Applied Sports Science newsletter – March 5, 2021

… “When I went [to Driveline], I had plateaued with velocity for a while at 89–92 (mph), but I guess the movement has changed,” Morris told The Campus. “You never want to be average with anything. With technologies that exist now like Rapsodo and Trackman, you can measure the spin rate and how the ball is moving. So, despite plateauing in velocity, I made my movement stand out as much as I could.”

His tangible improvement, driven by minor league experience and technical work with Driveline, positioned Morris as a candidate for Major League clubs. And MLB organizations bit, with the Texas Rangers and Milwaukee Brewers both giving Morris a shot. But his potential truly glowed when he trialed with the New York Mets, who eventually offered Morris a minor league deal.

… Fitzgerald, 37, has played the past five seasons on one-year contracts each worth $11 million, which has led the 11-time Pro Bowler to have to make a decision on his future each of those years. The latest he had decided to play since 2016 was Feb. 15 in 2018.

But [Steve] Keim said he doesn’t need Fitzgerald to make a decision by the start of the league year on March 17, despite the lowered leaguewide salary cap.

Fitzgerald, who’ll turn 38 in August, has said in the past that when he decides to retire, he’ll just walk away quietly, not wanting the pomp and circumstance or farewell tour that sometimes accompanies players’ retirements.

Krystle Mann, a stay-at-home mother to three sons, makes and sells cornbread and jam to pay for new baseball gear and help cover club fees – approximately $1,500 per year.

Her older son, Sam, 12, plays for the AZ Diamond Dawgs in Queen Creek, while her middle son, Tommy, 11, plays for both the Paladin Knights and AZ Storm in San Tan Valley. Both boys have played baseball for about seven years, making the transition from Little League to club baseball recently.

Club sports are run by private associations that, unlike school-sponsored sports programs, charge high fees to participants who are hoping to enhance their individual or team skills.

“I think this has been the best thing for the boys mentally, physically and emotionally,” Mann said.

What did we find? With proper warm up, on-ramping, and monitoring, there is no compelling reason not to incorporate them.

While studying for his master’s degree at the University of Oxford, Adam Mastroianni confronted a fear common to many party goers: Would he get stuck in a conversation with no polite way out?

Then, Mastroianni had another thought: Perhaps his future conversation partner had the same concern. “What if we’re all trapped in conversations because we mistakenly think the other person wants to continue?” he says.

Now, 5 years and one scientific publication later, Mastroianni has discovered both fears are well-founded: Most conversations don’t end when people want them to.

For decades one of my favourite tasks in medicine has been reading 12-lead electrocardiograms (ECGs). I’ve always thought the wealth of information provided was impressive—eg, conduction and heart rhythm abnormalities, lack of blood supply or damage to the heart, chamber enlargement or hypertrophy, and inflammation of the pericardium. In the 1980s, when I did emergency coronary angiograms for patients with acute myocardial infarction, I marvelled at how the ECG accurately predicted the infarct-related artery and whether the occlusion was proximal or distal. But today I realise that whatever I could discern from a close review of an ECG was only rudimentary—it was just human.

Background

Measuring gait function has become an essential tool in the assessment of mobility in aging populations for both, clinicians and researchers. A variety of systems exist that assess gait parameters such as gait cycle time, gait speed or duration of relative gait phases. Due to different measurement principles such as inertial or pressure sensors, accurate detection of spatiotemporal events may vary between systems.
Research question

To compare the absolute agreement and consistency in spatiotemporal gait parameters among five different clinical gait analysis systems using different sensor technologies.
Methods

We compared two devices using inertial sensors (GaitUp & Mobility Lab), two devices using pressure sensor systems (GAITRite & Zebris) as well as one optical system (OptoGait). Twelve older adults walked at self-selected speed through a walkway integrating all of the above systems. Basic spatiotemporal parameters (gait cycle time, cadence, gait speed and stride length) as well as measures of relative phase (stance phase, swing phase, double stance phase, single limb support) were extracted from all systems. We used Intraclass Correlation Coefficients as measures of agreement and consistency.
Results

