Applied Sports Science newsletter – December 9, 2015

Charles Woodson reflects on his football life—from falling in love with the game in the backyard, to winning the Heisman, to playing for Al Davis and the infamous Tuck Rule game, to winning the Lombardi Trophy in Green Bay. Will the elder statesman return for one more season—at least?

Ever wondered what goes through an athlete’s mind during the heat of battle?

We put that question to Ashton Eaton, who set a decathlon world record when he won gold at the Beijing World Championships in August. His answer provides an incredible insight of the finest ten-event performance in history.

… The No. 1 pick of last year’s draft began his sophomore campaign on a bad note, making just 29.3 percent of his shots over the Timberwolves’ first three games and exhibiting the general lethargy that some believed could keep him from reaching his potential.

But those outside the organization lacked crucial context that explained Wiggins’ dispiriting play in late October and early November: a back injury he suffered 48 hours before the season-opener. He’s been stellar ever since gaining full health, combining the facets that propelled him to an eye-popping rookie season with more subtle improvements that suggest legitimate superstardom. And while statistics – 24.1 points, 3.8 rebounds, and 2.2 assists on 55.6 percent true shooting in his last 14 outings – tell that story better than anything else, they aren’t nearly enough to explain the one that matters far more for the future.

Another Canadian college and university soccer season is in the books, with the conclusion of the Canadian Collegiate Athletic Association (CCAA) and Canadian Interuniversity Sport (CIS) play-offs and National Championships just a few weeks ago. In the Canadian college/university system, the play-offs and National Championships are microcosms of the competitive season, with multiple 90+ minute matches scheduled over a very short period of time, including several instances of back-to-back matches, as well as periods of time with 3 games played over just 4 days.

The impact of perceived wellness on a range of external load parameters, rating of perceived exertion (RPE) and external load:RPE ratios, was explored during skill-based training in Australian footballers. Fifteen training sessions involving 36 participants were analysed. Each morning before any physical training, players completed a customised perceived wellness questionnaire (sleep quality, fatigue, stress, mood and muscle soreness). Microtechnology devices provided external load (average speed, high-speed running distance, player load and player load slow). Players provided RPE using the modified Borg category-ratio 10 RPE scale. Mixed-effect linear models revealed significant effects of wellness Z-score on player load and player load slow. Effects are reported with 95% confidence limits. A wellness Z-score of ?1 corresponded to a ?4.9 ± 3.1 and ?8.6 ± 3.9% reduction in player load and player load slow, respectively, compared to those without reduced wellness. Small significant effects were also seen in the average speed:RPE and player load slow:RPE models. A wellness Z-score of ?1 corresponded to a 0.43 ± 0.38 m·min?1 and ?0.02 ± 0.01 au·min?1 change in the average speed:RPE and player load slow:RPE ratios, respectively. Magnitude-based analysis revealed that the practical size of the effect of a pre-training perceived wellness Z-score of ?1 would have on player load slow was likely negative. The results of this study suggests that monitoring pre-training perceived wellness may provide coaches with information about the intensity of output that can be expected from individual players during a training session.

The King-Devick test appears to be a promising tool in screening for concussions. However, limited evidence exists on the baseline associations between the K-D test and age and baseline screening tools used after concussion. Additionally, there are no published reference values for the K-D test in high school football players. The K-D test, the Balance Error Scoring System, and the Limits of Stability (LOS) test were administered to 157 high school football players. Additionally, a subsample of 62 participants completed the test twice to examine the reliability of K-D test. There was no relationship between the K-D test and the BESS, or the reaction time and directional control of LOS test. Students aged between 16 and 18 years demonstrated faster K-D test performance compared to students between 13 and 15 years of age. However, there was no association between K-D test and history of concussion. The reliability of the K-D test was (ICC2,1 = 0.89), and the minimal detectable change was 6.10 s. Normative reference values for high school football players are presented in this study.

… my favorite first example is using a deep network to spot objects in an image. One of the early showcases for the new approach to neural networks was an annual competition to recognize 1,000 different classes of objects, from the Imagenet data set, and TensorFlow includes a pre-trained network for that task. If you look inside the examples folder in the source code, you’ll see “label_image”, which is a small C++ application for using that network.

The README has the instructions for building TensorFlow on your machine, downloading the binary files defining the network, and compiling the sample code. Once it’s all built, just run it with no arguments, and you should see a list of results showing “Military Uniform” at the top. This is running on the default image of Admiral Grace Hopper, and correctly spots her attire.

… Earlier this year, an MIT team reported a low-cost, high-resolution camera that uses low-power microwaves to create 3-D images of objects hidden behind walls. Optical techniques based on lidar (laser illuminated detection and ranging) have also been used to image hidden objects. But both the microwave and lidar techniques take an hour or more. “That’s not going to work if you want to know whether a car is coming around the corner,” says Genevieve Gariepy, a physics doctoral student at Heriot-Watt University in Edinburgh, UK.

