Applied Sports Science newsletter – March 17, 2016

There is a new injury rehabilitation trend and it has nothing to do with actual medicine. As social media continues to blossom, posting video of one’s recovery workouts has become the norm.

Le’Veon Bell, Jason Pierre-Paul and Jamaal Charles are just a few examples of NFL players who recently have joined the injury update by social media movement. Draft eligible players, like Butkus Award winner Jaylon Smith, have also participated in the “check out how well I am doing” posting craze.

The aim of this study was to detect qualitative changes in the structure of coordinative variable (elbow angle) fluctuations during a quasi-isometric exercise performed until exhaustion. Seven physical education students performed a quasi-isometric arm-curl exercise holding an Olympic bar (weight: 80% 1RM) with an initial elbow flexion of 90° three times over a period of 4 weeks. They were encouraged to persist, even if the elbow angle was lost, until the fatigue-induced spontaneous termination point (FISTP). Changes in both elbow angles were registered during the task through an electrogoniometer. Detrended Fluctuation Analysis (DFA) was conducted on the initial and final 1024 data points of the series and the associated Hurst exponents were obtained. Multi-way RM ANOVA analyses revealed a significant main effect of the Time on task on the Hurst exponent values but also revealed a significant Trial × Time on task interaction. In the initial (non-fatigue) condition participants tended to produce anti-persistent fBm fluctuations. In the final part before exhaustion a tendency toward persistent fBm was dominant. The trial to trial differences in time-variability structure points to an existence of a long-term variability in control strategies during exercise. The changes in the temporal structure of the elbow angle variability as effort accumulated reflected an increase in low-frequency fluctuations signifying a change in psychobiological mechanisms used to negotiate the task demands. The variability properties of the coordinative variable during exercise may provide information about the dynamic mechanisms that lead to exhaustion.

The National Sleep Foundation kicks off its #7Days4BetterSleep in this year’s Sleep Awareness Week from March 6-13. Sleep is part of everyone’s daily routine, some more than others, but is often how we spend one-third of our existence on this planet. It’s been reported through the years that sleep is closely related to physical and mental health, cognitive processes and metabolic functions (Samuels, 2008).

For the athlete population, sleep serves as one of the most significant factors to ensure the appropriate amount of recovery from training sessions and games. Research indicates athletes generally sleep less than non-athletes and often have difficulty sleeping (Walters, 2002). Sleep serves multiple purposes. It has been emphasised that sleep helps with physical and psychological restoration and recovery, conservation of energy, memory consolidation, discharge of emotions, brain growth and maintenance of the immune system (Samuels, 2008). Sleep loss or a lack of sleep could lead to a general decline in athletic performance.

In professional sports, athletes and staff can expect to spend half of the team’s regular season games on the road. The figure pictured here is an example of the first half of the 2015 season for the Los Angeles Galaxy. A constant struggle with east to west or west to east travel is athletes and staff tend to battle fatigue during and after the long journeys. This more than likely is due to the cramped conditions; dehydration as a result of the low humidity on board the airplane; air turbulence; reduced barometric pressure; vibration; noise; flight anxiety and whole body stiffness due to relative inactivity while traveling (Reilly et al., 2005).

… The introduction of “corrective exercises” in the sports industry may have started the notion that adding additional movements before/after a training regime to address poor movement patterns is always a positive thing. The approach would be similar to the belief that a little salt added to a recipe could fix the taste of rotten meat. The reality is that every movement prescribed is a “corrective” opportunity for the athlete and coach to improve.

The stronger reality is that the correctives are often so limited in their time and effect, that the larger stimulus movements would override any attempt to “correct” and perhaps even reverse the effects of positive adaptations. We have proven this concept; there are negative effects from training exercises (see Sparta Point). In fact, every exercise can have as much positive as a negative effect on your movement pattern.

Bio-banding. Is it the answer or just another challenge in RAE? In Player Development Project Magazine Issue #10, Cruyff Football and Ajax consultant Steve Lawrence gave some background to relative age effects, explaining why they occur and identifying the use of cut-off date rules as the causal culprit. Steve is at the forefront of research in this area, and in this follow-up article he explains the concept of bio banding and suggests how to solve the issue of relative age effects.

Shaun Livingston talks about the value of wearable technology, and Andrew Bogut discusses the impact of the Warriors’ new training staff. [video, pre-roll + 1:11]

The aim of this study was to evaluate stress markers, mood states, and sleep indicators in high-level swimmers during a major 7-days competition according to the outcomes. Nine swimmers [six men and three women (age: 22 ± 2 and 22 ± 4 years, respectively)] were examined. Before (PRE) and after (POST) each race (series, semi-finals, and finals), salivary concentrations of cortisol, ?-amylase (sAA), and chromogranin-A (CgA) were determined. Mood states were assessed by the profile of mood state (POMS) questionnaire completed before and after the 7-days, and self-reported sleep diaries were completed daily. In the “failure” group, cortisol and sAA significantly increased between PRE-POST measurements (p < 0.05), while sCgA was not changed. Significant overall decrease of cortisol (-52.6%) and increase of sAA (+68.7%) was shown in the “failure group.” In this group, fatigue, confusion and depression scores, and sleep duration before the finals increased. The results in the “success” group show tendencies for increased cortisol and sCgA concentrations in response to competition, while sAA was not changed. Cortisol levels before the semi-finals and finals and sCgA levels before the finals were positively correlated to the fatigue score in the “failure” group only (r = 0.89). sAA levels before and after the semi-finals were negatively correlated to sleep duration measured in the subsequent night (r = ?0.90). In conclusion, the stress of the competition could trigger a negative mood profile and sleep disturbance which correspond to different responses of biomarkers related to the hypothalamo-pituitary-adrenal axis and the sympathetic nervous system (SNS) activity, cortisol, sAA, and CgA.

