Applied Sports Science newsletter – August 13, 2016

To say that Accam has taken an unconventional route into elite level football would be a vast understatement.

He started with the Right To Dream Academy, an independent centre of excellence founded as a social enterprise, in his native Accra. These sorts of third-party academies are found the world over and provide opportunities for academic and footballing development to those who may otherwise have slipped through the net. They’re particularly significant in Africa where, due to the developing nature of the domestic game, clubs don’t necessarily have the resources to have extensive youth recruitment networks.

On a macro level these sorts of institutions, with their emphasis on selling players to Europe, arguably hinder the progress of domestic African football. That said, on an individual level they can have a significant impact on the lives of young players like Accam.

First and foremost, Ryan Lochte would like you to know that he’s never slept through a swim practice.

“I’d be in the doghouse right now,” he says, laughing.

But in all seriousness, the 11-time Olympic medalist does believe he’s got the art of napping down to a science. All swimmers do, he insists — because it’s the only way to survive all those early morning training sessions. And the punishing dry land workouts. And perhaps more laps in the pool later on, too.

As we prepare to watch the five-woman U.S. team compete in Rio, we take a look at four of the reasons for the dramatic shift in gymnastics dominance and ask if the rest of the world will ever catch up.

1. The breakup of the Soviet Union

…

It is hard to argue with that, although it is hard for anyone in the room to comprehend the journey that Paul has made from his first club just down the road, US Roissy, to his status as one of modern football’s elite, a man whose arrival at Manchester United was presented with all the glamour of a Hollywood movie. But every story, however remarkable, has a beginning, and this is the story of Paul Pogba, United midfielder, France international and the most expensive footballer in the world.

“He was always curious to know things, even as a small child,” says Fassou. “He always wanted to learn new things. We always encouraged him to do lots of things and to follow his interests. When I saw him play football for the first time though, I could see that his technique was very good. He was four years old, and he always played with boys who were older than him.”

“I think the first thing people notice is all his little quirks and details, the little things he’s perfected over the years to get him ready to hit,” says ESPN staff writer Tommy Tomlinson.

It includes his batting stance. Tominson says Suzuki holds his bat out and up like a sword. Then he tugs his shirt sleeve. “It looks like an archer ready to draw a bow,” he say. “That batting stance is something that is unique in baseball history.”

Nearly everything is unique about Ichiro. He cleans his own cleats, something most players get an assistant to do. He clips any loose threads off his jersey, and then sweeps them up with a lint roller. And he stores his bats — made of Japanese Tamo wood — in a climate-controlled case.

… When you fail to meet an objective, you acquire data about what you need to do to meet your objective the next time. You get answers to all kinds of questions you would never otherwise have asked yourself. What if I lose my nutrition? What if I get too cold? What if I faint? The greater the failure, the more intensely we live the experience, and the deeper the data is embedded in both our physical and emotional bodies. For example, if your hands are so numb and cold you cannot squeeze your brakes, you absorb the physical sensations of pain. At the same time, you experience the emotional fear of not being able to stop while racing headlong down a rain-soaked hill.

Beyond what you are immediately aware of, your senses also upload all kinds of additional peripheral and residual data into your database of experiences. Even though you might not be able to do anything with the information at the time, you now understand the effects of the conditions better. This allows you to act proactively in the next cold race.

Sleep deprivation, such as that experienced because of shift work, jet lag, sleep disorders, and aging, leads to deterioration of many aspects of health. Cognition deteriorates rapidly and substantially when we stay awake through the night. To investigate the time course of brain responses during sleep loss, Muto et al. scanned volunteers repeatedly during an extended period of wakefulness (see the Perspective by Czeisler) in which circadian and homeostatic drives differentially affected local brain regions.

Background The loads to which professional rugby players are subjected has been identified as a concern by coaches, players and administrators. In November 2014, World Rugby commissioned an expert group to identify the physical demands and non-physical load issues associated with participation in professional rugby.

Objective To describe the current state of knowledge about the loads encountered by professional rugby players and the implications for their physical and mental health.

