Applied Sports Science newsletter – February 8, 2019

… “Obviously, it sucks,” Shaw said. “It’s tough, but that’s part of the job. Hockey’s not an easy sport. It’s physical, it’s demanding.”

Will this latest injury change the way Shaw thinks when he’s on the ice?

“Thinking’s never been a strong point of my personality,” he said with a grin. “The way I play and the way I have success, I’ve got to be in-your-face, aggressive. I’ll never change that, I don’t think, because then I wouldn’t be in the league.”

… Because of this roster crunch, bench players have to be able to play more than one position. There is no room anymore for a bench player who can only play first base. In fact, a backup infielder has to be able to play up-the-middle positions at least in a part time role. If a utility infielder can’t play shortstop, that is a problem. Similarly, it is beneficial to have a backup outfielder who can play center field, especially if a team can’t slide one of their starting corner outfielders to center.

Position versatility is more important than ever. That is why what the Rangers have in Isiah Kiner-Falefa could be as valuable as it is interesting. He did not have a stellar debut season at the plate, hitting .261/.325/.357 in 396 PA. A utility infielder with that batting line will not catch anybody’s attention, until you see that he played 35 games at catcher.

… Nearly 8 million teenagers played for their high school teams during the 2017-18 academic year, many of them occupying hours after school under the guidance of various head and assistant coaches. For many of these kids, their coaches reached them in ways their teachers couldn’t, and what they learned on the soccer field or basketball court has stuck in a way that a lecture on the French Revolution did not.

Much of this disparity has to do with the adolescent brain. “These young athletes are pulled into powerful situations where they’re directly engaging physically with other people,” said Mary Helen Immordino-Yang, professor of education, psychology and neuroscience at the University of Southern California. Unlike in the high school classroom, where learning is often abstract, students playing sports are carrying out physical activity in physical space, often in the company of others. The learning is direct and clear. And the interactions with teammates often elicit powerful emotional responses at a time when the adolescent brain is highly susceptible to social cues and hierarchies.

… a concerned parent shared a message from the UH athletic director alerting parents of three positive tests. Subsequent testing identified in at least nine more cases, according to one player who was hospitalized.

The team’s coach, Diego Bocanegra, would not talk about his players’ conditions in a call with Channel 2 Investigates but did admit his strength and conditioning coach is on the outs with the program.

“As of right now, Minor Bowens does not work with the soccer team any longer,” Bocanegra said.

… Information regarding skill development is abundant. Depending on what you come across, it can seem extremely daunting. Are athletes trying to develop motor programs? Do athletes learn and transfer skills better utilizing dynamics systems approach?

A more important question may be, “How do we connect the dots from research to our field/athletes?”

Below are 5 elements that can be implemented into your practice design that will take the research and make it more digestible.

Just one in 20 U.S. children and teens gets the amount of sleep, exercise and screen time that doctors recommend for optimal health, a new study suggests.

Children and teens are supposed to get at least one hour of moderate to vigorous physical activity each day and limit screen time to less than two hours. Kids ages 6 to 12 old also need 9 to 12 hours of sleep, while teens need 8 to 10 hours nightly.

Too little sleep or exercise, or too much screen time, can increase their risk of chronic health problems. These include obesity, mental health issues like anxiety and depression, poor academic achievement and unhealthy behaviors like smoking and drinking, the study team notes in JAMA Pediatrics.

