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Sports Science Monthly – January 2021

Every month we take a deep dive into the latest research in sports science. To kick of 2021 we’ve put together one of our biggest editions yet, reviewing 12 new articles on a range of topics from a critique of data-driven coaching, repeatability of training improvements, caffeine periodization, crowd wisdom, and what coaches can learn from hunter gatherers.

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November 2020 in review: technology and sport

The site theme in November was technology and sport. Throughout the month we put together 5 new articles and 3 new podcasts from 7 contributors about how to effectively integrate technology into training. You’ll find all the links below, as well as highlights from our archive on the topic.
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Navigating the technology paradox in sport

Technology is a good thing, right? When we evaluate technology we tend to focus on the benefits: what it can add. But the paradox of technology is that it often has hidden costs we do not see up front. Determining whether technology is good or not can be harder than it looks. Read more

Penetrating the data smog through better visualization

As anyone who witnessed the UK government’s recent presentation on COVID-19 data will know, data is only useful if it can be read and understood clearly. For those who missed the broadcast, the presentation consisted of many slides of data with the BBC banner on the screen blocking out the titles! The audience of millions was left looking at lines and bar charts that had no context or explanation. Unfortunately such examples can easily be found in the world of sport too. Read more

More data isn’t always the answer

This month’s theme on HMMRMedia is technology and sport. Over the past few years technology has often become synonymous with data. New technologies are allowing more data to be collected in sport. This information can then be utilized by coaches and support staff to understand where the athlete is at, and to make decisions on a future course of action. Read more

Digital twins and the future of data modeling in sport

On April 11, 1970, the crew of Apollo 13 blasted off from Kennedy Space Centre at the start of their mission to the moon. Following the recent successes of Apollo missions 11 and 12, James Lovell and Fred Haise were due to become the fifth and sixth humans to walk on the moon. However, just under 56 hours after taking off, and 330,000 km from Earth, disaster struck. Read more

GAINcast Episode 183: From data to speed (with Matt Rhea)

American football is a bastion of tradition. In some areas, such as strength and conditioning, that can hold the sport back. Many coaches, however, are working to change the traditions and they start out by asking simple questions all over again like how do we make our players better? On this week’s GAINcast, Matt Rhea explains how the forward-thinking setup he installed at Indiana University helped turn their program around using a practical data-driven approach. Read more

Burning questions for the future of training

You might think that the best way to predict the future is to ask the experts what lies ahead. In general, that is actually a poor idea. As Philip Tetlock has researched in depth, experts have a surprisingly poor track record in predicting the future. But there is a subgroup of experts that predict very well. These are not people with the most years of experience of access to the best algorithms. They are the experts who can think broadly, gather evidence from a variety of sources, work in teams, and, importantly, are willing to admit error and change course. Tetlock calls this group foxes. Read more

Key questions in data science for sports

Over the last decade or so, there has been a Big Data revolution. This is true of our general lives; a good example is how Cambridge Analytica collected, both legally and potentially illegally, data of Facebook users for the targeting of campaign advertisements, but also within sport, where, in part thanks to the increase in technology, there is a vast amount of data available to sporting teams. Read more

From big data to smart data

There is an arms race in today’s sporting environment. Teams, athletes, coaches and support staff aren’t just fighting for the best facilities and talent, they’re also seeing who can collect the most numbers. This is the era of big data, and the past decade has seen an unrivaled amount of information available in sports from a wide variety of methods, including the use of GPS systems, electronic timing gates, force platforms, blood testing, and general wellness questionnaires. The richness and vastness of information available, however, can also be seen as a curse; both teams and individuals can feel like they have to collect more and more data, in the hope that they can gain an edge over their competitors, and better enhance athletic performance. As with many things, we need to shift the focus on data from quantity to quality. Read more