The Phoenix Mercury’s star center said Thursday at the first day of USA Basketball camp that she left the WNBA bubble last summer because of mental health reasons and has been undergoing counseling.
“My decision to leave was a hard one to make, especially in the middle of the season,” Griner said. “I never thought I’d be in that situation. Everything that was going on, everything I was dealing with, I needed to take that leave. I definitely used counseling a lot when I left.”
The news hit with a somber jolt. The Wild, in midgame, announced that first-round draft pick Marco Rossi had returned home to Austria to recover after experiencing complications from COVID-19.
This wasn’t some random transaction notice. Not a knee sprain, nor a player being suspended. This was a 19-year-old professional athlete being shut down from activity after a physical flagged something wrong a few months after he was diagnosed with the virus and had seemingly recovered.
Scary stuff.
The reaction in sports is often robotic when a player suffers an injury that will sideline him or her for an extended period. Tough break, good luck in rehab, see you next season, next player up.
Giants assistant coach Alyssa Nakken became the first female coach in MLB history, and took it to the next level by coaching first base against the A’s in an exhibition game. Her Opening Day jersey now hangs in the National Baseball Hall of Fame.G
It might appear to be a lot of responsibility on that front alone, but many of her peers — other female representation in the league in various jobs — have embraced her, and offered her thanks for what she’s done for the industry.
“The other women from the other teams, whether they were analysts, strength coaches or others, would come to me and just say like, ‘Thank you, I now don’t have to like put my clothes under a table in a corner and try and find a space to change,’” Nakken said in an interview with MLB.com. “I think that was just a big improvement, but it also shows just how far we have to go. I mean, come on, it’s 2020. We’re just now finding spaces for females to put on their uniform to go to work.”
Nike and the NFL have pledged $5 million to help make women’s flag football a varsity sport.
In the meantime, Nike and the NFL have combined their efforts on Nike’s 11-Online website, where people can vote to bring varsity flag football to their states and where NFL coaches share some of their drills and exercises with young athletes hoping to improve their skills.
It is here that Zaler walks viewers through a range of dynamic warmup exercises to get them ready for a full workout. The NFL also features videos from NFL Network’s Colleen Wolfe, Rams assistant strength and conditioning coach Chelsea Romero, Washington assistant running backs coach Jennifer King, Browns chief of staff Callie Brownson and former 49ers offensive assistant Katie Sowers.
In 2016, Tiffany Morton made history when she was hired by the Kansas City Chiefs as an assistant trainer, making her the first woman athletic trainer in the NFL. But Morton didn’t see it as a big deal.
“I guess one of the pitfalls of my go-getter attitude is I kind of just didn’t think about it,” Morton tells CNBC Make It. “I was just focusing on trying to get a job.”
Now, Morton, 35, along with fellow female Chiefs trainer Julie Frymyer (who got the job in 2018) and NFL official Sarah Thomas, will be among the six women with on-field roles during Sunday’s Super Bowl. It’s the most women in on-field positions during a Super Bowl in NFL history.
“We’re excited,” says Morton, who was promoting an NFL partnership with Sleep Number 360 smart beds (which measure biometrics like heartrate and breathing to help people track their sleep).
There was a time when Rachel Balkovec wondered whether baseball’s most important jobs would ever be open to women. Pleased by recent progress in that regard, the second-year Yankees Minor League hitting coach believes that there is more change to come.
“My journey in sports and working in sports has been pretty treacherous at times, so it’s really cool to see women in sports being so widely celebrated,” Balkovec said.
International Journal of Sports Physiology and Performance from
The session rating of perceived exertion (sRPE) method was developed 25 years ago as a modification of the Borg concept of rating of perceived exertion (RPE), designed to estimate the intensity of an entire training session. It appears to be well accepted as a marker of the internal training load. Early studies demonstrated that sRPE correlated well with objective measures of internal training load, such as the percentage of heart rate reserve and blood lactate concentration. It has been shown to be useful in a wide variety of exercise activities ranging from aerobic to resistance to games. It has also been shown to be useful in populations ranging from patients to elite athletes. The sRPE is a reasonable measure of the average RPE acquired across an exercise session. Originally designed to be acquired ∼30 minutes after a training bout to prevent the terminal elements of an exercise session from unduly influencing the rating, sRPE has been shown to be temporally robust across periods ranging from 1 minute to 14 days following an exercise session. Within the training impulse concept, sRPE, or other indices derived from sRPE, has been shown to be able to account for both positive and negative training outcomes and has contributed to our understanding of how training is periodized to optimize training outcomes and to understand maladaptations such as overtraining syndrome. The sRPE as a method of monitoring training has the advantage of extreme simplicity. While it is not ideal for the precise recording of the details of the external training load, it has large advantages relative to evaluating the internal training load.