Findings The group defined ‘load’ as it relates to professional rugby players as the total stressors and demands applied to the players. In the 2013–2014 seasons, 40% of professional players appeared in 20 matches or more, and 5% of players appeared in 30 matches or more. Matches account for ?5–11% of exposure to rugby-related activities (matches, team and individual training sessions) during professional competitions. The match injury rate is about 27 times higher than that in training. The working group surmised that players entering a new level of play, players with unresolved previous injuries, players who are relatively older and players who are subjected to rapid increases in load are probably at increased risk of injury. A mix of ‘objective’ and ‘subjective’ measures in conjunction with effective communication among team staff and between staff and players was held to be the best approach to monitoring and managing player loads. While comprehensive monitoring holds promise for individually addressing player loads, it brings with it ethical and legal responsibilities that rugby organisations need to address to ensure that players’ personal information is adequately protected.

Conclusions Administrators, broadcasters, team owners, team staff and the players themselves have important roles in balancing the desire to have the ‘best players’ on the field with the ongoing health of players. In contrast, the coaching, fitness and medical staff exert significant control over the activities, duration and intensity of training sessions. If load is a major risk factor for injury, then managing training loads should be an important element in enabling players to perform in a fit state as often as possible.

PURPOSE:

High-intensity interval training (HIIT) is documented to yield effective improvements in the cardiovascular system and be an excellent strategy for healthy aging. However, it is not determined how age may impact the training response of key components of aerobic endurance.
METHODS:

We recruited 72 males (84.9±12.9 kg; 180.4±5.8cm) and 22 females (76.0±17.2 kg; 171.2±6.7cm) from 20-70+ years with a training status typical for their age group, and divided them into six decade-cohorts. The participants followed supervised training with a targeted intensity of 90-95% of maximal heart rate (HRmax) 3 x week for 8 weeks.
RESULTS:

After HIIT, all age groups increased (p<0.001-p=0.004) maximal oxygen consumption (VO2max) with 0.39±0.20 (20-29yrs), 0.28±0.21 (30-39yrs), 0.36±0.08 (40-49yrs), 0.34±0.27 (50-59yrs), 0.33±0.23 (60-69yrs), and 0.34±0.14 (70+yrs) L·min, respectively. These 9-13% improvements were not significantly different between the age groups. In contrast to age, the percentage improvements after HIIT were inversely associated with baseline training status (r=0.66; p<0.001). HRmax was not altered within the respective age cohorts, but the two oldest cohorts exhibited a tendency (p=0.07) to increase HRmax in contrast to a training-induced decrease in the younger cohorts.
CONCLUSION:

In healthy individuals with an aerobic capacity typical for what is observed in the population, the training response is likely not affected by age in a short term training intervention, but may rather be affected by the initial training status. These findings imply that individuals across age all have a great potential for cardiovascular improvements, and that HIIT may be used as an excellent strategy for healthy aging.

It’s being called the “best turn ever done.” Halfway through his leg of the 4×100-meter freestyle swimming relay, Michael Phelps and the United States trailed France’s Fabien Gilot. Phelps pushed off the wall and started kicking, staying underwater much longer than his competitors. When he finally surfaced, the US was ahead for good.

“In executing the turn, Phelps surfaced an astonishing 2.5 seconds after the Frenchman who touched the wall in the lead,” Timothy Burke of Deadspin wrote.

In the swimming world, it’s conventional knowledge that following the turn, dolphin kicks under the water are indeed faster than swimming on the surface. While on the surface, swimmers create a “bow wave” that slows down forward progress. There is also surface resistance—the friction of the top of the water pushing against the body of the athlete—that can be avoided by swimming underwater. Wave resistance increases as the swimmer’s velocity increases, so simply powering through it on the surface isn’t ever going to be the most efficient. In fact, swimming underwater became such a popular technique that it’s now only legal to swim underwater for just 15 meters after diving into the pool or doing the turn.

What does an Olympic athlete do after the competition? He runs another round to warm down, goes to the sauna or has a massage. Sports scientists have analysed the effect these activities have on the body.

As I learned at Barcelona, Pep is a character who commands instant respect and the demands he makes are contagious; if anyone can change City, it is him

“Gene doping” remains unlikely, but if scientists can safely boost athletic performance by manipulating genes, that should be cause for celebration

Emily Hu had always considered herself a mediocre athlete. Short legs made her a terrible runner, she says, and poor upper body strength made pull-ups an exercise in frustration. But the 33-year-old Californian stayed in shape through the years by practicing martial arts and hitting the gym regularly, never losing the desire to be “really strong.”

