The fastest repetition in a set predicts the number of repetitions completed to failure during resistance training: The impact of individual characteristics.

• Individual XRM-velocity relationships provided higher goodness of fit compared to general relationships on both testing sessions. • The goodness of fit of individual XRM-velocity relationships was not affected by sex, training status and history or personality traits. • Individual, but not general XRM-velocity relationships established in the first testing session provided acceptable predictions of XRM in the second testing session, on average. • Prediction accuracy of individual XRM-velocity relationships was not affected by sex, training status and history, or personality traits. The aim of this study was to examine the goodness of fit and prediction accuracy of general and individual relationships between the maximum number of repetitions completed in a set (XRM) and the fastest repetition in the set (XRM-velocity relationship) in the free-weight back squat exercise. The effects of sex, training status and history, as well as personality traits, on the goodness of fit and the accuracy of these relationships were also investigated. Forty-six resistance-trained people (15 females and 31 males) performed a one-repetition maximum (1RM) test, and two repetitions to failure (RTF) tests, 72 h apart. RTF tests were performed with 70, 80, and 90% of 1RM with 10 min of inter-set rest. A greater goodness of fit was found for individual XRM-velocity relationships (R2 = 0.98; residual standard error [RSE] = 1.01–1.15) compared to general XRM-velocity relationships (R2 = 0.45–0.49; RSE = 3.44–3.66). Individual, but not general XRM-velocity relationships established in the first testing session yielded acceptable prediction accuracy (mean error = 1.96 vs 2.81 repetitions) of XRM in the subsequent testing session. Sex, training status and history, and personality traits did not affect the goodness of fit of general and individual XRM-velocity relationships or their prediction accuracy, suggesting the potential generalisability of those findings among resistance-trained populations. Therefore, individual XRM-velocity relationships can be used to prescribe loads matching an intended XRM by recording only the fastest velocity of the set with a given load and predicting, with reasonable accuracy, the XRM for the individual. [ABSTRACT FROM AUTHOR]