Predicting maximal 400-m swim performance using submaximal swim times and training log variables

 The purpose of the present study was to examine the validity of using a combination of submaximal swim measures and log book variables to predict 400-m maximal swim performance in well -trained triathletes. Seven well -trained triathletes (five male, two female) recorded subjective ratings of well being (quality of sleep, fatigue, stress and muscle soreness), training effort (day prior), resting morning heart rate and previous day's training details (minutes swum, bicycled or run) in daily training logs for a 42 -day period during the preparation phase of a triathlon -training year. Each participant also completed three consecutive swimming performance measures (200-m and 500-m submaximal, and 400-m maximal swims) at two of four regular weekly swim -training sessions.  Statistical analyses revealed that 200-m submaximal swim time (r = 0.602, p = 0.000), 500-m submaximal swim time (r = 0.655, p = 0.000), quality of sleep (r = 0.201, p = 0.039), stress (r = 0.251, p = 0.013) and training effort (day prior) (r = 0.314, p = 0.003) were significantly correlated to the variation in 400-m maximal swim performance. Hierarchical regression analysis revealed that 49.4% of the variance in 400-m maximal swim performance was predicted by the 200-m and 500- m submaximal swim times. A combination of submaximal swim measures and log book variables significantly enhanced (F (7, 68) = 3.324, p = 0.004) the prediction such that 58.4% of the variance in 400-m maximal swim performance was explained. These results suggest that a combination of log book variables and submaximal swim measures account for a significant amount of the variance in 400-m maximal swim performance and that a combination of these variables may be used to monitor individual responses to swim training in well -trained triathletes.