Applied Sports Science newsletter – January 29, 2016

Just under two weeks ago, Joakim Noah played what may wind up being his final game in a Chicago Bulls uniform. The dislocated left shoulder he suffered in a Jan. 15 loss to the Dallas Mavericks put him out four to six months, effectively ending his season and sending him to unrestricted free agency this summer in a cloud of uncertainty.

Even before the injury, it was growing less likely by the week that Noah would be in Chicago after July.

His increasing frustration with his diminishing role in coach Fred Hoiberg’s rotation was obvious, and with this Bulls roster in a period of transition as it is, it was hard to picture the Bulls’ front office paying big money to bring back someone on the wrong side of 30 with the health history that Noah has.

Team Sky’s Sir Dave Brailsford is arguably Wales’ most successful sporting boss of the past 10 years.

He has overseen stunning Team GB successes at the Olympics and the Tour de France with Team Sky.

Sport Wales has been finding out the secrets of his success, at a training camp in Mallorca.

Manchester United’s Academy have teamed up with six-time European Champion, three-time World Champion and 2012 Olympic bronze-medal gymnast Beth Tweddle in a bid to further enhance key skills of players from a young age.

Where’s the line between getting tough on a player, but also building him up? David Shaw says it’s the difference between competitive and combative.

At the AFCA Convention in San Antonio earlier this month, Shaw explained how you create a positive environment within the team while also being hard on them. It comes down to trust and transparency.

Recently, I came across this exquisite investment article which discusses a phenomena called the Babe Ruth Effect and its application to financial portfolio management. The central takeaway from the article — “that the frequency of correctness does not matter; it is the magnitude of correctness that matters” — hit me like a lightning bolt of truth. The statement awakened a clarity about a variety of elements related to track and field, including training, coaching, as well the industry of the sport itself. What follows is my attempt to inspect how and why we could apply the mental model of the Babe Ruth Effect to these areas.

The frequency of correctness does not matter; it is the magnitude of correctness that matters.

There are a several degrees of application of the Babe Ruth Effect towards training. I am going to explore what I consider paramount, namely doing the work of the highest magnitude of correctness first — and often.

Background

Soft landing instruction, which is advocated in several injury prevention programs, is thought to have a qualitative relationship with decreased ground reaction forces (vGRF) and increased lower limb joint excursions.
Objective

To quantify the relationships among landing sound, vertical ground reaction forces (vGRFs), and lower limb kinematics during a drop landing task.
Methods

Twenty-six asymptomatic males aged 18-35 were asked to perform 15 single leg, drop landings from a 30 cm height. Five trials were collected under 3 sound conditions; normal, quiet and loud. The vGRF, lower limb kinematics (sagittal plane) and impact sound were recorded during the deceleration phase.
Results

A simple linear regression revealed a significant relationship between landing sound and vGRF (r2 = 0.42, p<0.001). A repeated measure ANOVA showed that ankle and knee excursion significantly increased by 7.0° and 11.7° respectively during quiet landings (compared to normal sound landings; p<0.001). During the loud landing condition, ankle joint excursion significantly decreased by 9.4° compared to normal sound landings (p<0.001) and hip joint excursion significantly increased by 4.0° compared to normal sound landings (p<0.045).
Conclusion

As landing sound decreases, so does vGRF during a drop landing task. These reductions were achieved by increasing ankle and knee joint excursions. Conversely, as the landing sound increases, so does vGRF. This was the result of decreasing ankle joint excursion and increasing hip joint excursion.

This thesis provides theoretical and applied support for the use of self-report measures for athlete monitoring. Athlete self-report measures were found to effectively reflect the training response, whilst also providing a means to improve communication, confidence, and regulation of athletic preparation. Context-specific guidelines for implementation were also identified.

Computer Vision used to be cleanly separated into two schools: geometry and recognition. Geometric methods like structure from motion and optical flow usually focus on measuring objective real-world quantities like 3D “real-world” distances directly from images and recognition techniques like support vector machines and probabilistic graphical models traditionally focus on perceiving high-level semantic information (i.e., is this a dog or a table) directly from images.

