and passed with flying colours.”

England also have sports psychologist Rebecca Symes in Poland with them and Swansea’s Mawson believes she has helped the squad overcome any mental challenges.

“Different players take different things from her. Personally she said the other day to remember three things you do when you play well,” he said.

 

In the AI Age, “Being Smart” Will Mean Something Completely Different

Harvard Business Review, Ed Hess from

… I believe that this process of upgrading begins with changing our definition of what it means to “be smart.” To date, many of us have achieved success by being “smarter” than other people as measured by grades and test scores, beginning in our early days in school. The smart people were those that received the highest scores by making the fewest mistakes.

AI will change that because there is no way any human being can outsmart, for example, IBM’s Watson, at least without augmentation. Smart machines can process, store, and recall information faster and better than we humans. Additionally, AI can pattern-match faster and produce a wider array of alternatives than we can. AI can even learn faster. In an age of smart machines, our old definition of what makes a person smart doesn’t make sense.

What is needed is a new definition of being smart, one that promotes higher levels of human thinking and emotional engagement. The new smart will be determined not by what or how you know but by the quality of your thinking, listening, relating, collaborating, and learning. Quantity is replaced by quality. And that shift will enable us to focus on the hard work of taking our cognitive and emotional skills to a much higher level.

 

FC Barcelona To Discuss Barca Innovation Hub At Soccerex

F.C. Business from

Following its unveiling earlier this year, FC Barcelona have confirmed that they will be presenting on their groundbreaking ‘Barca Innovation Hub’ project at this year’s Soccerex Global Convention 2017, taking place in Manchester, 4th-6th September.

With the club planning to work with organisations such as universities, start-ups and investment partners, the project aims to elevate the club’s insight offerings and thought leadership position to the forefront of the sports industry as a centre for knowledge, innovation and technology, and will focus on five key areas: team sports, sports performance, medical services and nutrition, and technology and social sciences.

 

[1706.06969] Comparing deep neural networks against humans: object recognition when the signal gets weaker

arXiv, Computer Science > Computer Vision and Pattern Recognition; Robert Geirhos, David H. J. Janssen, Heiko H. Schütt, Jonas Rauber, Matthias Bethge, Felix A. Wichmann from

Human visual object recognition is typically rapid and seemingly effortless, as well as largely independent of viewpoint and object orientation. Until very recently, animate visual systems were the only ones capable of this remarkable computational feat. This has changed with the rise of a class of computer vision algorithms called deep neural networks (DNNs) that achieve human-level classification performance on object recognition tasks. Furthermore, a growing number of studies report similarities in the way DNNs and the human visual system process objects, suggesting that current DNNs may be good models of human visual object recognition. Yet there clearly exist important architectural and processing differences between state-of-the-art DNNs and the primate visual system. The potential behavioural consequences of these differences are not well understood. We aim to address this issue by comparing human and DNN generalisation abilities towards image degradations. We find the human visual system to be more robust to image manipulations like contrast reduction, additive noise or novel eidolon-distortions. In addition, we find progressively diverging classification error-patterns between man and DNNs when the signal gets weaker, indicating that there may still be marked differences in the way humans and current DNNs perform visual object recognition. We envision that our findings as well as our carefully measured and freely available behavioural datasets provide a new useful benchmark for the computer vision community to improve the robustness of DNNs and a motivation for neuroscientists to search for mechanisms in the brain that could facilitate this robustness.

 

How To Encourage Muscle Stem Cells To Replace Missing Muscle? A Familiar Home, A Few Friends And Some Healthy Exercise

Stanford Medicine, Scope Blog, Krista Conger from

I’ve been writing a lot recently about ways to tinker with muscle stem cells to encourage them to repair muscles injured by overuse or trauma. But what about when muscle is missing completely? Major traumatic events such as landmine explosions can rip away whole chunks of tissue and make it difficult or impossible to ever regain function. In the face of such complete devastation, even muscle stem cells falter.

Now Stanford neurologist Thomas Rando, MD, PhD, and former postdoctoral scholar Marco Quarta, PhD, have outlined a three-part approach that, at least in mice, helps muscle stem cells grow new muscle tissue.

 

How Swansea City Uses Technology To Manage Today’s Athlete

SportTechie, Mark J. Burns from

Swansea City FC sits in the lower half of Premier League football clubs in terms of annual player spend, and as a result, it has to get scrappier and strategic with how it maximizes its talent on the pitch. That’s where Performance Director Richard Buchanan and his support staff of physiotherapists, data scientists, psychologists, sports scientists and other medical professionals enter the picture.

