Applied Sports Science newsletter – June 16, 2015

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The Warriors hired Kerr in May 2014 after 15 years as an NBA guard, eight as a broadcaster and three as a general manager. In one of his first memorable acts as coach, he halted a mundane staff meeting at the team’s Oakland headquarters and ordered his lieutenants into assistant Luke Walton’s SUV. They drove 30 miles to Muir Beach, stripped down to their boxers and jumped into the bracing Pacific. “Do s??? or go have fun,” player development coach Bruce Fraser cracked that day, a throwaway line that has become an organizational mantra. When Fraser notices Kerr tumbling down a rabbit hole of pick-and-roll coverages, he pulls him high into the Oakland Hills, and they find a trail. “You have to get out in the trees,” Fraser says.

… As the Warriors packed for a return trip to Oakland, owner Joe Lacob walked down the hallway outside the visiting locker room at Quicken Loans Arena. “Good coaching,” he said. Sometimes, the best coaching involves the smartest hiring. When Kerr landed the job last May, he tabbed two experienced assistants in Ron Adams and Alvin Gentry, but he also gave opportunities to Walton and Jarron Collins. He brought Bruce Fraser, who he has known since college, and U’Ren, who worked for him in Phoenix. He gave all of them a voice, regardless of rank, creating a culture where they aren’t afraid to speak—or text, even at 3 a.m., even in the middle of the Finals.

Philadelphia 76ers center Joel Embiid has suffered a setback in his long recovery from a stress fracture in his right foot, the team said Saturday night.

… The Cavs are among a number of NBA teams who have hired a director of sports science to monitor their players’ practice and game habits.

“We look at things like, ‘What are a player’s peak minutes?’” said Cavs general manager David Griffin. “And we really tried to spend a lot of time this year on recovery, giving guys appropriate time off in practice. You do have bigger players playing faster, colliding more often. Players are capable of doing things they never could in the past. They can change direction in a phone booth. The amount of torque, the pressure on your joints, it’s hard to control all of that power. Some of these are freak injuries. But the more smart people we get involved, we’ll start to find some answers.”

In an ideal world, of course, the league would lengthen and widen the court, affording more space for bigger, stronger athletes to operate and reducing the likelihood of collisions. That won’t happen because of the seat configuration already established in arenas.

… As a rule, organizations have favored other qualities and attributes – in particular, those that are easy to measure, and those that allow an employee’s development to be tracked in the form of steady, linear progress through a set of well-defined roles and business structures.

Learning agility, by contrast, has until recently been hard to measure and hard to define. It depends on related qualities such as emotional intelligence that are only just beginning to really be valued. It also relates to behaviors – such as the ability to recover from and capitalize on failure – that some managers would prefer not to think about.

I vividly remember the summers of my high school and collegiate life, laying on the couch for 4 hours between football practices to recover from dreaded double days in the August heat. Due to unfortunate consequences related to player health, these double training sessions have been phased out of many programs, but when conducted in a safe environment (ample hydration, recovery, etc.) there can be great benefit, especially for athletes returning to play form injury. Injured athletes not only want to return to play as quickly as possible, but because they are not practicing and competing have much less stress (outside of training) than athletes who are participating full time. This begs the question, how much is too much?

In the era of personalized medicine, interindividual differences in the magnitude of response to an exercise training program (subject-by-training interaction; “individual response”) have received increasing scientific interest. However, standard approaches for quantification and prediction remain to be established, probably due to the specific considerations associated with interactive effects, in particular on the individual level, compared with the prevailing investigation of main effects. Regarding the quantification of subject-by-training interaction in terms of variance components, confounding sources of variability have to be considered. Clearly, measurement error limits the accuracy of response estimates and thereby contributes to variation. This problem is of particular importance for analyses on the individual level, because a low signal-to-noise ratio may not be compensated by increasing sample size (1 case). Moreover, within-subject variation in training efficacy may contribute to gross response variability. This largely unstudied source of variation may not be disclosed by comparison to a control group but calls for repeated interventions. A second critical point concerns the prediction of response. There is little doubt that exercise training response is influenced by a multitude of determinants. Moreover, indications of interaction between influencing factors of training efficacy lead to the hypothesis that optimal predictive accuracy may be attained using an interactive rather than additive approach. Taken together, aiming at conclusive inference and optimal predictive accuracy in the investigation of subject-by-training interaction entails specific requirements that are deducibly based on statistical principles but beset with many practical difficulties. Therefore, pragmatic alternatives are warranted.

