It’s been a rough year for AL second basemen on the wrong side of 30. Robinson Cano, 35, was recently hit with an 80-game PED suspension. Dustin Pedroia, 34, played just three games last week before going back on the disabled list with inflammation in the same knee that had sidelined him for the season’s first two months. Jason Kipnis has played more like 41 years old than 31, and fellow 31-year-old Brian Dozier has been merely average. The oldest of them all, the soon-to-be 36-year-old Ian Kinsler, has been one of the majors’ worst. It’s increasingly possible that his days as a productive regular are over.
Very few players can claim to have had a 2018 quite like Nikita Parris. The flying Manchester City winger scored 11 goals from January on in all competitions for her club while her record of eight goals in 22 appearances for her country is impressive to say the least.
Despite her brilliance and continuous improvement on the pitch, questions and criticisms over her temperament and antics on the pitch have circled over the 24-year-old since she hit the big-time.
But Parris says she has “matured” as a player and adds her passion comes from a sheer will to win football matches.
“I think I’ve grown as a player and a person,” said the Liverpool-born winger. “I’d say I’ve matured. On the odd occasion you might still find me shouting or screaming at a referee because I do get increasingly frustrated but I have tried to control my temper.
Bayern Munich’s Joshua Kimmich spoke recently on the fitness routine that’s seen him perform at an iron man-like level the last few years. In an interview with the German newspaper TZ, Kimmich briefly outlined some of the key components of his physical preparation program, giving us a fascinating glimpse into the behind-the-scenes work that has kept one of game’s best fullbacks on the field and performing at a world class level.
In the interview, Kimmich mentions four key components to his training, 1) an emphasis on post-training and post-match recovery work, 2) training that stresses stabilization activities, 3) training that focuses on lower body power development, and 4) activities that are centered on mobility and flexibility.
Brian Peters joined the Texans in 2015. The 6-foot-4-inch linebacker, #52, played football at Northwestern University and took a circuitous route to Houston. He played for the Arena Football League, the United Football League and the Canadian Football League before reaching his ultimate goal: the National Football League. Peters, 29, spoke with Pulse about diet, mental discipline and giving back.
Previous research has established that general sleep screening questionnaires are not valid and reliable in an athlete population. The Athlete Sleep Screening Questionnaire (ASSQ) was developed to address this need. While the initial validation of the ASSQ has been established, the clinical validity of the ASSQ has yet to be determined. The main objective of the current study was to evaluate the clinical validity of the ASSQ. Methods
Canadian National Team athletes (N = 199; mean age 24.0 ± 4.2 years, 62% females; from 23 sports) completed the ASSQ. A subset of athletes (N = 46) were randomized to the clinical validation sub-study which required subjects to complete an ASSQ at times 2 and 3 and to have a clinical sleep interview by a sleep medicine physician (SMP) who rated each subjects’ category of clinical sleep problem and provided recommendations to improve sleep. To assess clinical validity, the SMP category of clinical sleep problem was compared to the ASSQ. Results
The internal consistency (Cronbach’s alpha = 0.74) and test-retest reliability (r = 0.86) of the ASSQ were acceptable. The ASSQ demonstrated good agreement with the SMP (Cohen’s kappa = 0.84) which yielded a diagnostic sensitivity of 81%, specificity of 93%, positive predictive value of 87%, and negative predictive value of 90%. There were 25.1% of athletes identified to have clinically relevant sleep disturbances that required further clinical sleep assessment. Sleep improved from time 1 at baseline to after the recommendations at time 3. Conclusions
Sleep screening athletes with the ASSQ provides a method of accurately determining which athletes would benefit from preventative measures and which athletes suffer from clinically significant sleep problems. The process of sleep screening athletes and providing recommendations improves sleep and offers a clinical intervention output that is simple and efficient for teams and athletes to implement.
Everyone knows, or has been, the athlete who dives head-first into volume and intensity, only to end up tired and slow come race day. In my last article I touched upon the physical and mental benefits of a “training camp.” But on the opposite end of the spectrum comes a possibly more important phase—what you do day in and day out. How do you plan your recovery and return to a consistent and sustainable training schedule after a big block of training? Let’s take a look.
After returning from a month on the road with UnitedHealthcare Pro Cycling’s early season training camp (and my first race of the season at Oro y Paz) it was clear I was going to need some recovery. Beyond the physical aspects, I was craving a mental break and a “return to normalcy.” Having meals, bottles and ride food prepared, laundry done, and daily massage gives you ample time to rest, but after a while it can leave you feeling like a robot.
Humans can perform a vast array of mental operations and adjust their behavioral responses based on external instructions and internal beliefs. For example, to tap your feet to a musical beat, your brain has to process the incoming sound and also use your internal knowledge of how the song goes.
MIT neuroscientists have now identified a strategy that the brain uses to rapidly select and flexibly perform different mental operations. To make this discovery, they applied a mathematical framework known as dynamical systems analysis to understand the logic that governs the evolution of neural activity across large populations of neurons.
“The brain can combine internal and external cues to perform novel computations on the fly,” says Mehrdad Jazayeri, the Robert A. Swanson Career Development Professor of Life Sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study. “What makes this remarkable is that we can make adjustments to our behavior at a much faster time scale than the brain’s hardware can change. As it turns out, the same hardware can assume many different states, and the brain uses instructions and beliefs to select between those states.”
