Applied Sports Science newsletter – February 16, 2019

… Cousins wasn’t ready to sit. Didn‘t want to sit. He’s tired of sitting, even though he’s still working on his timing and conditioning after a one-year layoff to recover from surgery to repair his ruptured left Achilles’ tendon.

He wanted to play, so he let Kerr know.

“I just wanted to try to finish the game out strong,” Cousins told Warriors sideline reporter Kerith Burke. “We’re trying to stick to this minutes restriction. I’m like a defiant child right now when it comes to it.”

Fifty-one players from an English Premier League soccer academy were split into under-23 (n = 21), under-18 (n = 14), and under-16 (n = 16) groups and performed bilateral and unilateral countermovement jumps, 5-, 10-, and 20-m sprints, and a 505 change of direction speed tests. All tests showed low variability (coefficient of variation ≤ 2.5%) and good to excellent reliability (intraclass correlation coefficient = 0.80-0.99). A 1-way analysis of variance showed that the under-23 group was significantly faster than the under-16 group during the 20-m sprint (2.90 vs. 2.98 s; p = 0.02; effect size = 0.94). No other significant differences were present between groups. Interlimb asymmetry was quantified from the single-leg countermovement jump, and no significant differences in the magnitude of asymmetry were present between groups. However, multiple significant correlations were present in each age group between asymmetry and physical performance tests, all of which were indicative of reduced athletic performance. Results from this study show that although interlimb asymmetry scores are comparable across age groups in elite academy soccer players, differences as low as 5% are associated with reduced physical performance during jumping, sprinting, and change of direction speed tasks. This study suggests the importance of monitoring jump height asymmetries in elite academy soccer players.

… In a new study by [Lawrence] Schwartz, he argues that nuclei must maintain a certain ratio with the volume of the cell: Hypertrophy requires more nuclei while atrophy requires less.

According to the research reviewed by Schwartz, the evidence suggests that these additional nuclei actually persist through atrophy, allowing individuals to “bank” these additional nuclei in their muscle cells to be drawn on later in life.

“If this is generalizable and it looks like it is, then once you acquire a nucleus you get to keep it,” Schwartz told Healthline. “Well it’s a whole lot easier to acquire those nuclei when you’re young and fit.”

If nothing else, the Seattle Mariners’ early arrival for spring training will give them a little more meet-and-greet time.

The Mariners have 20 new players, including seven projected new starters, on their training camp roster this spring after an offseason overhaul following an 89-victory 2018 that still left them eight games out of the playoffs.

“I’ve been studying mugs of these guys to get a feeling. It’s going to be a little bit different camp with all the new people,” manager Scott Servais said Monday. “A lot of educating to do. Name tags would be good. Mandatory wear your jersey out there with the name on the back.”

… The CSA says it surveyed 3,000 Canadians as well as its clubs and provincial partners in coming up with the plan, as well as surveying similar plans in other countries.

For CSA president Steven Reed, Monday was another chance to tout the million-plus Canadians who play soccer. He said in touring the globe to sell the so-called united World Cup bid, people were “flabbergasted” at the numbers.

“They all think that hockey is our main sport. Well it’s not. I mean you see it on TV a lot, but soccer is really the primary sport in our country and we want to continue to make it that way and grow it,” Reed said.

… “At The Citadel, things change every day,” said Skole, who played on that 1990 team. “But sometimes, it seems like they never change. We decided it was time to spend some money and do some things to keep up and catch back up.”

That’s why Skole, entering his second season atop The Citadel program, spent some $70,000 on upgrades during the offseason — not on office furniture, but on analytics systems and fixes to the practice field at College Park that can make an immediate impact on the Bulldogs’ competitiveness.

The Citadel spent about $20,000 each on the advanced metrics systems Trackman and Rapsodo, and about $45,000 on upgrades at College Park, where the Bulldogs practice when Riley Park is not available, Skole said.

… In my media diet roundup post for 2018, I said that getting adequate sleep has “transformed my life” and that sleep is “even lower-hanging self-help fruit than yoga or meditation”. I have not been sleeping well for the past several weeks and it’s taking a toll: I’ve been sluggish, eating poorly & erratically, feeling down, and not anywhere near my peak mental performance. This morning I woke up at 4am, couldn’t really get back to sleep, and I feel like I’m running at 60% capacity, 65% tops.