The world of computer vision is changing fast has changed. We now have powerful convolutional neural networks that are able to extract just about anything directly from images. So if your input is an image (or set of images), then there’s probably a ConvNet for your problem. While you do need a large labeled dataset, believe me when I say that collecting a large dataset is much easier than manually tweaking knobs inside your 100K-line codebase. As we’re about to see, the separation between geometric methods and learning-based methods is no longer easily discernible.

By 2016 just about everybody in the computer vision community will have tasted the power of ConvNets, so let’s take a look at some of the hottest new research directions in computer vision.

A new study of nearly 500 Division I athletes has found that almost one-quarter reported signs of depression over the past three years, with rates higher among women than men.

Female track-and-field athletes had the highest prevalence of depressive symptoms (38 percent), while male lacrosse players had the lowest (12 percent), according to the study, released on Wednesday.

Symmetry, or so we are told by science, underlies our appreciation of beauty. But what makes for beautiful—and injury free—running?

A lack of symmetry, that is relative differences in muscle strength, motion, flexibility, balance, and mechanics between sides of the body, is one element often highlighted as a risk factor for injury. However, while it’s easy to find asymmetry in all of us—small variances in leg length, scoliosis or ankle flexibility to name a few—it’s much more challenging to determine cause and effect.

This inherent asymmetry present in every runner makes achieving complete symmetry impossible and unrealistic. Dr. Irene Davis, Director of the National Running Center at Harvard, believes that it isn’t a question of whether or not asymmetry exists, but rather how much of it. “What we don’t know is how much asymmetry is normal and how much we can tolerate before it becomes a problem.”

BodyMatters, Dr. Ian Shrier’s free Massive Open Online Course (MOOC) in Sport and Exercise Medicine is re-launching for the 2nd time on Feb 10, 2016 (registration open now).

Last year, over 30,000 students from 185 different countries participated. This relaunch provides an opportunity for those who were unable to see it the first time around. Based on past experiences of other MOOCs, Dr. Shrier expects to have 8-10,000 students in this session.

Dan Wilcox’s job is not to just build athletes. His job is to build the right athlete for the position. As owner of Elite Fueling and nutritionist for the BYU football program, Wilcox knows how to feed athletes to get the job done, but what he feeds athletes depends largely on goals set by the coaching staff and the athletes willingness to do the work.

“Depending upon the training phase the coaching staff has the players in, we’ll gear up differently,” says Wilcox. “It’s completely individualized to the athlete. I do body composition measurements every week. So I will know during specific weeks what the window is as far as gaining body fat and losing muscle or losing muscle and gaining body fat.”

“We’re testing all of these guys, their sodium concentration and their sweat loss overall. So we will weigh them in, weigh them out. Collect this data so that we can ultimately customize a hydration plan for them that will help them perform at their optimal level,” Lindsay Langford.

… Wenger’s unusual hybrid approach, employing both the ability of impartial analytics and his own instincts, gives an empirical edge to his instinctual tactical decisions. When Aaron Ramsey was recently moved back to central midfield from the wing, Wenger defended the move: “If you look at his expected goals when he is in a central position, it is among the best in the Premier League”. Evidence-based analysis helps Wenger translate his findings to players too: “The weight is greater if you can say, “Look, this team has conceded 70 per cent of their goals from the left.” The players will believe you much more.”

When it comes to taking concrete action based on sound statistical analysis, Arsenal are ahead of the curve. This may be related to their purchase of the football statistics company StatDNA in 2013, which gave the club the unique capability to source, compile and analyse their own data internally. This has given them another edge; Arsenal recently signed Mohamed Elneny from the Swiss Super League, notably one of few competitions not covered comprehensively by Opta, who are the data providers for almost all Premier League clubs.

Yet while it may be tempting to see Wenger’s use of stats as a trump card in the club’s push for their first title since 2004, the reality is less black and white.

Prozone’s Head of U.S. Operations, Stewart Mairs, is leaving the business after 12 years to become Director of Soccer Strategy and Analysis at four-time MLS champion D.C. United.