Chemist and biomedical engineer Mark W. Grinstaff and coworkers at Boston University, in collaboration with orthopedists at Beth Israel Deaconess Medical Center, have devised a method for polymerizing a restorative charged hydrogel network inside damaged cartilage. Researchers have used hydrogels and polymers to strengthen tissues before, but only at surfaces, not throughout tissues, as in this study.

In an unassuming area nestled inside Baylor’s weight room sits the university’s Department of Athletic Performance, which attempts to balance the football program’s strength training with equipment and data-collection tools rooted in a more scientific approach.

Players run, lift weights and exercise, as at every other school in the Football Bowl Subdivision, only with gear meant to augment more traditional methods. One tool, called Omegawave, allows the Bears’ staff to track a player’s heart rate and general athletic readiness. Players practice with a GPS monitor placed between their shoulder blades, with the goal of tracing the total distance traveled, and at what velocity.

These tools — along with several others — combine to allow staff members to tailor plans for individual student-athletes. Baylor’s latest advancement brings this specialization down to an even more precise level: a player’s DNA.

… what’s surprised me is the relative lack of adoption by the sports-data analysis platforms. Currently you only get the in-depth analysis from ithlete/BIOFORCE HRV, Elite HRV, EMFIT QS and some others – ie the from the relatively small app-based players.

Sure you can see some of the more important measures (like RMSSD, pnn50, LF/HF ratio, SD1 or SD2**) in sporttracks desktop, or EPOC on Movescount and the recovery time HRV data is displayed on Garmin Connect and Polar Flow. But typically the bigger players just show a few bits of data and NOT analysis. There’s a number..but so what? Where’s the insight and actionability?

This past weekend was the Sloan Sports Analytics Conference, and if you happened to miss the event – it was full of great information regarding the latest in sport-science, athletics, technology, and analytics. If you don’t already have that weekend booked for next year, I would highly recommend you make plans to attend this conference in the future.

Throughout the event, I tweeted the thoughts and conversations I found most interesting. I want to expand on many of the tweets in a longer format than what 140 characters could provide via Twitter. Hopefully, I can provide a greater level of insight than what I wrote on the social media platform.

Disney researchers have figured out of a way to search sports footage using the equivalent of hand-drawn play diagrams.

“We have developed a novel query paradigm and retrieval system, which we call Chalkboarding, that allows the user to issue queries by drawing a play of interest—similar to how coaches draw up plays,” the research abstract states.

The technology was created in conjunction with STATS, Queensland University of Technology and Caltech as an alternative to keyword searching. It leverages the copious data collected by the STATS SportsVu six-camera system developed to track and record the positions of players, referees and the ball—at a rate of 25 times per second. The system also logs passes, shots, fouls and other game elements.

Wearable product developers this week discussed key challenges to driving adoption of the consumer-facing “Internet of Things” during the South by Southwest Interactive conference.

Josh Gunkel, a senior developer with Garmin, noted a major obstacle was “we have, readily available, all this data about ourselves,” but “what in the world does that mean?” Gunkel gave the example of Garmin, which, among other wearables, produces popular running watches designed to track biometrics. Gunkel said the next step is to take those biometrics to produce insight to help users understand “what’s going on with your body.”

Another example Gunkel gave is a minicast weather prediction application. “You can get that stuff on your phone, but for the person that has an active lifestyle … they can quickly see what they need when they need it on their watch. It has an inherent context about where you are, what you’re doing, what you’re trying to do, what information might be important to you. A lot of apps out there are junk, but we’re making progress.”

Watching Ryan Smith at work is enough to trigger a migraine.

At a local startup that aims to build a better football helmet, Smith and his colleagues spend their days strapping prototypes onto dummy heads and slamming them into things.

“We want to beat the crap out of it and see how it holds up,” he explained during a recent test that involved smacking the helmet broadside with a weighted pendulum. The dummy’s neck wobbled so violently it seemed as if it might snap.

Building a wristband that can accurately and consistently measure activities like steps taken or biometrics like heart rate is difficult. There are all kinds of issues to take into account, like noise from arm movements, and the ways in which different skin tones or skin translucencies might impact measurements.

Perhaps no one knows this better than the founders of Quanttus. The startup spent several years and millions of venture-capital dollars trying to develop a wrist-worn device that can measure blood pressure. Last week it released its first product, which is nowhere near realizing this dream: an iPhone app for tracking blood-pressure measurements.

Called Q Heart, the free app invites users to log blood-pressure measurements (though you’ll need a blood-pressure measuring cuff), and keep an eye on how they change over time. You can also log your heart rate—unlike some apps, Q Heart won’t measure this for you, either, though—and apply labels to indicate what you were doing in the last 30 minutes (drinking alcohol and being lightly active, for instance) and what you’re doing now, as well as how you’re feeling.