… At eight months pregnant, Morgan is facing the fact that she’s done everything in her power to be ready for the field only for the chance to disappear in the list of canceled moments that have characterized 2020. But like the steely competitor she is, she’s comfortingly unrattled by the whole thing—and already looking to the next goal. “We can only hypothesize over so much uncertainty in the future,” she says. Whether the next chance to play comes in the next three months or in the next year, she’ll be ready. “If I have no goal to try to achieve” she says, “then that’s not true to the core of who I am.”
Morgan kept up with her regular training schedule (which included six days a week of intense workouts—on-the-field sessions, weight training, Spin classes, runs) until she was seven months pregnant before letting off the gas to adopt an easier version of that routine (regular jogs, physical therapy, pelvic-floor physical therapy, prenatal yoga). Still, the idea that she’d risk her run for the gold to do something as predictable and potentially limiting as getting pregnant drew critics.
… “The hardest thing to evaluate is the heart and the head,” says Tampa Bay Buccaneers coach Bruce Arians, who has coached quarterbacks who could occupy an entire wing of the Hall of Fame. “I call it grit” — always with the grit — “and it shows whether they have leadership skills, whether guys follow them and whether they can make guys believe in them. That’s the hardest part. You can see everything else.”
The quarterback is the most important player on the field and probably the most important figure in American team sports. A great one can lift a team to the highest heights, and a bad one can consign it to a decade of aggravation. Teams invest a remarkable amount of capital, brainpower and sweat equity into finding, nurturing and pampering a good one. But on draft night, after all the evaluations of mental acuity and arm talent and grit, how much of the decision remains a guess?
Arians shrugs and answers quickly, as if citing a scientific study. “Thirty percent,” he says. “And that’s if you’ve really done all the work and you get lucky.”
… I chose a morning sport despite never being a morning person and loving a lie-in. This at least meant I was a glutton for punishment, which is a helpful trait in rowing.
Life in the GB rowing team revolves around the training programme, which is sent out in fortnightly instalments. We complete three training sessions a day and get every other Sunday off.
When you factor in the fatigue it does not really leave much room for anything else in life. Hence, life in the team becomes quite a selfish and monastic existence and it takes a lot of drive to stay the course and lends itself to those with an obsessive nature.
Research has demonstrated that induced mental fatigue impairs soccer-specific technical, tactical and physical performance in soccer players. The findings are limited by the lack of elite players and low ecological validity of the tasks used to induce mental fatigue, which do not resemble the cognitive demands of soccer. The current study collected survey data from English academy soccer players (n = 256; age groups – U14 – U23), with questions comprising of five themes (descriptors of physical and mental fatigue, travel, education, match-play and fixture congestion). The survey consisted of multiple choice responses, checkboxes and blinded/unblinded (for duration based questions) 0-100 arbitrary unit (AU) slider scales. Listening to music (81.6% of players), using social media (58.3%) and watching videos (34.3%) were the most common pre-match activities. Pre-match subjective mental fatigue was low (18.7±18.8 AU), and most frequently reported at the end of a match (47±26 AU) and remained elevated 24-hours post-match (36±27 AU). Travel (29±24 AU), fixture congestion (44±25 AU) and education (30±26 AU) demonstrated a low to moderate presence of subjective mental fatigue. These findings provide an overview of activities performed by English academy soccer players pre-match, and demonstrate that mental fatigue is experienced as a result of match-play.
New research from Stanford University has found that stress can hinder our ability to develop informed plans by preventing us from being able to make decisions based on memory.
“We draw on memory not just to project ourselves backward into the past but to project ourselves forward, to plan,” said Stanford psychologist Anthony Wagner, who is the senior author of the paper detailing this work, published April 2 in Current Biology. “Stress can rob you of the ability to draw on cognitive systems underlying memory and goal-directed behavior that enable you to solve problems more quickly, more efficiently and more effectively.”
