… “Elite athletes are getting older,” concludes sports scientist Carlos Lago Penas of the University of Vigo in a report for the Barcelona Innovation Hub, the research wing of Messi’s club. He cites a paper he wrote with colleagues at Vigo (lead author: Anton Kalén) showing that the average age of players in the Champions League rose from 24.9 years in 1992-93 to 26.5 last season. A rise of 1.6 years is bigger than it might appear on paper, given that the average age of almost all leading teams runs in a narrow band from 23 to 29.
In tennis, the average age of the top 100 male players has also risen in a decade from 26.2 to an all-time high of 27.9. Today’s three highest-ranked men are Rafael Nadal (33), Novak Djokovic (32) and Roger Federer (38), while 38-year-old Serena Williams remains arguably the best female player. The Vigo authors said that studies of baseball players and triathletes also suggest “a marked increase in the age of peak performance of elite athletes during the last two decades.”
Careers have lengthened in part because the norms of sporting stardom have changed.
… Neal, who patrols the wing for the Edmonton Oilers these days, is a product of that upbringing in Whitby, Ont., where kids played “hockey in the winter, lacrosse in the summer. Pretty much our whole hockey team was our whole lacrosse team,” Neal recalled.
He grew up watching Whitby products like Joe Nieuwendyk, Gary Roberts and Adam Foote. And who did they grow up watching? Well, for Foote it was two-sport players that really impressed him.
… Uhlaender has had plenty of success in her career. She won the world championship in 2012, completing a set of medals to go with her 2007 bronze and 2008 silver. She won the overall World Cup in 2007-08, followed up by finishing third the next year and again in 2012-13. She’s even found other competitive outlets, dabbling in weightlifting and track cycling.
Her cycling has provided a way to stay in shape without putting any more strain on a body that has had, as recounted by a Team USA story in 2017, a total of 12 surgeries — some resulting from a serious snowmobile accident (exacerbated by a collision while dancing), two related to an autoimmune disorder, and none resulting from any of her sports.
Tendons and other connective tissue are often thought of as non-trainable, but more and more research is showing that they are more responsive to load than we thought. Professor Keith Baar is a leading researcher on the topic and joins this week’s GAINcast to talk about how connective tissue works together with muscles and bones to produce movement. We also dive into how connective tissue can be trained, as well as several other topics he has been researching. [audio, 50:50]
“In North America, the term ‘weekly mileage’ is like the holy grail of distance running performance,” says Dr. Max Paquette. Max is an Associate Professor of Biomechanics in the Human Performance Center at the University of Memphis and is interested in quantifying training load in runners. “Everybody gauges performance, or how well an athlete is training based on how many miles they run per week. For some reason, there seems to be a mythical goal of 100 miles per week. Some coaches even believe that there are necessary mileage thresholds to achieve certain performances. ‘Mileage” is engrained in the running culture.”
Max and one of his Masters students, Megan Ryan, who is a competitive runner and was a member of the University of Memphis cross-country and track teams, have started to question whether there are key aspects of training that mileage alone is not telling the coaches and athletes. Training load monitoring using minutes instead of mileage has become increasingly popular. This is particularly prevalent in high schools where there are large numbers of athletes in training groups. “The human body does not come with an odometer or speedometer. It has no idea how far or how fast we run. It simply knows the extent to which its physiology is changed over the course of a run, which includes a time component.”
Background: The availability of a wide range of innovative wearable sensor technologies today allows for the ability to capture and collect potentially important health-related data in ways not previously possible. These sensors can be adopted in digitalized clinical trials, i.e., clinical trials conducted outside the clinic to capture data about study participants in their day-to-day life. However, having participants activate, charge, and wear the digital sensors for long hours may prove to be a significant obstacle to the success of these trials. Objective: This study explores a broad question of wrist-wearable sensor effectiveness in terms of data collection as well as data that are analyzable per individual. The individuals who had already consented to be part of an asymptomatic atrial fibrillation screening trial were directly sent a wrist-wearable activity and heart rate tracker device to be activated and used in a home-based setting. Methods: A total of 230 participants with a median age of 71 years were asked to wear the wristband as frequently as possible, night and day, for at least a 4-month monitoring period, especially to track heart rhythm during sleep. Results: Of the individuals who received the device, 43% never transmitted any data. Those who used the device wore it a median of ∼15 weeks (IQR 2–24) and for 5.3 days (IQR 3.2–6.5) per week. For rhythm detection purposes, only 5.6% of all recorded data from individuals were analyzable (with beat-to-beat intervals reported). Conclusions: This study provides some important learnings. It showed that in an older population, despite initial enthusiasm to receive a consumer-quality wrist-based fitness device, a large proportion of individuals never activated the device. However, it also found that for a majority of participants it was possible to successfully collect wearable sensor data without clinical oversight inside a home environment, and that once used, ongoing wear time was high. This suggests that a critical barrier to overcome when incorporating a wearable device into clinical research is making its initiation of use as easy as possible for the participant. [full text]
The purpose of this study was to investigate the test-retest reliability and concurrent validity of using the Push Band device 2.0 (PUSH) to quantify repetition velocity across 4 common resistance training exercises performed using free-weight and Smith machine training modalities. Twenty well-trained men (age: 25.1 ± 2.9 years, height: 182.4 ± 6.0 cm, body mass: 77.9 ± 12.0 kg, training age: 5.2 ± 1.4 years) visited the laboratory on 6 occasions (3 free-weight and 3 Smith machine sessions). Baseline strength assessments were conducted in the first session with each modality for squat, bench press, overhead press, and prone row exercises. The subsequent sessions featured repetitions performed with 30, 60, and 90% 1-repetition maximum. During these sessions, velocity was measured simultaneously using a validated linear position transducer (LPT; considered the criterion for this study) and 2 PUSH devices, one in body mode (PUSHBODY) and the other bar mode (PUSHBAR). Test-retest reliability was examined using the intraclass correlation coefficient (ICC) and coefficient of variation (CV). The LPT demonstrated slightly greater reliability (ICC = 0.80–0.98, CV = 0.4–5.1%) than the PUSHBODY (ICC = 0.65–0.95, CV = 0.8–6.9%) and PUSHBAR (ICC = 0.50–0.93, CV = 0.7–7.1%) devices. Near-perfect correlations existed between velocity measured using LPT and PUSH devices (r = 0.96–0.99). No significant differences existed between mean velocity measures obtained using LPT and either PUSH device. The PUSH device can be used in either bar or body mode to obtain reliable and valid repetition velocity measures across a range of loads and exercises performed using either free weights or a Smith machine.