So no one was as shocked as Hu when she showed up at her first powerlifting competition three years ago, which she’d entered out of “pure curiosity,” and swept all three events — squat, bench press, and dead lift. It was a breakthrough moment, with Hu discovering previously untapped potential that transformed her self-perception.

“I thought, if monkeying around at the gym could get me these results, think what hiring a professional could do,” recalls the medical device researcher. Hiring a coach and training some 10 hours per week has since produced phenomenal results: Hu is now a champion powerlifter, ranking in the world’s top 10 overall and breaking two world records in the bench press.

Orreco is a company that merges biology and advanced computer technology as a way to help elite athletes train longer, recover faster and reduce the risk of injury.

It profiles an athlete based on “biomarkers” in the blood and feeds this information into self-learning computer programmes that over time optimise training conditions for an athlete. This includes identifying the best sleep patterns for the individual, the best diet, training intensity and duration and other factors that affect performance.

Chief executive Dr Brian Moore set up Orreco with co-founder and consultant haematologist Andy Hodgson in 2009, although the research work related to Orreco goes back 15 years. Moore did a PhD on what made a world-class athlete and he began running a service for athletes including Sonia O’Sullivan at the time of the 2000 Sydney Olympics.

Learning and computation provides machine the ability to better understand the context of images and build visual systems which truly understand intelligence. The huge amount of image and video content urges the scientific community to make sense and identify patterns amongst it to reveal details which we aren’t aware of. Computer Vision generates mathematical models from images; Computer Graphics draws in images from models and lastly image processing takes image as an input and gives an image at the output.

The founders of Sensoria Inc. believe that clothing can be the next wave of “ultra-personal computing” and have created a collection of apparel featuring embedded sensors that connect to an app that tracks data such as activity type, heart rate, gait and in-footwear pressure to the user.

Founded in 2010, the company produces proprietary sensor-enabled T-shirts, sport bras and smart socks.

“We felt that there was an opportunity for the sports apparel and fashion industry to reinvent itself through technology, so we set out to create smart garments that behave like a biometric-sensing computer that feel natural with elegant and cool looks,” said Davide Vigano, chief executive officer, who cofounded the company with Chief Technology Officer Maurizio Macagno and Innovation Adviser Mario Esposito.

The gold medal-winning women’s U.S. Gymnastics team, however, is reportedly experimenting with infrared light therapy to alleviate pain and reduce swelling in its athletes. (Update: A spokesperson for the U.S. women’s gymnastics team has since denied this.) A few months ago, one of the trainers for the gold medal-winning women’s U.S. Gymnastics team reached out to Colorado-based BioCare Systems and received a sample of its LumiWave product, according to CEO Jon Weston, who added that his company has been supplying other elite sports teams with devices for years.

The ACL used to be the dreaded injury, but now Achilles is catching up. Both injuries end seasons and necessitate surgery. Both are predominantly non-contact injuries that have not dropped in frequency despite the limited practice of the current CBA.

This week Seahawks players Brandon Cottom and Ronnie Shields suffered Achilles tendon ruptures essentially back to back during practice. The Lions Eric Ebron was feared to have suffered the same fate. Hopefully the latest report of no need for a boot means his Achilles is not torn.

Although it seems that way, Achilles tears are not more common than in the past, they just haven’t decreased with new CBA practice limits.

… The world watched in horror as French gymnast Samir Ait Said severely fractured his tibia and fibula while vaulting. Italian cyclist Vincenzo Nibali broke his collarbone in two places, and Dutch cyclist Annemiek van Vleuten flew head-first over her handlebars, suffering serious injuries.

Despite these recent events, however, experts say that the frequency and severity of injuries at the Olympics have not varied in the past decade.

“The overall rate of injury was similar between the most recent Winter Games, 14 injuries per 100 athletes, and Summer Games, 13 injuries per 100 athletes, reflecting the panorama of sports disciplines,” said Dr. Lars Engebretsen, a professor at the University of Oslo in Norway who has served as the head of medical sciences for the International Olympic Committee since 2007.