The arms of baseball pitchers have to endure massive forces in order launch balls up to 100 miles per hour and injuries are common. A team at Ohio State University is using high tech tools, and the world’s most advanced pitcher mound, to gather a myriad of data points in order to better understand why injuries occur and what really happens to the human body during pitching.
The researchers combine on-field data, such as pitch count, games played, and such, with lab data that includes 3D motion tracking of pitches and detecting forces applied across the lower body. A mound with pressure sensors was created that is used along with cameras and position markers to record the movement of the pitcher’s body and what it is experiencing.
… “I think fitting is a collaborative effort between the fitter and the player,” he says. Before anyone takes a swing, he talks to the player. “If it’s a nine-year-old kid, I will talk to both the player and the parent, but I’ll slowly move the conversation to where the player is answering.”
He says that with the younger players, it is harder for them to open up. So, the first thing he asks is, “What are your goals?”
Spencer makes sure that the player understands a player can’t give incorrect answers to the questions he asks. “As objective as the data is, data doesn’t care about your feelings; data doesn’t care if you’re having a good day or a bad day. It’s going to display what happened on that last hit. It knows no bias,” he says.
For the past two decades, the benefits of high-protein nutritional regimes have been relentlessly marketed to the general public, largely through the booming diet, fitness and protein supplement industries. However, while this has lined corporate pockets – the whey protein supplement industry alone was worth $9.2bn (£6.9bn) in 2015 – scientific research has suggested time and again that it may be harming our health.
Adding to the mound of evidence, a recently published study by researchers at the University of Eastern Finland, who tracked 2,400 middle-aged men over the course of 22 years, reported that a high-protein diet resulted in a 49% greater risk of heart failure. Many large, long-term population studies have also found that people who consume large amounts of protein, especially in the form of red and processed meat, are more likely to be obese or develop type 2 diabetes, cardiovascular disease and colon cancer.
So why have we been persuaded into eating more and more protein? Thomas Sanders, professor of nutrition and dietetics at King’s College London, says the idea of a protein gap in our diet was first broached by a professor at MIT, Nevin Scrimshaw, in the 1960s. He claimed that the protein that comes from plant sources such as vegetables was deficient in vital amino acids and that we therefore needed to eat more animal protein.
“A lot of this work was supported by the food animal industry in the US, which was all for getting people to eat more meat,” Sanders says.
Many people groggily pour a cup of coffee in the morning to wake themselves up. But exactly how much caffeine should you consume — and when should you take it — to achieve “peak” alertness?
A new algorithm aims to answer that question.
The algorithm, developed by U.S. Army researchers, takes into account people’s sleep schedules and identifies how much caffeine they should consume, and when, to achieve optimal alertness.
Managers don’t matter. Port cities and dictators produce soccer powers. The English national team actually isn’t a quadrennial disappointment. And if you want to win a World Cup, you better share a border with a country that’s done it before.
Those are just a few of the takeaways from the new 2018 World Cup edition of Soccernomics: Why England Loses; Why Germany, Spain, and France Win; and Why One Day Japan, Iraq, and the United States Will Become Kings of the World’s Most Popular Sport, written by the economist Stefan Szymanski and journalist Simon Kuper. For anyone who wants to understand how the sport has been shaped by larger global forces and which of those forces determine success on a soccer field, there’s nothing better. I caught up with Stefan over the phone and Simon via email to get their take on the state of world soccer before things kick off in Russia.
… Fastball velocity has increased at a steady rate, some of that due to the rise of relief innings around the league and some of it probably to dramatic improvements in training and development. That’s not really the point of this post, though. The point of this post is to discuss one particular cause of the increase in strikeouts that likely has little to do with launch angle or players trying to hit home runs, but rather the talent level of the pitchers and a change in philosophy.
… [Bruce] Fraser knew Sammy Gelfand, Golden State’s manager of analytics, hailed from a family of physicists. Gelfand’s father, Norman, is a former University of Chicago physics professor who also worked as a scientist for nearly 30 years for Fermilab in Batavia, Ill., specializing in high-energy particle physics. Gelfand’s older brother Joseph, meanwhile, is an associate professor of physics at New York University Abu Dhabi, with an emphasis on astrophysics.
“He wanted me to look at it from a more theoretical standpoint,” Sammy Gelfand said of Fraser. “I’ve been working with my dad on it.”
The depths of that analysis of the Splash Brothers’ shots will be more of a summer emphasis for Gelfand. He shoulders an array of more pressing duties for the Warriors, built around the pre- and postgame statistical reports that have been vital daily tools for Steve Kerr and the rest of the Golden State coaching staff since Kerr’s arrival in May 2014.
The selection of athletes has been a central topic in sports sciences for decades. Yet, little consideration has been given to the theoretical underpinnings and predictive validity of the procedures. In this paper, we evaluate current selection procedures in sports given what we know from the selection psychology literature. We contrast the popular clinical method (predictions based on overall impressions of experts) with the actuarial approach (predictions based on pre-defined decision rules), and we discuss why the latter approach often leads to superior performance predictions. Furthermore, we discuss the “signs” and the “samples” approaches. Taking the prevailing signs approach, athletes’ technical-, tactical-, physical-, and psychological skills are often assessed separately in controlled settings. However, for predicting later sport performance, taking samples of athletes’ behaviours in their sports environment may result in more valid assessments. We discuss the possible advantages and implications of making selection procedures in sports more actuarial and sample-based.