FIFA has awarded “quality certification” to four Electronic Performance Tracking Systems (EPTS) after carrying out the “largest validity study of its kind”.
Catapult’s Clearsky, ChyronHego’s TRACAB Gen5, Fitogether’s OhCoach Cell B and STATSports’ Apex were the products awarded certification.
The main testing was carried out over a four-day period (20, 21, 22 & 23rd November 2018) at Barcelona FC’s Mini Estadi by a research team from Victoria University, supported by the Barcelona Innovation Hub. Phase one testing had been conducted in Melbourne’s Marvel Stadium.
… “A fundamental problem with nutrition science for decades has been that we’ve relied on a very weak kind of science,” Nina Teicholz, told Quirks & Quarks host Bob McDonald. Teicholz is a science journalist and executive director of the Nutrition Coalition — a non-profit organization that doesn’t accept industry funding. [audio, 14:02]
Liverpool manager Jurgen Klopp has lambasted the Christmas fixture schedule as “criminal” – even though his side are by no means the worst affected.
The Premier League leaders travel to second-placed Leicester for an 8pm Boxing Day kick-off before hosting Wolves on December 29.
However, many other sides have two matches in three days and the Liverpool boss – an outspoken critic of the congested calendar on numerous occasions – believes the authorities have got it all wrong.
… Wilson was on the line with his NC State football coach. Wilson had just missed spring practice to play baseball but wanted to return to the football team for his senior season.
Then Tom O’Brien told him he would no longer have his starting job.
A three-year starter at quarterback, Wilson could not accept that. What he did next took quite an emotional toll, but it fueled one of the biggest trends to shake the sport of college football — the rise of graduate transfers.
Gerard Lopez is many things. He’s the majority owner of Lille, but he’s also a Spanish entrepreneur who grew up in a soot-covered house next to a steel mill in Luxembourg. He was recruited to Miami University in Western Ohio to play basketball on a partial scholarship in 1998, but quickly found out that being a high school hoops phenom in Luxembourg was a bit like being the tallest elf. An early investor in Skype and a former Formula One team principal at Lotus, holding degrees in both Asian art and expert systems (basically what we know as artificial intelligence), Lopez says both played a key role in getting him to where he is today: at the nexus of sports, technology and entertainment.
ESPN caught up with him recently for a wide-ranging conversation about how his pursuits intersect.
England’s Women’s Super League became the first fully-professional women’s football league in Europe in 2018.
But when presented with a professional contract, football is not always a financially viable option compared to continuing a different job. Few football clubs offer salary packages comparable to those available in teaching.
What is life like for players who have made that choice? Why do some leave football behind? What influences their choices, and do they have regrets?
… P3 has assessed more than half of the current NBA, most more than once. The standard assessment includes hundreds of data points. Put it all together and it’s a massive database—the spreadsheets literally have so many columns that they exceed the capacity of Excel or Google Sheets. (P3 had to identify a vendor with even bigger spreadsheets.) Who knows what a machine might learn, loosed to swim in that ocean of data? Now every time a player gets hurt, the machine can dig back through all the past measurements, and see what correlations might exist. Does something in the measurement of a 17-year-old predict things in 25-year-olds?
Hell yes, and in powerful ways. The machine learning discovered that NBA players tend to fall into groupings. The P3 staff has given them names. Some of the categories are straight from the scouting report: “hyper-athletic guards,” “traditional bigs,” “athletic bigs.” One group is simply called “specimens.”
They tend to move like each other, and to have injury profiles like each other. Many NBA players are assessed long before they reach the NBA. In his Grand Rounds lecture, Elliott said some clusters “are full of athletes that were injured in their first two or three years.”
It’s fair to say that Tim Waskett is someone who prefers to stay under the radar.
On his LinkedIn profile, it says ‘not at liberty to say’ next to employer. On his Twitter account, he describes himself only as ‘indie games developer’.
Nowhere is there so much as a hint that Waskett is a key member of Liverpool’s research team, widely regarded as the finest data science unit in English football.
Since 2012, the astrophysicist (he has first-class honours in the subject from Cardiff University) has been a software developer and statistical researcher for the current European champions.
This week he emerged from anonymity to give an insight into his work in the annual Royal Institution Christmas Lectures.