Since joining the club starting with the 2009-10 campaign — and especially over the past few seasons — there’s been an inherent conversation around how to smartly leverage performance data, player-tracking devices, wearables and additional technology to manage their athletes’ health and wellness.

“For me, it was about creating this one unified team rather than having different professional disciplines in separate silos,” Buchanan said. “That’s the crux of what happens day-to-day, it’s about making sure everyone’s on the same page, information is getting shared and there is good communication. To me that is indicative into a successful, high performance environment. It seems to be a growing trend.”

 

To Debug Your Gut (and Maybe Your Brain, Too), Make Nice To The Bugs That Live Inside It

Stanford Medicine, Scope Blog, Bruce Goldman from

… We really don’t know what the optimal gut-microbial composition is (and no two people’s gut ecosystems are exactly the same), but we do know how best to achieve it. To work right, eat right. Our gut microbes feast on fiber, loosely defined as all the complex carbohydrates we can’t digest but they can. When they don’t get enough, they start munching on the mucus lining of our intestine. Not okay to chew the mucus. It’s a protective barrier that keeps microbes from getting out of the gut and into the bloodstream, where they emphatically don’t belong.

Modern inhabitants of industrialized societies average 15-20 grams of fiber intake a day. Members of hunter-gatherer tribes, whose diets presumably closely resemble what our ancestors ingested for 99.9 percent of our species’ evolution, eat 100 grams — the size of a hamburger — daily.

 

Penguins Hire Sam Ventura as Director of Hockey Research

NHL.com , Pittsburgh Penguins from

The Pittsburgh Penguins have added Sam Ventura to their hockey operations department as director of hockey research, it was announced today by executive vice president and general manager Jim Rutherford.

This move coincides with yesterday’s hockey operations announcements made by Rutherford at his season-ending media conference. Assistant general manager Bill Guerin was given the added responsibilities of serving as general manager and alternate governor of the Wilkes-Barre/Scranton Penguins. Jason Karmanos was promoted to assistant general manager alongside Guerin, and Mark Recchi was promoted to director of player development.

 

With new coaching regime, what is Broncos’ approach to advanced analytics?

The Denver Post, Nicki Jhabvala from

… Last season, the one-man analytics crew of Tanney grew to two when the team hired Scott Flaska, a University of Colorado graduate with a degree in mechanical engineering, to work as a football analyst.

And this season, despite a new coaching regime and an offensive scheme that resembles one from their past, the Broncos have kept their eyes on the future.

“In Miami last year, the analytics department played a big role for us as far as the advanced scouting and game-day management, also,” Broncos coach Vance Joseph said. “Mitch is a bright guy. He’s great with the numbers and the rules. For me, it’s going to be an important part of what we do as far as our game plan each week, and as far as game management. He’s going to be directly involved with game management during game day. He’ll be in the box and will be tied right to me.”

 

NBA draft 2017: The data prove this is pro basketball’s most important day

Quartz, Dan Kopf from

… if the Warriors gained an unfair advantage, it wasn’t in getting Kevin Durant.

The real edge they have over all other NBA teams—even other past championship squads— is a great eye for new talent. They have been super successful in the NBA’s amateur draft—the annual event in which teams pick the next generation of players, mostly from US colleges. This year’s NBA draft will be held Thursday (June 22) in Brooklyn, New York.

Quartz analyzed the makeup of the last 20 NBA champions to find out which of the winning teams best stocked their rosters in the draft. The average share of draftees’ minutes played in the playoffs’ final round was 38.6%. The 2017 Warriors share: 48.6%, fifth highest.

 

The Best Approach to Decision Making Combines Data and Managers’ Expertise

Harvard Business Review, Paolo Gaudiano from

Data is now the critical tool for managing many corporate functions, including marketing, pricing, supply chain, operations, and more. This movement is being further fueled by the promise of artificial intelligence and machine learning, and by the ease of collecting and storing data about every facet of our daily lives.

But is the pendulum starting to swing too far? As a practitioner and teacher of predictive analytics, my greatest concern is what I call the “big data, little brain” phenomenon: managers who rely excessively on data to guide their decisions, abdicating their knowledge and experience.

In a typical big data project, a manager engages an internal or external team to collect and process data, hoping to extract insights related to a particular business problem. The big data team has the expertise needed to wrangle raw data into usable form and to select algorithms that can identify statistically significant patterns. The results are then presented to the manager through charts, visualizations, and other types of reports. This scenario is problematic because most managers are not experts in data science, and most data scientists are not business experts. Addressing this dichotomy requires individuals who can “serve as liaisons” between the two.

 

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