Key result
EWMA acute:chronic workload ratio links to ~14-fold higher noncontact injury risk despite poor model fit.
Why the study?
The study was designed to prospectively investigate the relationship between noncontact injuries and workload in collegiate football during summer conditioning and preseason training.
Does the EWMA A:C ratio predict noncontact injuries in collegiate football players?
Cohort (n=34)
No
Does the EWMA A:C ratio predict noncontact injuries in collegiate football players?
Odds Ratio: 14.16 (95% CI 1.9–105.49)
While external workload ratios are significantly associated with noncontact injuries in collegiate football players, current continuous models lack sufficient goodness of fit for practical adoption.
EWMA A:C ratio associated with noncontact injury but models lack fit for adoption; hypothesis-generating for workload monitoring in Division I football.
Burghardt, WP, Pfeiffer, KA, and Kuenze, C. Assessing the relationship between external workloads and noncontact injuries during summer conditioning and preseason practice in National Collegiate Athletic Association Division 1 football players. J Strength Cond Res 37(4): 816-822, 2023-The purpose of this study was to prospectively investigate the relationship between noncontact injuries and workload in collegiate football during summer conditioning and preseason training. Workload and noncontact injury data were collected over the summer conditioning and preseason practice periods for a Division 1 National Collegiate Athletic Association football team ( n = 34). Seven- and 21-day exponentially weighted moving averages (EWMA) were calculated daily for each athlete. The acute:chronic ratio (A:C ratio) of these 2 measures was also calculated daily. Injury rates for noncontact injuries were calculated for both periods. Continuous variable modeling (panel logistic regression and restricted cubic spline) was used to assess the relationship of EWMA A:C ratio and noncontact injury using a 3-day lag period. Athletic exposures (AEs) were defined as individual sport training, practice, or competition sessions. Nine injuries were observed (6.97/1,000 AEs), with 4 injuries resulting in lost time (3.09/1,000 AEs). The mean EWMA A:C ratio was 0.92 ± 0.41 (95% confidence interval: 0.03-2.09). Both the panel logistic regression and the restricted cubic spline models showed a significant relationship between EWMA A:C ratio and noncontact injuries. However, the odds ratio (14.16) in the logistic regression had a very large standard error (14.51) and a wide 95% confidence interval (1.90-105.49). The restricted cubic spline model had a pseudo R2 of 0.136. Injury occurrence at given EWMA ratio values was lower than reported in previous research. Although both continuous models demonstrated a significant relationship between the EWMA A:C ratio and subsequent noncontact injuries over the next 3 days, neither model had sufficient goodness of fit to warrant adoption at this time.
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Burghardt et al. (2022) conducted a cohort in Noncontact injuries (n=34). Exponentially weighted moving averages (EWMA) acute:chronic workload ratio was evaluated on Noncontact injuries (OR 14.16, 95% CI 1.90-105.49). The EWMA acute:chronic workload ratio was significantly associated with subsequent noncontact injuries (OR 14.16; 95% CI 1.90-105.49), though models lacked sufficient goodness of fit for adoption.
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