Liverpool manager Jürgen Klopp dampened hopes of Virgil van Dijk playing for the Netherlands at the European Championship, saying it will be “very, very tight” whether the defender can be fit in time.
It all started with a casual chat at Dallas Stars training camp. Third-year winger Adam Mascherin mentioned to Texas Stars head coach Neil Graham that he and rookie center Riley Damiani had played together on and off in the Ontario Hockey League for two years.
It turned out to be a momentous side conversation.
“I remember telling [Texas Stars assistant coach] Travis Morin that we should be sure to start these two together at camp,” said Graham. “Maybe we’ll see how it blossoms and if it doesn’t work, we’ll make adjustments.”
… When Zelem landed in northern Italy back in August 2017, the culture shock was intense and instantaneous. “Turin’s not a touristy place like Rome or Milan and I soon realised no one in the airport spoke English,” she says. “The full extent of my Italian ran to ‘ciao’ so nothing was straightforward. For the first week I thought: ‘Wow, what have I done.’ Nobody in the shops understood me and doing the basics was very difficult.”
A city-centre flat share with a teammate, the New Zealand international Katie Rood, now playing for Lewes, transformed the mood music. “Katie and I still get on really well,” says Zelem. “But we’re so very, very, different as people it’s the most unlikely friendship. No one can believe we like each other but we were thrown together and had to make it work.
“Living abroad does that to you; Italy changed me into a different player but it developed me even more as a person. It made me independent – and left me with a lot of respect for all the overseas players coping so well in England.”
… “Marc is an incredibly valuable member of our team who incorporates science and technology to maximize the potential of our student-athletes,” Fuente continued. “But even more importantly, Marc serves as a real-life example of someone who embodies the traits we value the most as a football team. Whether it’s the unimaginable stress of his upbringing, his heroic service to our country in the U.S. Army, or his steadfast determination to get a college degree, Marc has deservedly earned the respect of our players, coaches, and staff. He’s a remarkable man with a remarkable story. I’m extremely grateful to have someone who possesses his talent and character working with our young men on a daily basis.”
The team had just gotten some new GPS training equipment, which allows detailed information about practice performance to be viewed and analyzed by coaches.
Lewis focused his dissertation on this same topic – athlete monitoring in American collegiate football.
Lewis implemented this monitoring with the football team, helping players reach their full athletic potential. Equipped with a GPS monitoring device and heart rate monitor, he’s able to download a set of 125 variables for each player after practice.
This is a polarising topic and one in which there are multiple perspectives and positions on this subject. However, for the purposes of brevity I will restrict my analysis and comparisons to physiotherapists and strength and conditioning (S&C) professionals working with athletic populations.
Historically the physiotherapist has reigned ‘top dog’ in the management hierarchy of the injured athlete, and for that matter any individual that has needed exercise as a method to ameliorate illness, disease or to improve physical function. Physiotherapy as a profession has been in existence for well over 100 years since its humble beginnings at the outbreak of world war one (1). This is in stark contrast to the strength and conditioning profession which only in the past 20 years has seen significant strides forwards in regard to its professional standing within professional sport and with the general public.
Historically, exercise prescription has been the preserve of the physiotherapy profession as a default. However, this precedent has not kept pace with the professional developments in S&C, exercise science and S&C research. I would argue that the physiotherapy profession has for too long rested on its laurels and paternalism with the medical profession, and it has fallen out of step with the emerging S&C profession in regard to professionalism. This is evident in the wanton clamour for short weekend style courses in S&C training by sectors of the physiotherapy profession to fill a gap in knowledge and expertise.