An affordable player monitoring solution could make the evaluation of external loading more accessible across multiple levels of football (soccer). The present study aimed to determine the accuracy of a newly designed and low-cost Global Positioning System (GPS) whilst performing match-specific movement patterns. Sixteen professional male football players (24 ± 3 years) were assigned a GPS device (TT01, Tracktics GmbH, Hofheim, Germany) and completed two experimental trials. In each trial, a continuous protocol including seven movements (sideways cornering, diagonal cornering, accelerating, decelerating, backwards jogging, shuttle running, and skipping) adding up to 500 m, was completed. Time-motion data was compared with criterion distance and velocity (photo-cell timing gates and radar). Validity was assessed through the standard error of the estimate (SEE) and reliability through the coefficient of variation (CV; both with 95% confidence limits). For the total distance covered during the protocol, the system was found to be valid (SEE = 3.1% [2.2; 5.8]) and reliable (intra-device CV = 2.0% [1.2; 7.6]). Similar results were found for velocity (SEE = 3.4% [2.6; 4.8], CV = 4.7% [3.2; 8.5]). In conclusion, the present GPS system, a low-cost solution, was found to be a valid and reliable tool for measuring physical loading during football-specific movements. [full text]
A long-standing challenge in motor neuroscience is to understand the relationship between movement speed and accuracy, known as the speed-accuracy tradeoff. Here, we introduce a biomechanically realistic computational model of three-dimensional upper extremity movements that reproduces well-known features of reaching movements. This model revealed that the speed-accuracy tradeoff, as described by Fitts’ law, emerges even without the presence of motor noise, which is commonly believed to underlie the speed-accuracy tradeoff. Next, we analyzed motor cortical neural activity from monkeys reaching to targets of different sizes. We found that the contribution of preparatory neural activity to movement duration (MD) variability is greater for smaller targets than larger targets, and that movements to smaller targets exhibit less variability in population-level preparatory activity, but greater MD variability. These results propose a new theory underlying the speed-accuracy tradeoff: Fitts’ law emerges from greater task demands constraining the optimization landscape in a fashion that reduces the number of ‘good’ control solutions (i.e., faster reaches). Thus, contrary to current beliefs, the speed-accuracy tradeoff could be a consequence of motor planning variability and not exclusively signal-dependent noise. [full text]
… I feel like a broken record saying this, but the NWHL began its condensed season in Lake Placid in what was not a bubble. Players and staff had to test negative within 72 hours of departing, and were also tested upon arrival – but with no required quarantine period, there was never any guarantee that COVID wasn’t being unknowingly brought in by one or multiple persons.
The number of anti-doping tests conducted by the International Tennis Federation (ITF) declined for the first time in ten years in 2020, illustrating the impact that Covid-19 is likely to have on the testing programmes of international sporting federations. The ITF reported 3,282 tests in 2020, its lowest number since 2013, and the first time that ITF testing numbers have fallen since 2010.
The total tests performed by the ITF in 2020 were less than half the 7,793* reported in 2019, as the number of tests performed both in competition and out of competition fell. Other sporting federations are likely to report a similar fall in testing numbers, due to the difficulty of complying with lockdown restrictions, health and hygiene procedures whilst also maintaining anti-doping protocol, which requires athletes being tested to be monitored at all times.
American Chemcal Society, ACS News Service Weekly Press Pac from
All athletes want to be at the top of their game when they compete, but some resort to nefarious approaches to achieve peak muscle growth, speed and agility. Recent developments in gene editing technology could tempt athletes to change their DNA to get an edge. Now, researchers reporting in ACS’ Analytical Chemistry demonstrate first steps toward detecting this type of doping both in human plasma and in live mice.
… An executive who spoke to TrueHoop says he had a most unusual conversation with a high-powered agent. Like the Warriors, his team had been ravaged by injuries and needed fast help. The call began in standard fashion: The executive asked if such-and-such free-agent clients were in shape and ready to go. The agent replied yes, several of them were.
Good. They went back and forth on some candidates, but both could sense that neither had asked the real question. Nobody had addressed the elephant in the room.
Finally, the agent blurted it out: “Remember … he’s had COVID-19 already. He might be, um, more employable for you.”
Making Sense Of: Bad Black Boxes
Cynthia Rudin, machine learning professor at Duke University, works on interpretable machine learning, that is, algorithms that are both predictive and explainable, as opposed to black box algorithms, which might be predictable and definitely are not explainable. Her recent Harvard Data Science Initiative seminar, “Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and use Interpretable Models Instead,” is on YouTube.
Injury prediction algorithms are the holy grail of modern sports science, the ideal combination of athlete preparation, sports medicine and quantitative data analysis. Most, maybe all, of these algorithms are blackboxes created by data analysts, and if you believe Dr. Rudin, they’re worthless.
The gain in accuracy with Interpretable AI comes from understanding what you’re doing, according to Rudin. If you have a black box model that sort of works, and you have a model explanation that expressed the problem and offered an understandable prediction, the accuracy afforded by the explanation is far greater. They’re both models but one of them makes sense.
For low stakes decisions a blackbox is okay. Who cares, right? But high-stakes decisions really need the extra accuracy, or more precisely, need to avoid the inaccuracy of blackbox algorithms. Sports injuries are high stakes, for the athlete, for the team on the field and for the front office.
The path to Interpretable AI in sports is 100% collaborative. Training staffs, sports medicine personnel, data analysts and front office decision-makers need to get on the same page.
Thanks for reading. And thanks to everyone who contributed to the newsletter in January. The support is a huge help.
-Brad