Objective

To map out and synthesise literature that considers the extent of shared decision-making (SDM) within goal-setting in rehabilitation settings and explore participants’ views of this approach within goal-setting.
Methods

Four databases were systematically searched between January 2005–September 2015. All articles addressing SDM within goal-setting involving adult rehabilitation patients were included. The literature was critically appraised followed by a thematic synthesis.
Results

The search output identified 3129 studies and 15 articles met the inclusion criteria. Themes that emerged related to methods of SDM within goal-setting, participants’ views on SDM, perceived benefits of SDM, barriers and facilitators to using SDM and suggestions to improve involvement of patients resulting in a better process of goal-setting.
Conclusions

The literature showed various levels of patient involvement existing within goal-setting however few teams adopted an entirely patient-centred approach. However, since the review has identified clear value to consider SDM within goal-setting for rehabilitation, further research is required and practice should consider educating both clinicians and patients about this approach.
Practice implications

To enhance the use of SDM within goal-setting in rehabilitation it is likely clinicians and patients will require further education on this approach. For clinicians this could commence during their training at undergraduate level.

The brothers Dan and Anthony Rigney of Australia attended the Olympic weight lifting competition on Sunday and were not exactly mortified that the sport is more polluted than Guanabara Bay.

Sure, they want athletes to be drug-free, but they also want to be entertained by raw human power. So yes, they would have preferred to see the Russian and Bulgarian teams, which were barred for doping. Likewise with Ilya Ilyin, a suspended two-time Olympic champion from Kazakhstan, who is the Barry Bonds of the clean and jerk.

“You like to see world records,” said Dan Rigney, 28, a physiotherapist and competitive lifter from Sydney. “It’s like baseball. People just want to see home runs.”

When tennis star Maria Sharapova admitted in March to having taken the heart drug meldonium, the public got a rare glimpse of a common practice that’s often called “legal doping.”

It involves taking a legal prescription drug that may improve performance but hasn’t been banned by anti-doping authorities. And lots of athletes competing in the Rio Olympics will be taking advantage of this loophole, doping experts say.

“If it’s not banned, athletes will use it,” says Ronald Evans, director of the Gene Expression Laboratory at the Salk Institute and an investigator for the Howard Hughes Medical Institute.

The currently accepted amount of protein required to achieve maximal stimulation of myofibrillar protein synthesis (MPS) following resistance exercise is 20–25 g. However, the influence of lean body mass (LBM) on the response of MPS to protein ingestion is unclear. Our aim was to assess the influence of LBM, both total and the amount activated during exercise, on the maximal response of MPS to ingestion of 20 or 40 g of whey protein following a bout of whole?body resistance exercise. Resistance?trained males were assigned to a group with lower LBM (?65 kg; LLBM n = 15) or higher LBM (?70 kg; HLBM n = 15) and participated in two trials in random order. MPS was measured with the infusion of 13C6?phenylalanine tracer and collection of muscle biopsies following ingestion of either 20 or 40 g protein during recovery from a single bout of whole?body resistance exercise. A similar response of MPS during exercise recovery was observed between LBM groups following protein ingestion (20 g – LLBM: 0.048 ± 0.018%·h?1; HLBM: 0.051 ± 0.014%·h?1; 40 g – LLBM: 0.059 ± 0.021%·h?1; HLBM: 0.059 ± 0.012%·h?1). Overall (groups combined), MPS was stimulated to a greater extent following ingestion of 40 g (0.059 ± 0.020%·h?1) compared with 20 g (0.049 ± 0.020%·h?1; P = 0.005) of protein. Our data indicate that ingestion of 40 g whey protein following whole?body resistance exercise stimulates a greater MPS response than 20 g in young resistance?trained men. However, with the current doses, the total amount of LBM does not seem to influence the response. [full text]

… The problem is one of signal to noise. You can’t discern the signal — a lower risk of dementia, or a longer life, or less obesity, or less cancer — because the noise, the enormous uncertainty in the measurement of such things as how much you exercise or what exactly you eat, is overwhelming. The signal is often weak, meaning if there is an effect of lifestyle it is minuscule, nothing like the link between smoking and lung cancer, for example.

And there is no gold standard of measurement, nothing that everyone agrees on and uses to measure aspects of lifestyle.