High agreement and consistency between all systems was found for basic spatiotemporal parameters, whereas parameters of relative phase showed poorer agreement and consistency. Overground measurement (GAITRite & OptoGait) showed generally higher agreement with each other as compared to inertial sensor-based systems.
Significance

Our results indicate that accurate detection of both, the heel-strike and toe-off event are crucial for reliable results. Systematic errors in the detection of one or both events may only have a small impact on basic spatiotemporal outcomes as errors remain consistent from step to step. Relative phase parameters on the other hand may be affected to a much larger extent as these differences lead to a systematic increase or reduction of relative phase durations.

This study investigated if training in a virtual reality (VR) environment that provides visual and audio biofeedback on foot placement can induce changes to spatial and temporal parameters of gait during overground walking. Eighteen healthy young adults walked for 23 min back and forth on an instrumented walkway in three different conditions: (i) real environment (RE), (ii) virtual environment (VE) with no biofeedback, and (iii) VE with biofeedback. Visual and audio biofeedback while stepping on virtual footprint targets appearing along a straight path encouraged participants to walk with an asymmetrical step length (SL). A repeated-measures, one-way ANOVA, followed by a pairwise comparison post-hoc analysis with Bonferroni’s correction, was performed to compare the step length difference (SLD), stance phase percentage difference (SPPD), and double-support percentage difference (DSPD) between early and late phases of all walking conditions. The results demonstrate the efficacy of the VE biofeedback system for training asymmetrical gait patterns. Participants temporarily adapted an asymmetrical gait pattern immediately post-training in the VE. Induced asymmetries persisted significantly while later walking in the RE. Asymmetry was significant in the spatial parameters of gait (SLD) but not in the temporal parameters (SPPD and DSPD). This paper demonstrates a method to induce unilateral changes in spatial parameters of gait using a novel VR tool. This study provides a proof-of-concept validation that VR biofeedback training can be conducted directly overground and could potentially provide a new method for treatment of hemiplegic gait or asymmetrical walking.

The NFL draft is quickly approaching and thousands of former college players are training hard to prove they belong in the big leagues, working with trainers and experts to hone their skills and reach their peak performance during the NFL’s College Pro Days that will take place between March 5 and April 9.

To help players figure out what they need to work on, human performance company EXOS and Intel are partnering together on an AI program called 3D Athlete Tracking that will assist in identifying areas of improvement.

“There’s a massive gap in the sports and movement field, between what people feel when they move and what they actually know that they’re doing,” said Ashton Eaton, a two-time Olympic gold medalist in the decathlon and Intel’s product development engineer in the Olympic Technology Group

The lightweight Pixellot Air camera can monitor the global application of the Barça Academy methodology and record youth football matches away from the club facilities

A bowl-shaped aromatic molecule could be a template for new flexible electronic materials (Nat. Commun. 2021, DOI: 10.1038/s41467-021-21019-4). Shunsuke Furukawa and Masaichi Saito of Saitama University and Tomoyuki Akutagawa of Tohoku University focused on ferroelectric materials, whose dipole moments can be reversed using an electric field. Ferroelectrics are used in computer memory and in piezoelectric devices, which convert mechanical pressure into electric current. The team sought an organic alternative to conventional ferroelectrics, which contain rare or toxic metals. Scientists have demonstrated ferroelectric bowl-shaped molecules and supramolecular assemblies. Akutagawa, a physicist, was looking for new candidates when he met Furukawa and Saito through a π-aromaticity research project. Akutagawa recognized that low-molecular-weight, bowl-shaped aromatic molecules had ferroelectric possibility, and Furukawa and Saito proposed using variants that they had developed. The group found a sulfur-substituted molecule, CnSS (shown). Stacks of these molecules act as ferroelectrics as the bowl shapes flip inside and out. The researchers hope to find other molecules that will be ferroelectric without needing to be stacked.

