Applied Sports Science newsletter – July 20, 2016

Some people are dramatically better at activities like sports, music and chess than other people. Take the basketball great Stephen Curry. This past season, breaking the record he set last year by over 40 percent, Curry made an astonishing 402 three-point shots – 126 more than his closest challenger.

What explains this sort of exceptional performance? Are experts “born,“ endowed with a genetic advantage? Are they entirely “made” through training? Or is there some of both?

Techno music blares from speakers inside the TD Bank Sports Center weight room, where 10 Quinnipiac men’s hockey players are laying in an odd position: their heads resting atop large exercise balls, feet planted firmly on the ground.

Brijesh Patel, the school’s first full-time strength and conditioning coach, explains the exercise. Within seconds, everyone is dropping their hips to within an inch of the floor, then thrusting upward.

If there’s any urge to crack jokes about these rhythmic movements, the players resist. This is only the beginning of a long workout. Patel has lots more in store over the next two hours. There’ll be cardiovascular drills, weight lifting and outdoor sprints up York Hill in the scorching July heat.

Do we have a consensus agreement on how to measure training load? The short answer is NO, and most likely we never will. Sport Science is an art with simple data to correlate; there are no fixed answers. That’s why you’ve got a job. You can combine ‘x’ amount of variables by athlete, group of athletes, sports, gender and present a formula that you believe works best for your players. … A few weeks ago we attended the Training Load 2016 conference in Qatar hosted by the Aspire Academy and based on some comments and private discussions we’ve got some questions and discussions for others to comment on and enrich the current applied science knowledge.

It is one of life’s great enigmas: why do we sleep? Now we have the best evidence yet of what sleep is for – allowing housekeeping processes to take place that stop our brains becoming overloaded with new memories. … Support is growing for a theory that sleep evolved so that connections in the brain can be pruned down during slumber, making room for fresh memories to form the next day. “Sleep is the price we pay for learning,” says Giulio Tononi of the University of Wisconsin-Madison, who developed the idea.

What do you get if you combine the broad trends of smartphones, wearables, Internet of Things, an individual desire for control and healthcare costs for society? You get VCs investing in health-tech startups, that’s what.

And the latest evidence of this is Stockholm-based Lifesum raising a $10 million funding round led by Nokia Growth Partners (NGP), with Draper Esprit, Bauer Media Group and SparkLabs Global Ventures.

Lifesum, which tracks what you eat and your exercise, says it now has 15 million users. That’s less than the 80 million users which MyFitnessPal had when it was acquired by athletic apparel maker Under Armour in February 2015. But Lifesum is aiming at doing more than tracking what you had for breakfast.

Catapult listed on the ASX in 2014 and this week it pulled off a successful $100 million capital raising to acquire two sports analytics companies. Chief Executive and co founder Shaun Holthouse speaks to Elysse. [video, 11:07]

Ask any security researcher, and you’ll hear the same thing: If a device has an operating system, it can be compromised. Fitness bands may not seem like a prime target for hacking, but given the potential information they offer about users’ health, losing control of one could be a very bad thing. Unfortunately for exercise aficionados, most fitness bands are not particularly secure, and their companion smartphone apps aren’t much better.

AV-Test, a Madgeburg, Germany-based security firm, researched seven different fitness bands as well as the Apple Watch in order to see if things had improved since the company’s first round of evaluations last year. The short answer: kind of. While no fitness band is above reproach, a handful are relatively impenetrable. On the other hand, the ones that fall short are essentially exploits waiting to happen.

Trials of a prototype robot for sports therapy have just begun in Singapore, to create a high quality and repeatable treatment routine to improve sports recovery, reducing reliance on trained therapists.

The robot named Emma, short for Expert Manipulative Massage Automation, has already treated 50 patients in trials including professional athletes for conditions ranging from tennis elbows, stiff neck and shoulders, to lower back pain.

Background

Most of the research in the area of psychosocial factors in rehabilitation after sports injuries has focused on risk behaviors, while relatively few studies have focused on behaviors that facilitate rehabilitation. The objective of our study was to understand the psychosocial features that characterize elite female football players who express a resilient behaviour during rehabilitation after a first-time anterior cruciate ligament (ACL) injury and reconstruction.
Methods

A qualitative method was used based on individual in-person interviews and video communication of players who incurred a first-time ACL tear during the 2012 season of the Swedish Women’s Elite Football League. In total, 13 players had a first-time ACL and were interviewed post-season. The interviews were followed by a thematic content analysis. Based on this, eight players were identified as showing resilient behaviors during their rehabilitation and were included in the final analysis.
Results

Three core themes representing psychosocial factors that help players cope successfully with rehabilitation were identified: (I) constructive communication and rich interaction with significant others; (II) strong belief in the importance and efficacy of one’s own actions; and (III) the ability to set reasonable goals.
Conclusions