Physical literacy (PL) provides a powerful lens for examining movement in relation to physical activity (PA) and motor skill outcomes, environmental context, and broader social and affective learning processes. To date, limited consideration has been given to the role PL plays in promoting positive health behaviours. There is no clear conceptual framework based on existing empirical evidence that links PL to health, nor has an evidence-informed case been made for such a position. The purpose of this paper is to (1) present a conceptual model positioning PL as a health determinant, and (2) present evidence in support of PL as a health determinant, drawing on research largely from outside physical education. Viewing PL from the perspective of a multidimensional, experiential convergence process enables it to be differentiated from other models. However, parallels between our model and existing models that focus on movement competence are also drawn. Arguing from a pragmatic perspective on PL, we present evidence for positioning PL as a determinant of health from two literature sources: research on motor coordination disorders in children, and associations between motor competence, PA and health in typically developing children. Statistical modelling approaches consistent with the concept of PL are discussed. Results from these approaches—confirmatory factor analysis and cluster analysis—support the idea that measures related to motor competence, motivation and positive affect work in an integrative manner to produce differences in PA and subsequent health outcomes in children. There is increasing interest in PL, particularly in the field of public health. Presenting a model that explicitly links PL to health can lead to the generation of new research questions and the possibility of broadening impact beyond the context of physical education alone. To date, there has been little conceptual attention to what positioning PL as a determinant of health means. By providing an evidence-based model of PL as a determinant of health, we hope to further the discussion and stimulate increased empirical research in the field.

… The Sports Office has been one of the key pieces we’ve added. It means all our data – GPS data, forceplates, strength measurements and so on – is together in one place and we don’t have to sift through 1,000 different spreadsheets to get it.

For every piece of technology we have that records something, we enter the data either directly or indirectly into The Sports Office. For example the guys’ weights will load up automatically from the scale. It makes all our processes smoother and more systematic. Everything we need to is at our fingertips.

We’re also able to come in and check through the roster in the morning. If anyone needs to dig deeper, the info is there for everyone – they don’t have to ask the strength coach for his testing numbers or the medical guys for someone’s rehab programme.

That’s the key to this cohesive system we want. The physio needs to see what the players did in the weight room, our nutritionist needs to see where they are in their rehab and whether they need to add protein or carbs. If I’m on the phone with you, my guys need to be able to log in and see information and act on it.

… One of the desire paths of the smartphone camera is that since we have it with us all the time and we can take unlimited pictures for free, and have them instantly, we don’t just take more pictures of our children and dogs but also pictures of things that we’d never have taken pictures of before. We take pictures of posters and books and things we might want to buy – we take pictures of recipes, catalogues, conference schedules, train timetables (Americans, ask a foreigner) and fliers. The smartphone image sensor has become a notebook. (Something similar has happened with smartphone screenshots, another desire path that no-one thought would become a normal consumer behavior.)

Machine learning means that the computer will be able to unlock a lot of this. If there’s a date in this picture, what might that mean? Does this look like a recipe? Is there a book in this photo and can we match it to an Amazon listing? Can we match the handbag to Net a Porter? And so you can imagine a suggestion from your phone: “do you want to add the date in this photo to your diary?” in much the same way that today email programs extract flights or meetings or contact details from emails.

This is an interesting product design challenge. Some of this can be passive, as with automatically detecting flights in email – you wait until you know you have something. Machine learning means we now have this with face recognition and object classification: every image on your phone is indexed by default, and you can ask for ‘all pictures of my son at the beach’ or ‘every picture of a dog’. But you can do many more analyses than this, and we take lots of photos, and there will be something you could analyse in all of them. You can perhaps index or translate all of the text in all the photos you take (presuming that isn’t resource-prohibitive), but should you do a product search on every object in every picture on the phone? At some point, you probably need some sort of ‘tell me about this’ mode, where you explicitly ask the computer to do ‘magic’.

… geometric pipelines are leaky patchworks requiring esoteric training and involving many different people. Instead, we adapt fundamental mathematics to work directly on messy geometric data. As an archetypical example, I will discuss how to generalize the classic formula for determining the inside from the outside of a curve to messy representations of a 3D surface. This work helps keep the geometry processing pipeline flowing, as validated on our large-scale geometry benchmarks. Our long term vision is to replace the current leaky geometry processing pipeline with a robust workflow where processing operates directly on real geometric data found “in the wild”. To do this, we need to rethink how algorithms should gracefully degrade when confronted with imprecision and uncertainty. Our most recent work on differentiable rendering and geometry-based adversarial attacks on image classification demonstrates the potential power of this philosophy.

ncaahoopR is an R package for working with NCAA Basketball Play-by-Play Data. It scrapes play by play data and returns it to the user in a tidy format and allows the user to explore the data with assist networks and in game win-probability charts.

… Fit Intelligence has been intended to be deployed to a range of different sport and lifestyle products. Made with an industrial grade fibre support system, strategically placed for optimal hold and a forefoot lockdown band, this is a shoe that is capable of responding to athletes and their environment. On its ability to adapt to their consumers’ needs Charles Johnson, PUMA’s Global Director of Innovation said, “We have created a product that speaks to the future of sport which is life in motion. It’s fast and changing all the time.” Adding, “Fi is a platform that can be used for many different things. We want to learn what those things are from people who have experienced it.”