Gariepy, Daniele Faccio, and their colleagues designed a new system that is similar to lidar, but much faster and more sensitive. It can precisely detect a hidden object’s position in just a few seconds, “so we can track the object’s motion in real time,” she says.

Our brains make vision seem easy. It doesn’t take any effort for humans to tell apart a lion and a jaguar, read a sign, or recognize a human’s face. But these are actually hard problems to solve with a computer: they only seem easy because our brains are incredibly good at understanding images.

In the last few years the field of machine learning has made tremendous progress on addressing these difficult problems. In particular, we’ve found that a kind of model called a deep convolutional neural network can achieve reasonable performance on hard visual recognition tasks — matching or exceeding human performance in some domains.

Researchers have demonstrated steady progress in computer vision by validating their work against ImageNet — an academic benchmark for computer vision. Successive models continue to show improvements, each time achieving a new state-of-the-art result: QuocNet, AlexNet, Inception (GoogLeNet), BN-Inception-v2. Researchers both internal and external to Google have published papers describing all these models but the results are still hard to reproduce. We’re now taking the next step by releasing code for running image recognition on our latest model, Inception-v3.

Background: It is not clear whether risk factors for revision anterior cruciate ligament reconstruction (ACLR) are the same throughout patients’ lives.

Purpose: To assess (1) the risk of revision ACLR by age and (2) age-specific risk factors for revision ACLR.

Study Design: Case-control study; Level of evidence, 3.

Methods: A cohort study using patients having undergone primary ACLR who were registered in the Kaiser Permanente ACLR Registry (February 2005 to June 2013) was conducted. Aseptic revision was the main endpoint. Age was evaluated as a risk factor for revision. The cohort was stratified into 4 age groups: 40 years. Graft type, sex, body mass index (BMI), and race were assessed as revision risk factors within each group. Survival analyses were conducted.

Results: Of the 21,304 patients evaluated, 7026 (33%) patients were aged 40 years. Allografts were used in 8671 (41%) patients, hamstring autografts in 6823 (32%), and bone–patellar tendon–bone (BPTB) autografts in 5260 (25%). The 5-year revision probability was highest in patients 40 years old (1.9%; 95% CI, 1.3%-2.7%). Compared with patients aged >40 years, the adjusted revision risk for patients aged <21 years was 7.76 (95% CI, 5.52-10.90). In patients aged 35 kg/m2 (HR, 0.49; 95% CI, 0.34-0.70) compared with those with a BMI <30 kg/m2, and black patients (HR, 0.55, 95% CI, 0.36-0.85) compared with white patients. Sex, BMI, and race were not associated with the risk of revision in older patients. In patients ?40 years old, those with allografts had a higher risk of revision than those with BPTB autografts (HR, 2.69, 2.35, and 3.04 for patients aged <21, 21-30, and 31-40 years, respectively). Patients <21 years old with hamstring autografts had a 1.61 times (95% CI, 1.20-2.17) higher risk of revision than did patients with BPTB autografts; these differences were not identified in older patients.

Conclusion: Age at the time of ACLR surgery is a strong risk factor for revision ACLR. Other risk factors for revision ACLR, such as graft type, sex, race, and BMI, may vary in strength and significance over a patient’s life. Understanding the age-related risk factors associated with revision ACLR may help with appropriate patient counseling and optimal graft choice when performing ACLR.

The NFL’s quest to become safer has extended to an Army lab at Aberdeen Proving Ground, where rubbery, fluid-filled straps tether a crash test dummy’s football helmet to its body. While they allow turning of the head, the straps tighten automatically under jarring blows to minimize violent head whips.

Designed by Army Research Laboratory scientists, the “smart” strap system was one of three recent winners of an open competition for funding to develop new approaches to reduce brain injuries to players.

November’s Return to Play (#RTP2015) Conference in Bern, Switzerland, saw a stellar line-up of speakers engaging with >800 well-informed clinicians and researchers from over 50 countries. BJSM will publish a consensus statement in July 2016 ( and you can watch all the presentations here: http://www.sportfisio.ch/rtp2015-videos-2/!).

Kate Burks, sports dietician and nutrition coach and Liz Fusco, nutritionist for the US Rowing team, shared their tips for using nutrition to stay on the top. Burks started by comparing muscles to sponges. When a sponge is dried up there are several problems – it is not easy to use, it is not pliable and the little tiny holes are incapable of absorbing any particles. So, what can you do to make sure your ‘sponges’ are ready to row? Burks advises to follow these five tips.

How important is the identity of a football club? It’s a tough question to quantify and even tougher to answer when sentiment is concerned. With passions raised in south west London and Milton Keynes as AFC Wimbledon and MK Dons squared off in the Johnstone’s Paint Trophy last season, we examine how important the identity of a football club is commercially in terms of the business model and, more importantly, for the fans.