SportRXiv Preprints; Anthony Brady, Sam Briend, Alex Caravan, Kyle Lindley, Michael O'Connell, Griffin Gowdey, Kyle Boddy from
The stride phase of the baseball throwing motion is an influential aspect in throwing performance as described in previously published literature. The Rocker drill is a constraint that is often used to change or improve baseball throwing performance throughout a wide range of settings, coaches, and training programs. Due to the lack of quantified and documented effects of the Rocker drill on throwing mechanics, this study aims to identify the resulting changes in performance, kinematics, kinematic velocities, and kinetics from the Rocker drill and a variation of the Rocker drill to determine which constraint may promote more effective mechanical changes. We hypothesize that the normal Rocker drill will have significantly different throwing arm, trunk, and lower body kinematic positions at front Foot Plant, maximum throwing shoulder external rotation, and Ball Release, as well as significantly different ball velocity, maximum kinematic velocities, and throwing elbow kinetics when compared to the “Foot-up” variation of the Rocker drill. A total of 30 healthy baseball pitchers with collegiate or professional competition experience threw three to five regulation baseballs out of the “stretch” pitching position, the Rocker drill, and a less constrained, Foot-up variation of the Rocker drill as close to maximal intent as possible. [full text]
To evaluate the effects of injury prevention programmes on injury incidence in any women’s football code; explore relationships between training components and injury risk; and report injury incidence for women’s football. DESIGN:
Systematic review and meta-analysis. DATA SOURCES:
Nine databases searched in August 2019. ELIGIBILITY CRITERIA:
Randomised controlled trials evaluating any injury prevention programme (eg, exercise, education, braces) were included. Study inclusion criteria were: ≥20 female football players in each study arm (any age, football code or participation level) and injury incidence reporting. RESULTS:
Twelve studies, all in soccer, met inclusion criteria, with nine involving adolescent teams (aged <18 years). All studies (except one) had a high risk of bias. Eleven studies examined exercise-based programmes, with most (9/11) including multiple (≥2) training components (eg, strength, plyometric, balance exercises). Multicomponent exercise programmes reduced overall (any reported) injuries (incidence rate ratio (IRR) 0.73, 95% CI 0.59 to 0.91) and ACL injuries (IRR 0.55, 95% CI 0.32 to 0.92). For exercise-based strategies (single-component and multicomponent), hamstring injuries were also reduced (IRR 0.40, 95% CI 0.17 to 0.95). While exercise-based strategies resulted in less knee, ankle and hip/groin injuries, and the use of multiple training components was associated with greater reductions in overall and knee injuries, further studies would be required to increase the precision of these results. The incidence of overall injuries in women's football was 3.4 per 1000 exposure hours; with ankle injuries most common.
CONCLUSION:
In women’s football, there is low-level evidence that multicomponent, exercise-based programmes reduce overall and ACL injuries by 27% and 45%, respectively.
A couple of decades ago, Jeff Alger, then a senior manager at Microsoft, was coaching state-level soccer teams and realized that there was very little science to player development.
“There were no objective ways of measuring how good players are,” said Mr. Alger, “and without being able to measure, you have nothing.”
He said it offended his sense of systems design to recognize a problem but do nothing about it, so he quit his job, got a master’s degree in sports management and started a company that would use artificial intelligence to assess athletic talent and training.
His company, Seattle Sports Sciences, is one of a handful using the pattern-recognizing power of machine learning to revolutionize coaching and make advanced analytics available to teams of all kinds.
The trend is touching professional sports and changing sports medicine. And, perhaps inevitably, it has altered the odds in sports betting.
John Milton, the architect of Seattle Sports Sciences’ artificial intelligence system, spent a week in October with the Spanish soccer team Málaga, which plays in Spain’s second division, capturing everything that happened on the pitch with about 20 synchronized cameras in 4K ultra high-definition video.
“It’s like omniscience,” Mr. Milton said. The system, ISOTechne, evaluates a player’s skill and consistency and who is passing or receiving with what frequency, as well as the structure of the team’s defense. It even tracks the axis of spin and rate of rotation of the ball.
… some have questioned whether Alabama’s use of the watches violates NCAA guidelines. “I don’t know, maybe [Alabama] got a different interpretation or something,” Clemson head football coach Dabo Swinney said during a Friday conference call, per ESPN’s Mark Schlabach. “There are a lot of different interpretations out there right now.”