The wena wrist pro and wena wrist active straps signal Sony’s changing wearable tech ambitions. But why are they so expensive?

… “We are essentially putting a mobile research lab on the feet of athletes all over the world, and creating a whole new frontier to accelerate both product development and sports science,” Michael Donaghu, Nike’s vice president of innovation, said at an event last month.

It makes sense that people are willing to share information with fitness apps, which they downloaded to help them live healthier lives. But the apps can’t help unless you hand over information like your diet and exercise routine.

“Even with all of the privacy breach issues, consumers are still willing to give information,” Cleary said. “You just gotta show them what they get in return.”

A system which uses a combination of artificial intelligence (AI) and high resolution fixed cameras could change the way some sports like basketball are covered.

Developed by Playsight the system can track players, the ball and events like passes and three-point field goals.

Teens who suffer a sports-related concussion are likely to improve more quickly if they start aerobic exercise within a few days under the guidance of a health care specialist, according to what has been hailed as a landmark study led by two University at Buffalo researchers.

The findings contradict a long-held belief in medical circles that those concussed are best served by at least several weeks of rest before resuming regular activities.

“This should start to change the approach to concussion care from being a very passive approach – essentially don’t do anything until your symptoms go away – to one that’s more active in promoting some moderate level of physical activity,” said Dr. John Leddy, director of the UB Concussion Management Clinic and lead author of the study.

As the single most popular and top-grossing sport in the United States, football is practically a national religion. Over 100 million Americans tuned into the Super Bowl in 2018, a number likely to be repeated this Sunday. Celebrated for its athleticism, spirit, and camaraderie, more recently, the sport has also become infamous for its link to permanent brain injuries.

In a recent seminar for the Department of Epidemiology Injury Unit, Kathleen E. Bachynski, PhD ’16, said public awareness on the health risks of football is a good thing, but too often, discussion on this topic has centered on player behavior rather than inherent risks of the game. In recent years, the NFL has set the rules for the way we understand the issue, purchasing public trust by teaming up with some of the country’s most trusted health authorities.

… While players on the 40-man roster are subject to MLB’s Joint Drug Prevention and Treatment Program, minor league players must adhere to the Minor League Drug Prevention and Treatment Program. The most glaring disparity between these two lists is the prohibition of marijuana, which is listed as a “drug of abuse” in the MiLB program, and conspicuously absent from the major league program. It has been noted that this discrepancy may simply serve as a proxy for assessing character or work ethic, which can lable players who use marijuana with stubborn stereotypes, though there is some anecdotal evidence that suggests that front offices vary in their willingness to work with players when it comes to marijuana use.

The reason for the disparity between the major league and minor league drug programs comes down to the Collective Bargaining Agreement and the MLBPA: “The player’s union has consistently opposed strict punishment for marijuana offenses going back to MLB’s first Joint Drug Agreement in 2002. Minor league players are not protected by the union, so MLB can impose whatever punishment they want.”

In January, the influential medical journal The Lancet released a report calling for a dramatic and worldwide overhaul of our collective eating habits. The report is 46 pages long (and lists 37 authors), but its core idea is simple: We should eat less red meat (50 percent less, worldwide) and more nuts, vegetables, fruits, and legumes (100 percent more, worldwide). The authors are calling their proposed plan “The Planetary Health Diet,” and they argue that adopting it would improve both human health and the health of the environment. By reducing red meat production and consumption, they argue, we would reduce premature deaths (the report cites studies that link saturated fat intake with disease) and protect the environment by reducing livestock-related greenhouse-gas emissions.

The report’s lead author is Harvard professor Walter Willett. Willett is also the author of the 2001 book Eat, Drink, and Be Healthy: The Harvard Medical School Guide to Healthy Eating. Our conversation has been condensed for clarity.

In the information age, the ability to read and construct data visualizations becomes as important as the ability to read and write text. However, while standard definitions and theoretical frameworks to teach and assess textual, mathematical, and visual literacy exist, current data visualization literacy (DVL) definitions and frameworks are not comprehensive enough to guide the design of DVL teaching and assessment. This paper introduces a data visualization literacy framework (DVL-FW) that was specifically developed to define, teach, and assess DVL. The holistic DVL-FW promotes both the reading and construction of data visualizations, a pairing analogous to that of both reading and writing in textual literacy and understanding and applying in mathematical literacy. Specifically, the DVL-FW defines a hierarchical typology of core concepts and details the process steps that are required to extract insights from data. Advancing the state of the art, the DVL-FW interlinks theoretical and procedural knowledge and showcases how both can be combined to design curricula and assessment measures for DVL. Earlier versions of the DVL-FW have been used to teach DVL to more than 8,500 residential and online students, and results from this effort have helped revise and validate the DVL-FW presented here.