With increased professionalism in sport there has been a greater interest in the scientific approach to training and recovery of athletes. Applying appropriate training loads along with adequate recovery, is essential in gaining maximal adaptation in athletes, while minimizing harm such as overreaching, overtraining, injury and illness. Although appropriate physical stress is essential, stress for many athletes may come from areas other than training. Stress from may arise from social or environmental pressure, and for many athletes who combine elite athletic training with university study, academic workloads create significant stress which adds to the constant pressure to perform athletically. This research aimed to determine if subjective stressors were associated with counterproductive training adaptations in university athletes. Moreover, it aimed to elucidate if, and when, such stressors are most harmful (i.e., certain times of the academic year or sports training season). We monitored subjective (mood state, energy levels, academic stress, sleep quality/quantity, muscle soreness, training load) and objective (injury and illness) markers in 182 young (18–22 years) elite athletes over a 4-year period using a commercially available software package. Athletes combined full-time university study with elite sport and training obligations. Results suggest athletes were relatively un-stressed with high levels of energy at the beginning of each university semester, however, energy levels deteriorated along with sleep parameters toward the examination periods of the year. A logistical regression indicated decreased levels of perceived mood (0.89, 0.85–0.94, Odds Ratio and 95% confidence limits), sleep duration (0.94, 0.91–0.97) and increased academic stress (0.91, 0.88–0.94) and energy levels (1.07, 1.01–1.14) were able to predict injury in these athletes. Examination periods coincided with the highest stress levels and increased likelihood of illness. Additionally, a sudden and high increase in training workload during the preseason was associated with an elevated incidence of injury and illness (r = 0.63). In conclusion, young elite athletes undertaking full-time university study alongside their training and competition loads were vulnerable to increased levels of stress at certain periods of the year (pre-season and examination time). Monitoring and understanding these stressors may assist coaches and support staff in managing overall stress in these athletes. [full text]

The purpose of this study was to determine the intrasession and intersession reliability of Zephyr Bioharness (ZB) and Fitbit Charge variables in both healthy men and women at rest, during the Modified Canadian Aerobic Fitness Test (mCAFT), and throughout recovery. Stratified convenience and snowball sampling were used to recruit 60 participants (30 women, 48 ± 15 years) and (30 men, 48 ± 15 years) from McMaster University student, staff, and faculty population. At rest, intrasession average heart rate (b·min). Intraclass correlation coefficients (ICCs) and Standard Error of Measurement [SEM] for Zephyr ranged from (0.94-0.97) [1.17-1.70] to (0.92-0.97) [1.45-2.10] for Fitbit Charge. During the mCAFT, the Zephyr ICCs and (SEM) ranged from 0.31-0.99 (1.28-8.10) to 0.45-0.99 (1.45-8.71) for the Fitbit Charge. Throughout the recovery, the ICCs and (SEM) ranged from 0.44-0.98 (1.26-10.47) to 0.45-0.98 (1.15-11.90) for Zephyr and Fitbit devices, respectively. At rest, intersession ICCs (SEM) for Zephyr and Fitbit ranged from 0.90-0.94 (1.73-2.37) to 0.88-0.94 (1.83-2.67), respectively. At mCAFT, the Zephyr ICCs (SEM) ranged from 0.91-0.97 (3.12-4.64) to 0.85-0.98 (3.28-4.88) for the Fitbit. Throughout the recovery, the ICCs (SEM) ranged from 0.93-0.97 (2.65-4.66) to 0.76-0.91 (3.17-4.67) for Zephyr and Fitbit devices, respectively. To conclude, both the ZB and Fitbit Charge devices demonstrated excellent reliability measures throughout the 3 phases. The findings from our study add to the existing pool of literature regarding the reliability parameters of wearable devices and suggest that stable and consistent measures of heart rate and physical activity can be obtained using ZB and Fitbit Charge devices among healthy male and female participants at rest, during a standardized submaximal fitness test (mCAFT), and throughout recovery.

Locations services is a rapidly growing solution area for Bluetooth® technology, expected to reach close to 400 million products per year by 2022. The widespread adoption and success of current Bluetooth location services offerings have helped spark market demand for more precise location services capabilities. To meet this demand for even greater performance, the Bluetooth member community added a new direction finding capability that brings a time-tested method for determining signal direction to proven, trusted Bluetooth technology.

“Bluetooth has emerged as the technology of choice for location services, allowing companies to build robust, reliable solutions for the wide variety of organizations that require accurate location to power their businesses,” said Fabio Belloni, chief customer officer and co-founder of Quuppa. “Today’s introduction of a standard approach to Bluetooth direction finding promises to open up even more opportunities for us, our partners, and our customers.”

NFL and college football teams often toggle practice between their indoor facilities and outdoor fields all in the same session. Global soccer clubs may practice on a sprawling complex of grass fields but compete within the confines of high-walled, mass-capacity stadiums. In both cases, a wearable tracking device might work in one situation or the other but never both.

That was the problem Catapult Sports sought to solve with its new line of elite wearables, Vector. The Catapult Vector is the first to combine communication with satellite navigation for outdoor tracking and ultra-wideband capabilities for indoor use.

