Background Previous research has demonstrated a relationship between modifiable (e.g. hamstring strength, muscle fascicle length and high-speed running load), non-modifiable factors (e.g. age, previous injury) and hamstring strain injury (HSI) risk. However, these factors have mostly been assessed in isolation and no study to date has investigated the associations between running load, strength and muscle architecture with HSI risk. The study aim was to explore the interactions between modifiable HSI risk factors that are commonly assessed within elite Australian footballers. Methods A prospective cohort study design. Eccentric knee flexor strength and biceps femoris long head (BFlh) fascicle lengths were measured in 299 unique elite-level Australian Football players (age 24 ± 4 years, height 188 ± 8 cm, and weight 87 ± 9 kg) during two pre-seasons. Data from wearable micro-sensor units (high-speed running at = 24k/hr and total distance) were collected over two seasons of elite Australian Football. Results Across 408 player-seasons there were 67 HSIs (16.4%), which took an average of 17 ± 10 days and 23 ± 12 days to return to full training and competitive matches, respectively. Univariate analysis showed that BFlh pennation angle (OR 1.6, 95% CI 1.2-2.2), fascicle length (OR 0.6, 95% CI 0.5-0.9), weekly high-speed running distance (OR 1.7, 95% CI 1.2-2.4), weekly change in total distance (OR 1.5, 95% CI 1.1-2.2) and weekly change in high-speed running distance (OR 1.6, 1.2-2.2) were significantly different between the injured and uninjured group (P < 0.05). Combining strength and architectural variables of BFlh pennation angle, fascicle length and peak force was able to explain 12% of variance in the risk of sustaining a HSI. The addition of running load exposure variables of weekly distance and change in weekly distance to the multivariate model increased the explained variance to 20%. Conclusion Combining measures of running load exposure with hamstring strength and architecture, increases the variance explained by multivariate models for determining HSI risk. Despite this, there was still approximately 80% of unexplained variance in sustaining a HSI in this study. Key Points - Running load, eccentric knee flexor strength and biceps femoris long head (BFlh) architectural variables were measured in this study, with pennation angle, fascicle length, weekly high-speed running, weekly change in total distance and weekly change in high-speed running each having a significant association with HSI risk (P < 0.05) in isolation. - Multivariate modelling showed that a combination of five variables of BFlh pennation angle and fascicle length, eccentric knee flexor strength, weekly distance and weekly change in distance had the strongest association with HSI risk. - However, these variables when combined only explained ~ 20% of the variance, leaving 80% of the difference between injured and non-injured players unexplained by the variables measured in this study.
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