The result is a large body of studies whose conclusions are not reproducible. “We don’t know how to measure diet or exercise,” said Dr. Barnett Kramer, director of the National Cancer Institute’s division of disease prevention.

… In a survey of the training diets of Olympic athletes by SB Nation and Eater, the reporters found health foods like Greek yogurt, oatmeal, and kale were surprisingly prominent. There was nary a pizza or pancake in the mix during training season except for the odd celebratory meal.

When we looked at the lunches of six current Olympians, we found much the same. For example, US gymnast Gabby Douglas goes for grilled chicken breast and asparagus for her midday meal.

We present a novel, quantitative view on the human athletic performance of individual runners. We obtain a predictor for running performance, a parsimonious model and a training state summary consisting of three numbers by application of modern validation techniques and recent advances in machine learning to the thepowerof10 database of British runners’ performances (164,746 individuals, 1,417,432 performances). Our predictor achieves an average prediction error (out-of-sample) of e.g. 3.6 min on elite Marathon performances and 0.3 seconds on 100 metres performances, and a lower error than the state-of-the-art in performance prediction (30% improvement, RMSE) over a range of distances. We are also the first to report on a systematic comparison of predictors for running performance. Our model has three parameters per runner, and three components which are the same for all runners. The first component of the model corresponds to a power law with exponent dependent on the runner which achieves a better goodness-of-fit than known power laws in the study of running. Many documented phenomena in quantitative sports science, such as the form of scoring tables, the success of existing prediction methods including Riegel’s formula, the Purdy points scheme, the power law for world records performances and the broken power law for world record speeds may be explained on the basis of our findings in a unified way. We provide strong evidence that the three parameters per runner are related to physiological and behavioural parameters, such as training state, event specialization and age, which allows us to derive novel physiological hypotheses relating to athletic performance. We conjecture on this basis that our findings will be vital in exercise physiology, race planning, the study of aging and training regime design. [full text]

Many businesses are turning to data analytics to provide insight for making operational decisions. Two areas in particular where data analytics can help companies is (1) improved service delivery to customers, and (2) more efficient and effective resource allocation. To arrive at actionable insights, the analysis often relies on multiple data sets of varying size and content. In this article, we will discuss one simple example where data engineering, data analysis, and the merging of two data sets can help a company in both the above areas.

One scientist is on a quest to find the genetic mutations that make athletes elite?—?which may lead to new treatments for the rest of us.

If you’ve watched gymnastics in Rio, you’ve probably noticed that the gymnasts are pretty small, and that Simone Biles, the greatest gymnast probably ever, is small even compared to her American teammates. But at 4-foot-8, Biles is actually only slightly smaller than her peers. In fact, over the past 30 years, the average elite female gymnast has shrunk from about 5-foot-3 on average to about 4-foot-9.

Why are elite female gymnasts getting smaller? Because the more demanding gymnastics routines have become, the bigger an advantage it is to be small. A smaller gymnast not only has a better power-to-weight ratio. She also has a lower moment of inertia.

The Olympics are all about competing on the world’s biggest stage, and one of the things the Games do every four years is highlight exceptional performances by younger and older athletes. Gymnast Oksana Chusovitina, representing Uzbekistan, competed in her seventh Olympic games at age 41 in Rio this year. Other older athletes include U.S.’s Meb Keflezighi, 41, Jo Pavey, 42, an English track and field athlete and Mary Hanna, 61, an Australian competing in equestrian. By contrast, Nepal’s Gaurika Singh, 13, competed in swimming as the young athlete at the Rio Games.

It is possible to combine the available data on the age of Olympians with individual examples to draw some conclusions about this topic, which is also a focus of a lot of the emails I have been getting throughout this first week of the Rio 2016 Olympics.

On September 24, 2016, student statisticians, developers and engineers will take part in the first ever NBA Basketball Analytics Hackathon. Teams accepted to the Hackathon will build basketball analytics tools and develop solutions to challenging and important problems in the field of basketball analytics, and present their work to a panel of expert judges and an audience of NBA League Office and team personnel, media, invited guests and the other competitors. Prizes will be awarded to the top three teams, including a tour of the NBA League Office and a lunch with NBA staff. The event will provide an unparalleled platform for the competitors to display their talent in front of key decision makers in the field.