Applied Sports Science newsletter – December 5, 2017

Aaron Rodgers, who was activated off injured reserve Saturday, will go through a “trial practice week” by primarily serving as the scout team quarterback for the Green Bay Packers.

Rodgers broke his right clavicle Oct. 15 and underwent a surgical repair.

“He’s trial return,” coach Mike McCarthy said Monday. “Just like everybody. I go through this every time a player comes off an injury. You either go down and you’re in the rehab group, and then once you get out of the rehab group, you’re trial return, so you’re limited reps in the practice.”

Kawhi Leonard is feeling healthy and will return “soon” from a quadriceps injury that has kept him out all season, but the Spurs All-Star forward does not have a target date for his debut.

“I feel good, soon to come (and) be able to play on the floor,” Leonard said of his return. “It’s been a long wait, but I’m feeling pretty healthy right now.”

Leonard did not play during the preseason and has missed the team’s first 24 games with right quadriceps tendinopathy. He said the injury, which was due to “wear and tear,” began to bother him in the offseason.

… Some of this criticism was justified. Slight and gangly, De Gea lacked authority in the air. He often chose to punch when it would have been better to clasp the ball decisively. He was regularly outmuscled by attacking players. And he had the tendency to parry long-range shots back into danger. For a time, he was replaced by Anders Lindegaard, which must have been a serious blow to his self-esteem.

But a number of things strike one forcibly looking back on those early wobbles. The first is the dedication with which the Spaniard reformed his training and technique. In the off season, he bulked up, working for hours in the gym with United’s physical coaches to build his core strength. He improved his diet (ditching his infamous preference for tacos). He also, crucially, improved his strategic positioning, perhaps the most undervalued aspect of the goalkeeper’s art.

… Question: I understand that you didn’t play high school football until your senior year. What’s the story behind that?

Answer: I was in the state finals for track in 11th grade and a guy who ran hurdles with me was a starting cornerback. Long story short, he ended up getting in trouble with drugs and got kicked off the team. So, he came to me probably a week later and said, ‘I think you should go try out for my spot.’ He explained to me there were young corners but he said he trusted me to get the job done. And he ended up convincing me to do it.

Nick Davies, the former Norwich City Head of Sports Science, is returning to West Ham to work under David Moyes.

The appointment is expected to be announced tomorrow. TGG does not know the exact job title at this stage, nor how it will impact the position of Gary Lewin, the current Head of Sports Science and Medicine.

Two weeks ago, Moyes said he was close to appointing a new Head of Fitness to replace Miljenko Rak, who had been sacked along with Slaven Bilic on November 6th.

Fatigue monitoring is characterised by using various techniques in order to examine the physiological and psychological fatigue accumulated from training and competing in sport. This is a particularly important tool for coaches, sport scientists, and other practitioners alike due to the fact that high-levels of fatigue can inhibit proper adaption to training and hinder performance in competition. Therefore, actively monitoring fatigue levels in athletes can provide important feedback needed to adjust training in order to improve overall performance.

There are several ways to monitor fatigue through different subjective (e.g. questionnaires) or objective (e.g. blood lactate) measures. Recently, much research has attempted to assess the validity and reliability of many of these measures (e.g. wellness questionnaires). While many practitioners have developed well-rounded fatigue monitoring programmes, there is still a huge demand for more research to verify the best methods for tracking fatigue.

… Social skills are important in the modern labor market because computers are still very poor at simulating human interaction. Skill in social settings has evolved in humans over thousands of years. Human interaction in the workplace involves team production, with workers playing off of each other’s strengths and adapting flexibly to changing circumstances. Such non-routine interaction is at the heart of the human advantage over machines. The growing importance of social skills can potentially explain a number of other trends in educational outcomes and the labor market, such as the narrowing – and in some cases reversal – of gender gaps in completed education and earnings.

Deming explains the importance of social skills by observing that workers naturally vary in their ability to perform the great variety of workplace tasks. Teamwork therefore increases productivity through comparative advantage. He suggests that the benefits of teamwork can only be realized through costly coordination among workers, and he models social skills as a reduction in worker-specific coordination costs. Workers with high social skills can “trade tasks” at a lower cost, enabling them to work with others more efficiently.