Ground truth data is useful for training, experimentation, and benchmarking; however, video annotation encompasses additional challenges compared to its static image counterpart. For instance, if the objective is to annotate an object in a video, the user has to delineate its spatio-temporal extent at each frame in the video. Nonetheless, if the objective is event annotation, standard object annotation methods might not be sufficient as an event can consist of one or multiple objects interacting with each other in potentially complex ways. The first component of this thesis plans to address this problem by engineering and deploying a video annotation tool. A second and major component consists of developing methods for learning and integrating information from large databases of potentially heterogeneous video. Currently, video surveillance technologies for anomaly identification assume the availability of hours or days of video data originating from the location where the system will be deployed. However, in the parallel fields of object and scene recognition, research has reached breakthrough advancements transitioning from instance to class recognition and classification. One objective of this thesis is to extend these well studied technologies and adapt them to scene instances that have not been seen previously. Scene- matching techniques are used at the video frame level to perform video retrieval given a query video or image and a large database of videos captured at different scenes. The data from the nearest neighbors is then be integrated to compile a summary of what is likely to happen in scenes similar to the query, generating motion predictions for the image.

The Dodgers Accelerator is designed to enable companies to explore and launch new business models as well as help accelerate the growth of great products and services that have recently launched but not yet scaled.

A newly identified small molecule increases the rate of tissue regeneration in the colon, liver, and bone marrow of mice. With further testing and development, such a compound could lead to therapies that would help patients heal tissues damaged by disease or excised through surgery.

In previous studies on animals or patients, scientists have tried to accelerate tissue and blood cell growth by administering analogs of prostaglandin E2 (PGE2), a lipid that promotes regeneration by initiating signals that cause stem cells to proliferate. They’ve also administered agents that stimulate PGE2 signaling and treated stem cells with PGE2 analogs before injecting them into patients. But none of this work has yet led to approved tissue regeneration therapies.

The new strategy boosts levels of PGE2 through another mechanism: by inhibiting an enzyme that breaks it down.

In the quest to keep arms healthy, the Tampa Bay Rays have always positioned themselves ahead of baseball, emphasizing a comprehensive shoulder-strengthening program long before other teams caught on. Now the Rays are hoping technology can give them a step up, too.

The Rays will be the first team to install Kinatrax, a markerless motion-capture system, in their stadium, sources told Yahoo Sports. An announcement touting the move is expected Monday.

This study examined the effect of microcycles in eccentric strength and high-intensity interval training (HIT) on sleep parameters and subjective ratings. Forty-two well-trained athletes (mean age 23.2 ± 2.4 years) were either assigned to the strength (n = 21; mean age 23.6 ± 2.1 years) or HIT (n = 21; mean age 22.8 ± 2.6 years) protocol. Sleep monitoring was conducted with multi-sensor actigraphy (SenseWear Armband™, Bodymedia, Pittsburg, PA, USA) and sleep log for 14 days. After a five-day baseline phase, participants completed either eccentric accented strength or high-intensity interval training for six days, with two training sessions per day. This training phase was divided into two halves (part 1 and 2) for statistical analyses. A three-day post phase concluded the monitoring. The Recovery-Stress Questionnaire for Athletes was applied at baseline, end of part 2, and at the last post-day. Mood ratings were decreased during training, but returned to baseline values afterwards in both groups. Sleep parameters in the strength group remained constant over the entire process. The HIT group showed trends of unfavourable sleep during the training phase (e.g., objective sleep efficiency at part 2: mean = 83.6 ± 7.8%, F3,60 = 2.57, P = 0.06,

We know LeBron’s exhausted in more ways than one. His unfathomable physical workload continues to drive the overmatched Cavs. But insufficient sleep is as much a factor in limiting him from winning this thing all on his own.

At Fatigue Science, when we talk about fatigue, we’re talking about reduced alertness, reaction time, and effectiveness—all of which manifest in the form of sub-optimal athletic performance. This mental fatigue results from inadequate sleep or when sleep and activities fall outside of our biological need to consistently sleep at night and be active in the day—it’s not the same as fatigue resulting from physical exertion.

Researchers from Boston Children’s Hospital and Merck have built the beginnings of “digital phenotype” of insomnia and other sleep disorders based on data from Twitter. This study, published today in the Journal of Medical Internet Research, is one of the first to look at relationships between social media use and sleep issues, and—based on assessments the sentiments expressed in users’ tweets—gives preliminary hints that patients with sleep disorders may be a greater risk of psychosocial issues.