This study investigated the activity profile during small-sided games (SSG) in elite youth soccer players. Internal load (IL) including heart rate (HR) and external load (EL) such as distance covered in different speed-zones (SZ) were collected from forty-eight players of three different teams (U15, U16, U18). The investigation included a total of eighteen 5vs.5 SSGs, each consisting of four 2-minute bouts on a 40x32m pitch during spring season. Total group results (n = 48) showed a reduction in total-distance (p = 0.001; = 0.12), high-intensity-running (p = 0.009; = 0.09), and low-intensity-running distance (p = 0.028; = 0.07) between bouts. Similarly, a reduction in the number of both acceleration-low (p = 0.001; = 0.12) and deceleration-high (p = 0.003; = 0.11) values was observed. Additionally, time spent in HR-zones 3 and 4 (p≤0.007; ≥ 0.10), increased, with a reduction in HR-zone 1 (p = 0.000, = 0.25). Age group comparison showed less distance covered in SZ 1 (p≤0.000; = 0.56) and greater deceleration-high values (p≤0.038; = 0.32) in U15 players compared to other age groups. Further, U15 showed lower values in low-intensity-running compared to U18 (p = 0.038; = 0.22). No age-related differences were found for IL and repeated sprint ability (RSA) values. The higher EL in younger age groups should be taken into account when implementing soccer specific SSGs. In addition, HRmean values between 80–85% of HRmax and RSA numbers, which are similar to match-play data, indicate SSGs as an effective training tool to prepare youth soccer athletes for the demands of competition. [full text]
Introduction: Most running-related injuries are believed to be caused by abrupt changes in training load, compounded by biomechanical movement patterns. Wearable technology has made it possible for runners to quantify biomechanical loads (e.g., peak positive acceleration; PPA) using commercially available inertial measurement units (IMUs). However, few devices have established criterion validity. The aim of this study was to assess the validity of two commercially available IMUs during running. Secondary aims were to determine the effect of footwear, running speed, and IMU location on PPA.
Materials and Methods: Healthy runners underwent a biomechanical running analysis on an instrumented treadmill. Participants ran at their preferred speed in three footwear conditions (neutral, minimalist, and maximalist), and at three speeds (preferred, +10%, −10%) in the neutral running shoes. Four IMUs were affixed at the distal tibia (IMeasureU-Tibia), shoelaces (RunScribe and IMeasureU-Shoe), and insole (Plantiga) of the right shoe. Pearson correlations were calculated for average vertical loading rate (AVLR) and PPA at each IMU location.
Results: The AVLR had a high positive association with PPA (IMeasureU-Tibia) in the neutral and maximalist (r = 0.70–0.72; p ≤ 0.001) shoes and in all running speed conditions (r = 0.71–0.83; p ≤ 0.001), but low positive association in the minimalist (r = 0.47; p < 0.05) footwear condition. Conversely, the relationship between AVLR and PPA (Plantiga) was high in the minimalist (r = 0.75; p ≤ 0.001) condition and moderate in the neutral (r = 0.50; p < 0.05) and maximalist (r = 0.57; p < 0.01) footwear. The RunScribe metrics demonstrated low to moderate positive associations (r = 0.40–0.62; p < 0.05) with AVLR across most footwear and speed conditions.
Discussion: Our findings indicate that the commercially available Plantiga IMU is comparable to a tibia-mounted IMU when acting as a surrogate for AVLR. However, these results vary between different levels of footwear and running speeds. The shoe-mounted RunScribe IMU exhibited slightly lower positive associations with AVLR. In general, the relationship with AVLR improved for the RunScribe sensor at slower speeds and improved for the Plantiga and tibia-mounted IMeasureU sensors at faster speeds.
Nextiles, a textiles manufacturing startup backed by the National Science Foundation (NSF) and Massachusetts Institute of Technology (MIT), is launching into the sports and performance market to provide smart thread technology that captures biometric and biomechanics data. Spun out of academia, Nextiles was founded in 2018 while George Sun, a trained biological and electrical engineer, was finalizing his PhD in biomaterials at MIT. While attending MIT’s Media Lab, Sun was recruited to lead the embedded engineering team at PUMA, with a focus on incorporating sensors into footwear. Through his work, he was inspired to recreate the sensor industry and provide a superior form factor by developing a now-patented technique to sew sensors directly into fabric. In its early stages of development, Nextiles was recognized and awarded by MIT to fund further optimization of the smart fabric technology and was also selected to go through MIT’s accelerator program, Delta-V and finally joining the Newlab community in Brooklyn.