“The most unique thing about this device is no one is doing both GPS and local positioning, or LPS as we’d call it, in one device,” said Rod Lindsell, Catapult’s product director for elite wearables.

Startups aiming to become major players in global sportstech innovation will be vying for a spot in The University of Queensland’s 2019 HYPE UQ SPIN Accelerator.

HYPE Sports Innovation – which developed the program to champion entrepreneurship and sportstech innovation — is a global startup accelerator that provides access to mentors and investors from around the world to fast-track promising local startups onto the world stage.

UQ ilab Director Bernie Woodcroft said the three month program connected passionate entrepreneurs with mentors from world-leading brands including the Union of European Football Associations, Nike, Adidas and the National Football League.

Athletes who wish to resume high-level activities after an injury to the anterior cruciate ligament (ACL) are often advised to undergo surgical reconstruction. Nevertheless, ACL reconstruction (ACLR) does not equate to normal function of the knee or reduced risk of subsequent injuries. In fact, recent evidence has shown that only around half of post-ACLR patients can expect to return to competitive level of sports. A rising concern is the high rate of second ACL injuries, particularly in young athletes, with up to 20% of those returning to sport in the first year from surgery experiencing a second ACL rupture. Aside from the increased risk of second injury, patients after ACLR have an increased risk of developing early onset of osteoarthritis. Given the recent findings, it is imperative that rehabilitation after ACLR is scrutinized so the second injury preventative strategies can be optimized. Unfortunately, current ACLR rehabilitation programs may not be optimally effective in addressing deficits related to the initial injury and the subsequent surgical intervention. Motor learning to (re-)acquire motor skills and neuroplastic capacities are not sufficiently incorporated during traditional rehabilitation, attesting to the high re-injury rates. The purpose of this article is to present novel clinically integrated motor learning principles to support neuroplasticity that can improve patient functional performance and reduce the risk of second ACL injury. The following key concepts to enhance rehabilitation and prepare the patient for re-integration to sports after an ACL injury that is as safe as possible are presented: (1) external focus of attention, (2) implicit learning, (3) differential learning, (4) self-controlled learning and contextual interference. The novel motor learning principles presented in this manuscript may optimize future rehabilitation programs to reduce second ACL injury risk and early development of osteoarthritis by targeting changes in neural networks. [full text]

… “The players are always looking to find ways to streamline the game to make it more competitive and to put a better product for fans on the field,” said Chris Iannetta, the veteran catcher for the Colorado Rockies, in a telephone interview. “What we’re against is making wholesale changes we don’t feel are going to be meaningful.”

There is incentive for the players to engage Manfred, because the collective bargaining agreement, which runs through 2021, gives him the right to unilaterally impose some ideas he proposed last year, including a 20-second pitch clock. But Iannetta, a member of the union’s executive subcommittee, said the players’ primary objective was to create a sport in which more teams actively try to win.

In 2016, a new men’s volleyball head coach stepped onto the court at War Memorial Gym for the first time in 13 years. It was his first head coaching role in a Canadian university.

He was young. He was an academic.

Two years later, his team were national champions.

… Statistical modeling in soccer, like other sports, has some history. Most of that research was focused on analyzing results. Statistical models were developed and tested to predict game outcomes, and these models were then benchmarked against bookmaker odds. These models relied on regression methods familiar in econometrics to fit a model the data – what in data science is now called “training” the data. The anthropomorphism here can be a little confusing if you’re not familiar with what is being done. The old methods were optimization methods: getting the computer to solve a maximization problem, which as byproduct reveals the sensitivity of the variable to each other.

“Machine Learning” does the same thing- the computer solves an optimization problem, only now based on millions of observations rather than a few hundred. Moreover, machine learning doesn’t tie you down to one statistical model, it optimizes among models. While these are important advances, it’s also important not to lose sight of the fact that the same fundamental principles apply. I don’t know if humans can be thought of as massive optimization solvers (though I doubt it), but the word “learning” in machine learning should not lead us to think that machines are doing anything more than optimization routines.

In the past, the models were constrained by the availability of data and the ability to process it, but in the soccer prediction world, the models worked quite well. The main outcome of this research was that recent results, suitably weighted, were fairly good predictors of future results.