… “By creating a mental periodization plan for yourself, you’ll start working on that aspect early on in the season—whether it’s using visualization prior to a certain workout or practicing positive self-talk during long rides and runs,” says Larry Judge, a professor in the Department of Physical Education, Sport, and Exercise Science at Ball State University. “So by performance time, the work has already been put in and both your mind and body are ready.”

Your seasonal plan should be broken down into three separate phases, or mesocycles, lasting four to 12 weeks each. Here’s how to plot your path to mental domination.

The obvious answer is five: vision, hearing, touch, smell, and taste. But the reality may not be so simple.

Eric Leuthardt believes that in the near future we will allow doctors to insert electrodes into our brains so we can communicate directly with computers and each other.

PURPOSE:

This study evaluated whether glycogen-associated water is a protected entity not subject to normal osmotic homeostasis. An investigation into practical and theoretical aspects of the functionality of this water as a determinant of osmolality, dehydration, and glycogen concentration was undertaken.
METHODS:

In vitro experiments were conducted to determine the intrinsic osmolality of glycogen-potassium phosphate mixtures as would be found intra-cellularly at glycogen concentrations of 2% for muscle and 5 and 10% for liver. Protected water would not be available to ionic and osmotic considerations, whereas free water would obey normal osmotic constraints. In addition, the impact of 2 L of sweat loss in situations of muscle glycogen repletion and depletion was computed to establish whether water associated with glycogen is of practical benefit (e.g., to increase “available total body water”).
RESULTS:

The osmolality of glycogen-potassium phosphate mixtures is predictable at 2% glycogen concentration (predicted 267, measured 265.0 ± 4.7 mOsmol kg-1) indicating that glycogen-associated water is completely available to all ions and is likely part of the greater osmotic system of the body. At higher glycogen concentrations (5 and 10%), there was a small amount of glycogen water (~ 10-20%) that could be considered protected. However, the majority of the glycogen-associated water behaved to normal osmotic considerations. The theoretical exercise of selective dehydration (2 L) indicated a marginal advantage to components of total body water such as plasma volume (1.57% or 55 mL) when starting exercise glycogen replete.
CONCLUSION:

Glycogen-associated water does not appear to be a separate reservoir and is not able to uniquely replete water loss during dehydration.

Modern movement tracking technologies enable acquisition of high quality data about movements of the players and the ball in the course of a football match. However, there is a big difference between the raw data and the insights into team behaviors that analysts would like to gain. To enable such insights, it is necessary first to establish relationships between the concepts characterizing behaviors and what can be extracted from data. This task is challenging since the concepts are not strictly defined. We propose a computational approach to detecting and quantifying the relationships of pressure emerging during a game. Pressure is exerted by defending players upon the ball and the opponents. Pressing behavior of a team consists of multiple instances of pressure exerted by the team members. The extracted pressure relationships can be analyzed in detailed and summarized forms with the use of static and dynamic visualizations and interactive query tools. To support examination of team tactics in different situations, we have designed and implemented a novel interactive visual tool “time mask”. It enables selection of multiple disjoint time intervals in which given conditions are fulfilled. Thus, it is possible to select game situations according to ball possession, ball distance to the goal, time that has passed since the last ball possession change or remaining time before the next change, density of players’ positions, or various other conditions. In response to a query, the analyst receives visual and statistical summaries of the set of selected situations and can thus perform joint analysis of these situations. We give examples of applying the proposed combination of computational, visual, and interactive techniques to real data from games in the German Bundesliga, where the teams actively used pressing in their defense tactics.

The NFL now has NextGen Stats which record and calculate player running speed during games. The concept is new and interesting…gives viewers an idea of how fast a player is in pads during a variety of play scenarios. The question is how much does this data really tell us that we didn’t already know? For example, is anyone surprised that players like Marquise Goodwin, Leonard Fournette, Ted Ginn, Travis Benjamin, Todd Gurley, or Tyreek Hill appear on their fastest “ball carrier” list? We aren’t either.

Sure, it can be argued that the NextGen list is comprised of speed data based on players in pads during games and not simply 40 times or track times. However NexGen’s lists generally reflect players that have outstanding high school track times, college track times, and solid NFL Combine performances.

So what about players like Kareem Hunt, Melvin Gordon, Isaiah Crowell, Tevin Coleman, Alvin Kamara and Jordan Howard? They all appear on the NextGen fastest “ball carrier” lists. None of them are considered track burners. Right? They just have great “game” speed. Right? You might be surprised!