Applied Sports Science newsletter – March 2, 2016

… [Jill] Ellis has moved Horan from her traditional role at striker to the center midfield as the team adjusts to the absence of Lauren Holiday, who retired at the end of last year. Abby Wambach, Shannon Boxx and Laurie Chalupny also retired from the team that won the World Cup, giving opportunity to younger players like Horan.

“I think Lindsey’s range of passing, I’ve said it before, is exceptional. Her vision, short or long passes, I think is very, very good,” Ellis said. “I think it (the move to midfield) was predicated by need, and then seeing if she could do it. And obviously the defensive side is different for her. But already in training and in some of the games, she’s aggressive. She’s willing to do the work.”

A lot of problems in today’s world are too big for our brains. An algorithm that identifies how cause and effect are linked could lead us to better solutions

Background

Advanced testing technologies enable insight into the kinematic and kinetic determinants of sprint acceleration performance, which is particularly important for field-based team-sport athletes. Establishing the reliability and validity of the data, particularly from the acceleration phase, is important for determining the utility of the respective technologies.
Objective

The aim of this systematic review was to explain the utility, reliability, validity and limitations of (1) radar and laser technology, and (2) non-motorised treadmill (NMT) and torque treadmill (TT) technology for providing kinematic and kinetic measures of sprint acceleration performance.
Data Sources

A comprehensive search of the CINAHL Plus, MEDLINE (EBSCO), PubMed, SPORTDiscus, and Web of Science databases was conducted using search terms that included radar, laser, non-motorised treadmill, torque treadmill, sprint, acceleration, kinetic, kinematic, force, and power.
Methods

Studies examining the kinematics or kinetics of short (?10 s), maximal-effort sprint acceleration in adults or children, which included an assessment of reliability or validity of the advanced technologies of interest, were included in this systematic review. Absolute reliability, relative reliability and validity data were extracted from the selected articles and tabulated. The level of acceptance of reliability was a coefficient of variation (CV) ?10 % and an intraclass correlation coefficient (ICC) or correlation coefficient (r) ?0.70.
Results

A total of 34 studies met the inclusion criteria and were included in the qualitative analysis. Generally acceptable validity (r = 0.87–0.99; absolute bias 3–7 %), intraday reliability (CV ?9.5 %; ICC/r ?0.84) and interday reliability (ICC ?0.72) were reported for data from radar and laser. However, low intraday reliability was reported for the theoretical maximum horizontal force (ICC 0.64) within adolescent athletes, and low validity was reported for velocity during the initial 5 m of a sprint acceleration (bias up to 0.41 m/s) measured with a laser device. Acceptable reliability of results from NMT and TT was only ensured when testing protocols involved sufficient familiarisation, a high sampling rate (?200 Hz), a ‘blocked’ start position, and the analysis of discrete steps rather than arbitrary time periods. Sprinting times and speeds were 20–28 % slower on a TT, 28–67 % slower on an NMT, and only 9–64 % of the variance in overground measurements of speed and time (?30 m) was explained by results from an NMT. There have been no reports to date of criterion validity of kinetic measures of sprint acceleration performance on NMT andTT, and only limited results regarding acceptable concurrent validity of radar-derived kinetic data.
Conclusions

Radar, laser, NMT and TT technologies can be used to reliably measure sprint acceleration performance and to provide insight into the determinants of sprinting speed. However, further research is required to establish the validity of the kinetic measurements made with NMT and TT. Radar and laser technology may not be suitable for measuring the first few steps of a sprint acceleration.

I wasn’t going to write a blog post on this week’s Training Load Monitoring conference held at Aspire because all the presentations will apparently be made available online, plus all the papers presented will be published in a special edition of IJSPP next year (which by the way is such a fantastic idea and one I hope many events will adopt going forward). Clearly there was no need for a Sports Discovery post… But I just couldn’t help myself… As many others at the conference also pointed out…

So I will not be sharing specific content from the individual presentations as hopefully you will be able to watch and read these for yourselves soon. Plus there are also plenty of resources on Twitter if you search for #TrainingLoad16 (which was in fact trending during the conference!) But I will be sharing some of the themes that I think stood out across three days of outstanding talks.

… bone responds to mechanical stress by getting stronger—that’s why weight-bearing activities like running and weight lifting are important for preventing osteoporosis—but Beck highlights a lesser-known fact about bone strengthening: during the initial weeks of the bone remodeling process, your bones temporarily become weaker.

When the Purdue men’s basketball team travels, Josh Bonhotal is its behind-the-scenes Superman. As the Boilermakers’ director of sports performance, his job is to keep every player fueled, rested and energized.

I was able to attend the 2nd Aspire Academy Sports Science Conference this week. The main topic of the conferences “Monitoring Athlete Training Loads – The Hows and Whys”. … Below you will find some “interesting/take-home/conclusion/key messages” of presentations.

… Working memory is your brain’s dashboard. It’s the place you can temporarily put information while your brain decides whether or not it is worth the effort to put it somewhere more permanent, like your long-term memory.

As it turns out, different senses have different dashboard capacity. This means that how much you can remember seems to depend on whether, for example, someone says something to you or shows something to you. Because of this, it is important to look at different types of working memory separately.

