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This study presents a novel algorithm for automatically analyzing modality patterns in countermovement jump (CMJ) force-time curves. Bimodal peaks (Fz1, Fz3) are identified using a minimum threshold (Ttrough_drop) for their relative drop to the intermediate trough value (Fz2). In a large sample of athletes (n = 214), 75% of jumps were technically bimodal (Ttrough_drop > 0%) but this decreased to 17% (Ttrough_drop > 5%) and 0% (Ttrough_drop > 20%) using alternative definitions. This suggests that conflicting findings in other studies may be explained by a lack of standardized criteria for classifying modality. The drop from Fz1 to Fz2 in bimodal jumps was also largely correlated (r = 0.75) to the force at zero velocity and braking acceleration (r = 0.63). These findings highlight the potential value of extracting new quantitative features related to curve modality for CMJ research and interpretation.