An Alabama spokesman told ESPN on Friday that only director of sports medicine Jeff Allen is viewing information collected by the players’ Apple watches, including sleeping patterns, heart rates during workouts and other health-related data.
Matt Self, Alabama’s senior associate athletics director for compliance, said in a statement: “The SEC is aware that Alabama provided Apple Watches to some of our student-athletes. We are in constant communication with the SEC discussing the appropriate manner in which to utilize these and any other resources to provide for the health and well-being of our student-athletes during this crisis.”
… “There’s really not a tool out there that lets you teach and communicate with your players like Learn to Win,” [Tommy] Hatton said. “People have been responsive to it, because they’ve been seeing this as the only option right now with the restrictions and because of the effectiveness to actually learn through our platform.”
The platform is now being utilized by more than 100 football and basketball programs across the college and high school levels. It gives coaches the opportunity to build lessons, quizzes, installs, playbooks and diagrams all in one place to help their athletes learn the concepts. Beyond handwritten quizzes on plays and game plans, as well as tip sheets that coaches had been using for years, those concepts weren’t able to provide real-time feedback on what the players were actually absorbing and what they were missing.
Video Object Detection is a very interesting problem that could help a lot of people. I found out about it talking to a shark researcher (maybe not his exact title). They have grad students counting sharks in a video from an underwater camera. These videos can be very long and sometimes there are no sharks in hours. I thought about Machine Learning instantly, what could go wrong. I started reading about it and found different approaches.
Auto ML Solution (Google, MSFT…): I used these solutions in the past with images, with good results. The con is that these services do not provide video support, at least I was not able to find it.
Tensorflow: I watched a ton of videos of examples of the Object Detection API. Be careful with the videos, search for recent ones the version changes can make very hard to follow the tutorial. I had some trouble trying to train the model with my own images. It might have been a combination of the documentation, my package management and maybe luck. I ended looking for another way.
Tensorflow Object Counting API: I found this repository. It has great examples and it’s built on top of Tensorflow. I still had some problems training my own images. My only comment would be that this API still lacks the abstraction I wanted to see on an API, at least for the training part.
Detecto: I found about this repository and the first thing I noticed was that it promised the abstraction I was looking for. I managed to train with my own images, all the different examples are ~5 lines of code. You don’t need to understand about Pytorch in order to use it.
If you shout something loud enough, and with enough confidence, people will listen. This is independent of the information you are sharing: it could be total nonsense! We get bombarded with nutrition information through social media. Some of it comes from people who have a solid background in nutrition, some of it even from experts in the field, but the vast majority of information seems to be from people who have “an opinion” but no background in the matter at all. I often say: “everyone who eats and drinks is an expert in nutrition these days”. It appears that these people, not impaired by knowledge, voice their opinion, often passionately, sometimes aggressively through various social media channels. For athletes it is not always easy to separate fact from fiction.
The Dunning-Kruger Effect, named after two physiologists (Dunning and Kruger) is a cognitive bias whereby people who are incompetent, are unable to recognize their own incompetence. And worse, they do not only fail to recognize their incompetence, they actually feel confident that they are competent.
In the field of sports nutrition we see this on a daily basis. Someone has read something about a nutrition topic, a diet, a supplement or something else, on social media and has googled a bit more around the topic. Now they are confident to share their experience with the rest of the world. The fact isn that only know a little (and of this little knowledge some of it may be right, and some of it may be wrong, because without detailed and deeper knowledge and good education, it is difficult to distinguish good from bad information). But this bit of knowledge, gives them confidence to shout about their views. Someone who knows nothing at all about a topic will not be very not very confident, and will admit they know nothing about the topic. But those who have a little knowledge, but not enough to realise how much they don’t know, and how much more there is to learn, will have a huge amount of confidence. This is sometimes referred to as Mount Stupid (see infographic). This is also the origin of the statement: “he knows enough to be dangerous”.
“This handbook is more geared at some of the technical skills, concepts, and sports analytics history that I think are worth familiarizing yourself with.”
Sports Illustrated, Ross Dellenger and Pat Forde from
Administrators and insiders weigh in as the coronavirus threatens the college football season—and explain why the entire NCAA system could hang in the balance.