The findings suggest three core themes of psychosocial factors that characterize first-time ACL-injured elite female football players showing resilience during rehabilitation after ACL reconstruction. Suggestions for medical teams about ways to support communication, self-efficacy, and goal-setting during the rehabilitation process, are provided. [full text]

OBJECTIVE:

To investigate the effects of fatigue induced by a repeated sprint ability (RSA) test on the neuromuscular responses of soccer players with a recent history of lower limb injuries (CH) and a matched control group in good fitness condition (GH).
DESIGN:

This was a case-control study.
PARTICIPANTS:

Nine CH and 9 GH.
INDEPENDENT VARIABLE:

Allocation to CH or GH.
MAIN OUTCOME MEASURES:

Each player was assessed for blood lactate concentration and jumping performance [squat jump (SJ) and countermovement jump (CMJ)] before/after RSA. Post-RSA rate of perceived exertion (RPE) was obtained. Receiver operating characteristic analysis was performed to calculate RSA sensitivity and specificity in distinguishing between CH and GH. Intraclass correlation coefficient was used to assess reliability.
RESULTS:

No baseline differences were found for any variable. ?SJ before/after RSA was -14 ± 2% and -5 ± 2% in CH and GH, respectively (P < 0.05). ?CMJ before/after RSA was -15 ± 2% and -7 ± 2% in CH and GH, respectively (P < 0.05). ?SJ-based and ?CMJ-based (before/after RSA) area under curve (AUC) resulted in 0.90 ± 0.07 and 0.86 ± 0.09, respectively, with both AUCs differentiating between CH and GH with 77.78% sensitivity and 88.89% specificity. Pooled AUC resulted in 0.88 ± 0.06. Intraclass correlation coefficient was high (0.85/0.97).
CONCLUSIONS:

Repeated sprint ability is a simple, low-cost field test potentially able to assist in clinical decision making for return to sport.

Nutrient timing has been the subject of many research studies, and has always been controversial among athletes, researchers, exercise physiologists, and dietitians. A number of researchers have even made reference to an “anabolic window of opportunity.” The idea behind this “anabolic window” is to try maximizing exercise-induced muscular adaptations and facilitating the repair of damaged tissue [1]. Some researchers even claim that certain nutrient timing can increase fat-free mass [2].

This article will deal with the post-exercise period, which is often considered the most critical part of nutrient timing. In it, I’ll try to analyze if such an “anabolic window” really exists.

Ever wondered how long you’d have to swim to burn off the calories in an organic peanut butter cup? Or how far the strawberries or burger on your plate traveled to get there?

For answers, ask the Sage Project, one of the latest of the food technology companies helping consumers navigate nutrition. While a number of food apps count calories and track eating habits, Sage goes beyond the food label to give customers additional information about additives and preservatives, how much sugar has been adding during processing or how far a food has traveled.

“Food labels are a data visualization that we see every day, but we don’t get a lot from them,” said Sam Slover, the co-founder and chief executive of Sage. “There are a lot of things about those labels that make assumptions about what you know and what you want to know.”

Every statistician is familiar with the tedious “Lies, damned lies, and statistics” gibe, but the economist, writer and presenter of Radio 4’s More or Less, Tim Harford, has identified the habit of some politicians as not so much lying – to lie means having some knowledge of the truth – as “bullshitting”: a carefree disregard of whether the number is appropriate or not.

So here, with some help from the UK fact-checking organisation Full Fact, is a nine-point guide to what’s really going on.

Does cooperating require the inhibition of selfish urges? Or does “rational” self-interest constrain cooperative impulses? I investigated the role of intuition and deliberation in cooperation by meta-analyzing 67 studies in which cognitive-processing manipulations were applied to economic cooperation games (total N = 17,647; no indication of publication bias using Egger’s test, Begg’s test, or p-curve). My meta-analysis was guided by the Social Heuristics Hypothesis, which proposes that intuition favors behavior that typically maximizes payoffs, whereas deliberation favors behavior that maximizes one’s payoff in the current situation. Therefore, this theory predicts that deliberation will undermine pure cooperation (i.e., cooperation in settings where there are few future consequences for one’s actions, such that cooperating is not in one’s self-interest) but not strategic cooperation (i.e., cooperation in settings where cooperating can maximize one’s payoff). As predicted, the meta-analysis revealed 17.3% more pure cooperation when intuition was promoted relative to deliberation, but no significant difference in strategic cooperation between more intuitive and more deliberative conditions.

… even under the best of circumstances, measurement is incredibly difficult. And the things of interest to managers, such as the size of a market, the effects of an advertising campaign, and the true costs associated with a poor quality product, are far more complex than time, weight, and distance. Because of this I urge managers to adopt a healthy skepticism of all measurements until they understand them deeply.

Here are a few steps to dig into your measurements and identify if they can be trusted.