Optimizing collective behaviour helps to increase performance in mutual tasks. In team sports settings, the small-sided games (SSG) have been used as key context tools to stress out the players’ awareness about their in-game required behaviours. Research has mostly described these behaviours when confronting teams have the same number of players, disregarding the frequent situations of low and high inequality. This study compared the players’ positioning dynamics when manipulating the number of opponents and teammates during professional and amateur football SSG. The participants played 4v3, 4v5 and 4v7 games, where one team was confronted with low-superiority, low- and high-inferiority situations, and their opponents with low-, medium- and high-cooperation situations. Positional data were used to calculate effective playing space and distances from each player to team centroid, opponent team centroid and nearest opponent. Outcomes suggested that increasing the number of opponents in professional teams resulted in moderate/large decrease in approximate entropy (ApEn) values to both distance to team and opponent team centroid (i.e., the variables present higher regularity/predictability pattern). In low-cooperation game scenarios, the ApEn in amateurs’ tactical variables presented a moderate/large increase. The professional teams presented an increase in the distance to nearest opponent with the increase of the cooperation level. Increasing the number of opponents was effective to overemphasise the need to use local information in the positioning decision-making process from professionals. Conversely, amateur still rely on external informational feedback. Increasing the cooperation promoted more regularity in spatial organisation in amateurs and emphasise their players’ local perceptions.

Royal Philips (NYSE: PHG, AEX: PHIA) today announced that it will introduce a next-generation monitoring solution for at-risk patients in low acuity hospital settings, such as the general ward. As an industry-first, the new medical-grade biosensor enabled solution demonstrates Philips’ continuing commitment to better addressing clinicians’ and patients’ needs through monitoring.

Unlike fitness trackers and consumer focused wearables, the new medical-grade, connected biosensor automatically and continuously measures clinically relevant vital signs including heart rate, respiratory rate, skin temperature and more. The biosensor then transmits the data it collects to a connected clinical decision support software application, where the software can be configured to promptly notify the appropriate caregiver or clinician when preset limits are exceeded.

As I ran alongside the Yampa River in Colorado, I didn’t just feel in the zone—I knew I was in it. The sensor embedded in my Lumo Run tights was tracking my cadence and beaming it to an iPhone carried by Lumo co-founder Charles Wang, who ran beside me. For several minutes, the Lumo Run app on Wang’s phone had been silent, meaning my steps per minute hovered around my target of 185. (Lower numbers suggest you’re overstriding, which ups the load on your knees and hips and raises your risk of injury.)

But before I could collect my gold star, my cadence dipped to 170, and the app issued this advice: “Imagine you’re running through a puddle, trying not to make a splash.” I adjusted. Sure enough, my steps per minute returned to the target.

… The new ClearSky system, with a T6 tracker, less than half the size of the current S5 device, will use all the same inertia data sensors, but combined with RF ultra wideband tracking systems for precise location indoors or outdoors.

“This is the first device to put them all in one,” Brian Kopp, Catapult’s North American president tells SI.com. “The reason this is important is [that it marks] the two worlds of analytics and sports science merging.”

… “It’s a league like no other. Certainly the biggest eye-opener is the travel, the road games as they call them. They’re certainly not road games because every game is a flight. I think that was the olden days when they used to travel by bus. We’re scheduled to fly 63,000 miles this year to play our 17 away games,” says Coyle.

Sandy Stewart, his longtime assistant and Houston housemate, explains the team’s poor 2015 away form like this: Houston to New York or Los Angeles is about the same distance as London to Moscow. “There’s not many teams go to Russia and win,” he says. And that’s before you’ve considered the variations in temperature, altitude and pitch surface.

… Setting virtuous goals at the beginning of the year can be quite effective, recent research tells us, since the first day of the year is a temporal landmark. Temporal landmarks signal the start of a new, distinct time period — making us feel we can start from a clean slate. They highlight a contrast between current and future goals (which are often different!) and can thus be a relatively simple way to motivate yourself to accomplish your virtuous goals. So, here is the good news: If you feel like you already failed on your resolutions like me, you do not need to wait till December 31 to start fresh. You simply need to identify a good temporal landmark, and give it another shot.

We identified the perceptual–cognitive skills and player history variables that differentiate players selected or not selected into an elite youth football (i.e. soccer) programme in Australia. A sample of elite youth male football players (n?=?127) completed an adapted participation history questionnaire and video-based assessments of perceptual–cognitive skills. Following data collection, 22 of these players were offered a full-time scholarship for enrolment at an elite player residential programme. Participants selected for the scholarship programme recorded superior performance on the combined perceptual–cognitive skills tests compared to the non-selected group. There were no significant between group differences on the player history variables. Stepwise discriminant function analysis identified four predictor variables that resulted in the best categorization of selected and non-selected players (i.e. recent match-play performance, region, number of other sports participated, combined perceptual–cognitive performance). The effectiveness of the discriminant function is reflected by 93.7% of players being correctly classified, with the four variables accounting for 57.6% of the variance. Our discriminating model for selection may provide a greater understanding of the factors that influence elite youth talent selection and identification.