Behind the science, Nextiles blends traditional sewing techniques with printed circuit boards to make flexible material with sensors embedded within fabrics, such as your everyday sportswear. Through its patent-protected manufacturing process, Nextiles’ fabrics allow for complete biomechanic and biometric sensing captured on one platform – no straps, rings, wraps or clunky attachments that only capture partial data. Nextiles leverages the use of traditional sewing machines and commonly found threads, such as nylon or spandex. The threads used are semi-conductive, which measure mechanical changes from multiple data points. Nextiles differentiates its suite of data analytics by providing Newtonian measurements through its fabrics (force, bending, stretching, velocity, pressure) to offer athletes and teams data such as torque, power, fatigue, strain, and much more. The fabric captures traditional measurements as well by combining force data with IMU technology (direction, speed, distance). Nextiles provides clients with APIs and SDKs to stream data via Bluetooth in real-time and offers the ability for data to be stored locally and in the cloud.
Sportico, Scott Soshnick and Eben Novy-Williams from
Intel Corp. is exploring a sale of its sports division, a unit that focuses on immersive video for leagues, broadcasters and fans, according to multiple people familiar with the matter.
The Intel Sports Group’s main initiative is True View, which builds three-dimensional, 360-degree video through an array of cameras installed in a stadium or arena. The unit works with more than two dozen teams across the NFL and NBA, along with a handful of European soccer clubs.
The computer processor manufacturer, which has a market cap of about $230 billion, has retained PJT Partners to assist with the possible sale, according to the people, who were granted anonymity because the discussions are private. Possible suitors could include tech companies, media platforms, or one of the many sports technology SPACs still seeking a target.
The SAP-NHL Coaching Insights App for iPad, upgraded with new features in Version 3.0 this season, is helping NHL coaches get the most out of their players in new ways.
Take Connor McDavid, the NHL leading scorer with 84 points (28 goals, 56 assists) in 47 games. Edmonton Oilers coach Dave Tippett wants to play the center as much as possible but must manage his ice time to keep him fresh.
Tippett no longer has to guess on the bench or wait for numbers between periods.
“I’ll just say, ‘Where’s Connor at?’ ” Tippett said.
An assistant can tap his iPad Pro and give Tippett instant, accurate data from the app, such as how much McDavid has played in game time or how much he has rested in real time as of that second.
Artificial intelligence (AI) represents the fourth industrial revolution and the next frontier in medicine poised to transform the field of orthopaedics and sports medicine, though widespread understanding of the fundamental principles and adoption of applications remain nascent. Recent research efforts into implementation of AI in the field of orthopaedic surgery and sports medicine have demonstrated great promise in predicting athlete injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting the patient experience. Not unlike the recent emphasis thrust upon physicians to understand the business of medicine, the future practice of sports medicine specialists will require a fundamental working knowledge of the strengths, limitations, and applications of AI-based tools. With appreciation, caution, and experience applying AI to sports medicine, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. In this Current Concepts review, we discuss the definitions, strengths, limitations, and applications of AI from the current literature as it relates to orthopaedic sports medicine.
… Scientists already suspected that head injuries were more common, and required longer recovery times, in female athletes. But concrete data were lacking, says neuropathologist Willie Stewart at the University of Glasgow, UK, who led the study. “We’re doing so little research in female athletes,” he says. Such a large volume of data on sports injuries, collected by the Michigan High School Athletic Association, offered an opportunity to investigate whether female athletes really are at higher risk of concussion (see ‘Concussion risk’).
The subject of stealing signs in Major League Baseball has once again come to the forefront this week, and I can’t help but wonder if a good number of people need a refresher on what kinds of stealing are acceptable and simply just part of the game, and what kinds of sign stealing are not acceptable. Further, I can’t help but wonder if we’re collectively getting too sucked in to catching things on video in slow motion.
Twice within the last week, there’s been at least mild controversy made over the matter of sign stealing that leads me to believe we could take a collective breath here.
NFL coaches love to talk about the concept of complementary football. Offense and defense feeding off each other’s success toward the common goal of victory.
As it turns out, complementary mathematics can be just as crucial on the analytics side, as two University of Pittsburgh doctoral students recently proved in the league’s 2021 Big Data Bowl, a massive data science competition in which more than 200 teams from all over the world compete to impress a panel of judges — including coaches — with fresh ideas.
Wei Peng and Marc Richards did just that in collaborating on the winning entry, crowned last month during a slickly produced Zoom broadcast on which they presented their models measuring the effectiveness of defensive backs.