… Mohammed Bamba of the Orlando Magic and Jayson Tatum of the Boston Celtics are two NBA players who have openly discussed the long road back from Covid. Despite each recovering and showing no symptoms, they have found it hard to get their wind under them as they work themselves back into top form.

Bamba, known for his elite shot-blocking ability, was drafted No. 6 overall in 2018 to the Orlando Magic. Despite the talent he brought to Orlando, he played limited minutes and had marginal production due to the Magic’s crowded front court. Bamba was diagnosed with the virus on June 11th, 2020, but tested negative before reporting to the bubble, where he played a total of 10 minutes. Nearly six months later, he still had not fully recovered.

The NFL was among six pro sports leagues that participated, along with the leagues’ players’ unions, in a study that revealed today that five professional athletes developed heart problems after testing positive for COVID-19.

The study, published today, identified 789 professional athletes in the NFL, NBA, WNBA, MLB, NHL and MLS who have tested positive for COVID-19. Three of them developed myocarditis, or inflammation of the heart, and two developed pericarditis, or inflammation of the tissue surrounding the heart.

The five athletes were not named, but one of them was Bills tight end Tommy Sweeney, who tested positive for COVID-19 in October and was ruled out for the season with myocarditis in November. Another was Boston Red Sox pitcher Eduardo Rodriguez, who missed the entire 2020 MLB season after being diagnosed with myocarditis but is participating in spring training this year.

… Machine learning uses powerful algorithms to discover insights based on real-world data that can then be used to make predictions about future outcomes. As new data comes available, machine learning programs can automatically adapt and produce updated predictions. As with any tool, machine learning is not a silver bullet. However, there are many situations in which the technology can outperform linear and statistical algorithms.

Here are five of the most common use cases where machine learning can make a big difference:

1. When engineers can’t code rules for certain problems

In the hypercompetitive world of sports analytics, teams face the ongoing risk of rivals recruiting top staff and extracting valuable trade secrets. A new book sheds light on this phenomenon and how teams try to mitigate the risk—and how these efforts may in the long run hurt the broader industry.

Northwestern University economists recently reported that the factor that predicts a country’s COVID-19 death rate is that nation’s level of pre-COVID income inequality. With that insight in hand the same researchers modeled further to find out why and found that “the poor have shouldered a disproportionate number of COVID deaths mainly because of disparities in access to quality healthcare and in health preconditions that long predate the pandemic.”

Disparities in access to quality X and in Y negative precondition that predates the pandemic for any quality of life measure (X) and preventable physical or mental health condition (Y). It’s going to be true across the board during the pandemic. Income inequality is a force multiplier for COVID’s disastrous outcomes. Sports is no exception.

Anxiety and depression among young Americans runs higher than before the pandemic, and the data show that it’s worse for young athletes. But if you attend one of the elite private schools in Washington DC, and not one of the public schools on sports lockdown, the workarounds to continue to play are inconvenient but not a real hindrance to skirting the District’s ban on high school sports.

People with lower incomes are more likely to believe health misinformation.
The Great Sport Myth, the idea that sports’ meritocracy is a ticket to a better situation, coined by sociologist Jay Coakley, is also misinformation.

The high income side of the equation is uglier. Donors at the University of Texas at Austin, hundreds of them according the the Texas Tribune, call students who protest the school’s derogatory fight song disrespectful. Institutional barriers are not going away.

The double whammy of misinformation and structural inequity are shutting down the youth sports development pipeline in low income areas. The future of sports will, no doubt, suffer.

The best view of Boston is from the top of the John Hancock Tower, because you don’t see the John Hancock Tower. If you look at sports from a position of privilege and like what you see, it’s probably because you cannot see the disastrous effects of income inequality.

Thanks for reading.
-Brad