More than seven months after Jordan McNair’s death, Maryland state lawmakers have proposed a bill that would upend the college athletics model across the state and give athletes the right to unionize and collectively bargain over issues related to health and safety, as well as compensation.

Del. Brooke E. Lierman ­(D-Baltimore) proposed the measure this week and said recent events on college campuses have highlighted a growing need for an independent advocate who can work on behalf of athletes. Lierman cited McNair, the 19-year-old Maryland football player who collapsed after suffering exertional heatstroke at a conditioning workout in May, and the hundreds of young Michigan State athletes who suffered sexual abuse at the hands of Larry Nassar.

Human populations exhibit complex behaviors—characterized by long-range correlations and surges in activity—across a range of social, political, and technological contexts. Yet it remains unclear where these collective behaviors come from or if there even exists a set of unifying principles. Indeed, existing explanations typically rely on context-specific mechanisms, such as traffic jams driven by work schedules or spikes in online traffic induced by significant events. However, analogies with statistical mechanics suggest a more general mechanism: that collective patterns can emerge organically from fine-scale interactions within a population. Here, across four different modes of human activity, we show that the simplest correlations in a population—those between pairs of individuals—can yield accurate quantitative predictions for the large-scale behavior of the entire population. To quantify the minimal consequences of pairwise correlations, we employ the principle of maximum entropy, making our description equivalent to an Ising model whose interactions and external fields are notably calculated from past observations of population activity. In addition to providing accurate quantitative predictions, we show that the topology of learned Ising interactions resembles the network of interhuman communication within a population. Together, these results demonstrate that fine-scale correlations can be used to predict large-scale social behaviors, a perspective that has critical implications for modeling and resource allocation in human populations. [full text]

Football clubs over the last twenty years have operated under a simple business model: win matches, and the fans, sponsors and prize money will follow. And yet while these income streams are bigger than ever, clubs all over the world are now increasingly dependent on a fourth source of money: the transfer market.

According to UEFA’s Club Benchmarking reports, in 2014 transfer proceeds were worth 26 per cent of total revenues in Europe’s top 15 leagues. The latest released figures from 2017 tells us that figure is now 38 per cent: clubs have increased their dependency on transfer income by nearly 50 per cent in just three years.

Despite a whirlwind of rumors before the trade deadline passed, Anthony Davis will remain in New Orleans until at least this July. But with the Pelicans likely trying to maximize their draft pick, could they run afoul of the league’s anti-tanking or anti-resting policies?

… Psychologist Tina Kiesler and her research team1 found that there was an inverted-U curve relationship between performance on a 25-question basketball knowledge exam and performance on picking game winners in the NCAA tournament. This inverted-U curve, depicted conceptually in Figure 1, appears to mirror the frown of a basketball expert peering at it. The most knowledgeable subjects were actually the worst pickers of all. This team of researchers found the same general pattern among subjects predicting outcomes in other sports, and they cited studies showing that experts perform no better than novices in some other domains.

… Bringing new techniques and ideas to old problems must be a very good thing. But this leads obviously to two questions: (a) what went before? and (b) how is this innovative research an improvement on what went before?

Statistical modeling in soccer, like other sports, has some history. Most of that research was focused on analyzing results. Statistical models were developed and tested to predict game outcomes, and these models were then benchmarked against bookmaker odds. These models relied on regression methods familiar in econometrics to fit a model the data – what in data science is now called “training” the data. The anthropomorphism here can be a little confusing if you’re not familiar with what is being done. The old methods were optimization methods: getting the computer to solve a maximization problem, which as byproduct reveals the sensitivity of the variable to each other.

“Machine Learning” does the same thing- the computer solves an optimization problem, only now based on millions of observations rather than a few hundred. Moreover, machine learning doesn’t tie you down to one statistical model, it optimizes among models. While these are important advances, it’s also important not to lose sight of the fact that the same fundamental principles apply. I don’t know if humans can be thought of as massive optimization solvers (though I doubt it), but the word “learning” in machine learning should not lead us to think that machines are doing anything more than optimization routines.

In the largest analysis of the issue thus far, investigators have found that the smaller the research team working on a problem, the more likely it was to generate innovative solutions. Large consortiums are still important drivers of progress, but they are best suited to confirming or consolidating novel findings, rather than generating them.

The new research, published on Wednesday in the journal Nature, is the latest contribution from an emerging branch of work known as the science of science — the study of how, when and through whom knowledge advances. The results could have wide-ranging implications for individual investigators, the academic centers that employ them and the government agencies that provide so much of the financing.

“There has been a huge amount of debate in the scientific community about the effects of moving to larger research teams,” said Albert Lazlo Barabasi, a professor of network science at Northeastern University, who was not involved in the research. “This new paper gives us a way to resolve the debate. It’s an enormous contribution.”