Craig Pickering

Sports Science Monthly – December 2020

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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.

As always, the full Sports Science Monthly is available exclusively to HMMR Plus Members. You can browse the past topics on our archive page. The first topic below is free to everyone, but sign up now to read about all the latest research. To get an idea of what Sports Science Monthly is all about, the April 2016 edition is available in its entirety for free.

This Month’s Topics

Athlete availability across a season

Quick Summary – In a group of high-level pre-elite track and field athletes, there was a disproportionately high number of injuries within the first month of training, suggesting a mis-match between training load and tolerance capacity.

In the first half of 2020, I authored a series of articles for HMMRMedia on the topic of performance health, in which I explained the concept of keeping the athlete healthy—and therefore “available” to train and compete—as a crucial pillar of performance. A kay part of optimizing athlete health is avoiding any injuries that might disrupt performance, particularly “time-loss” injuries, which result in time away from training and competition. Even injuries that don’t result in lost time can disrupt performance by preventing the athlete from training or competing at their full capacity. An important part of minimizing any risk of injury or illness is in ensuring that the load on the athlete—including, but not limited to, training volume, intensity, and life stress—does not exceed their capacity for tolerance. Non-sporting factors, such as exams and lack of sleep, can increase the life load on the athlete, reducing their load-tolerance capacity for training and competition, and hence increasing their risk of either injury or underperformance. Given their age, youth athletes are often at an increased risk of higher-than-normal life loads as they deal with exams, time pressures, and the social side of growing up. However, injury incidence profiles of youth and developing athletes are often poorly understood and quantified, which can harm our ability to deliver useful interventions and support strategies to reduce injury risk in this athlete cohort.

However, a recent study, published in Injury Epidemiology, goes some way to enhancing our understanding of this complex problem. Here, the authors contacted athletes registered to an athletics club in Gothenburg, Sweden. The athletes had all placed in either the top six of the Swedish National Championships, or the top three of the Swedish Youth Championships. In total, 76 athletes started the study; 17 dropped out, resulting in 59 completing the full length of the study. (October to August). This cohort was comprised of 23 endurance runners, 23 sprinters, and 13 jumpers. The athletes filled out training diaries daily, recording their injury/illness status.

Overall, the results showed that the endurance athletes had the highest average number of training sessions across the season. Most training-related injuries occurred in October, the first month back training following an extended break. Across all event groups, 22% suffered an injury in October; in December, the next highest month, this was 15%. Splitting out event groups, endurance athletes had their highest injury incidence rates in October (26%) and May/June (22%). Sprinters experienced the most injuries in December (18%) and April (19%). Jumpers had their highest injury prevalence in October (21%) and December (20%). In terms of overall availability, this was 78% for the whole cohort across the study period, meaning that athletes completed 78% of planned sessions. Sprinters had the lowest availability—71%–followed by jumpers (77%) and then endurance athletes (83%). Availability tended to be lower in females (77%) compared to males (80%). Endurance athletes had an injury incidence rate of 2.4 injuries per 1000 training hours; for jumpers, this was 1.6 / 1000h, and for sprinters 1.3 / 1000h. The rate in females (1.83 / 1000h) was slightly higher than in males (1.79 / 1000h).

As most overuse injuries occurred in the first month back of training, this suggests that training load is being increased too rapidly for athletes to be able to adequately tolerate the imposed demands. Secondly, overuse injury incidence was typically higher, across all event groups, during periods of traditional higher training loads (i.e. the winter training period), which supports that there is likely a mismatch between load and tolerance. This comes back to the Acute:Chronic Workload Ratio (ACWR) model (remembering that all models and wrong, but some are useful). This model suggests that injury risk is highest when the current training load is either too high or too low relative to previous training; in the case of this study, the injuries in October—when athletes would be returning from a post-season break—suggest that they are being exposed to too high a training load, too soon.

The overall availability of 78% falls below the threshold of 80% identified by previous research as the level required to be substantially more likely to achieve performance goals in athletics. As a result, we can clearly see that, by failing to support athlete availability through optimized loading, we are likely harming their ability to develop sufficiently to support their future performance, harming their long-term potential—a doubly bad outcome. In terms of general advice, it’s clearly important to have a more gentle increase in exercise load following a training break, and, as we get more research, we should (hopefully) be able to better understand the key drivers of injuries within each event group, and provide more bespoke interventions and support as and where needed.

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