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Improving decision making in sport

Sport is full of decisions: from the tactical decisions made by a soccer player, to training decisions made be a coach, or funding decisions made by a governing body. Making decisions in sport is hard, because sporting environments are typically highly complex. But new models on decision making help us better understand the decision making process and how to improve it.

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.

On the folly of rewarding A, while hoping for B

A new year means new goals and targets for many teams. While targets can help motivate and orient a team, coaches need to make sure their targets are pointing athletes in the right direction. A poorly chosen target might reward the wrong behavior, and history has given us countless examples of this happening.

Craig Pickering’s top reads of 2020

At the end of each year, I like to do a round-up of the books I read over the preceding 12 months, as it often serves to remind me of some key ideas and concepts. In 2019, I read 50 books, and in 2018 it was 59; this year it was 56. Here’s the list of what I enjoyed the most or found the most useful; hopefully it’ll provide some good recommendations for you to get stuck into in 2021.

Sports Science Monthly – December 2020

Every month we take a deep dive into the latest research in sports science. In the December edition we start off looking at athlete availability. A new year-long study helps identify key times of year that injury might occur. We also look at the role of perception in the long jump, altitude training, back pain, cortisol response, probiotics, and more.

How do you know if you’re a good coach?

Coaching is a crucial part of taking athletes on their journey towards reaching their potential. But while it’s easy to measure how “good” an athlete is—usually via their absolute or relative performance—understanding how “good” a coach is can be much more challenging.

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.

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.

Sports Science Monthly – November 2020

Every month we take a deep dive into the latest research in sports science. In the November edition we start off looking at elite coaches. Player development pathways are often discussed, but what are the pathways and processes of elite coaches? After that topic, we dive into some analysis of talent identification in jumping events, within-sport specialization, putting ecological dynamics in practice, the Cirque du Soleil, and more.

Learning how to win ugly

By his own admission, Brad Gilbert was not the most talented tennis player. And yet, across the span of his sporting career, he accumulated $5.5 million in prize money, and achieved a career high world ranking of #4, along with twenty singles titles and an Olympic bronze medal. By almost anyone’s account, that is a successful career—so how did Gilbert, who on paper, should have been a middle of the pack player, achieve so much success? As he points out in his book, Winning Ugly, it’s because tennis matches aren’t played on paper, they’re played on a court, between real people—and people can be gamed.