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Background Contemporary literature indicates that a higher body mass index (BMI) serves as a risk factor for metabolic disease and is also correlated with greater disease severity. Subsequently, it has been linked to increased COVID-19 severity. The purpose of the study was to investigate whether regular CrossFit™ participation was associated with lower BMI, decreased COVID-19 severity and susceptibility. Methods A cross-sectional study was conducted on 1806 CrossFit™ (CF) participants. Participants were asked about their age (yrs), sex (male vs. female), ethnic group, body height (cm) and weight (kg). Body mass index (BMI, kg/m2) was computed and consistent with WHO (2018) criteria. Participants self-reported their training history, health and lifestyle history, nutritional customs, present training status and suspected levels of exposure to COVID-19. Once submitted the collected data were coded, cleaned and analysed. Results The final model comprised of 1806 CF individuals from an online survey response rate of 2086. The participants age ranged from 18 to 65+ yrs. Self-reported mean body mass index (BMI: kg/m2) reported that < 1% were underweight, 41% were healthy, 46% overweight, 10% class I obese, 2% class II obese, and < 1% class III obese. A Kruskal–Wallis H test compared gender and self-reported probability of being infected with COVID-19 with significant differences between subgroups (x2 (4, N = 1739) = 10.86, p = 0.03). Analysis of BMI and perceived severity of COVID-19 revealed a difference however not, significant (x2 (4, N = 1739) = 9.46, p = 0.051). Results on BMI and perceived probability of COVID-19 infection revealed no significant difference (x2 (4, N = 1739) = 2.68, p = 0.61). A separate analysis on BMI and perceived COVID-19 susceptibility revealed no significant difference (x2 (4, N = 1740) = 6.02, p = 0.20). Conclusions The purpose of the study was to establish whether habitual CrossFit™ participation is associated with reduced BMI, and to further investigate whether habitual participation impacted perceptions of disease. Results of the study indicate that self-reported CrossFit™ participation during the first UK lockdown, measured in minutes of exercise was indicative of a lower BMI. This has been associated with greater host immunity to disease. A history of CrossFit™ participation was not shown to impact perceptions of disease. However, our sample population reported few changes to habitual exercise during lockdown which may be due to the ‘community’ and increased adherence associated with CrossFit™.

The purpose of this study was to investigate the effects of playing position, pitch location, team ability and opposition ability on technical performance variables (pass, cross, corner, free kick accuracy) of English Premier League Soccer players in difference score line states. A validated automatic tracking system (Venatrack) was used to code player actions in real time for passing accuracy, cross accuracy, corner accuracy and free kick accuracy. In total 376 of the 380 games played during the 2011–12 English premier League season were recorded, resulting in activity profiles of 570 players and over 35’000 rows of data. These data were analysed using multi-level modelling. Multi-level regression revealed a “u” shaped association between passing accuracy and goal difference (GD) with greater accuracy occurring at extremes of GD e.g., when the score was either positive or negative. The same pattern was seen for corner accuracy away from home e.g., corner accuracy was lowest when the score was close with the lowest accuracy at extremes of GD. Although free kicks were not associated with GD, team ability, playing position and pitch location were found to predict accuracy. No temporal variables were found to predict cross accuracy. A number of score line effects were present across the temporal factors which should be considered by coaches and managers when preparing and selecting teams in order to maximise performance. The current study highlighted the need for more sensitive score line definitions in which to consider score line effects.

The aim of this study were to investigate the effects of playing position, pitch location, team ability and opposition ability on the physical activity profiles of English premier league soccer players in difference score line states. A validated automatic tracking system (Venatrack Ltd.) was used to track players in real time (at 25 Hz) for total distance covered, high speed running distance and sprint distance. This is the first study to include every team from an entire season in the English premier league, resulting in 376 games, 570 players and 35 000 rows of data from the 2011-12 season being analyzed using multi-level modelling. Multi-level regression revealed an inverted "u" shaped association between total distance covered and goal difference (GD), with greater distances covered when GD was zero and reduced distances when GD was either positive or negative. A similar "u" shaped association was found with high speed distance covered at home. In addition distance covered (both at home and away) were predicted by playing position. All activity profiles (with the exception of sprint distance at home) were predicted by pitch location and time scored. Lastly, distance away from home and high speed running at home were predicted by opposition ability. Score line appears to effect player activity profiles across a number of situational factors and thus should be considered by managers when preparing and selecting teams to maximize performance. The current study also highlighted the need for more sensitive score line definitions in which to consider score line effects.