Effect of mathematical modelling on determining lactate minimum test parameters before and after seven weeks of monitored training

Abstract

Summary Objectives The aim of this study was to investigate whether lactate minimum test parameters after seven weeks of training are dependent on mathematical modelling. Equipment and methods Eight female elite basketball athletes (age 20 ± 1 years; body mass 69.2 ± 5.6 kg; height 173.8 ± 9.1 cm; fat mass 21 ± 4%) were evaluated. Athletes were subjected to the lactate minimum test before and after seven weeks of training (pre-competitive phase). The rating of perceived exertion (RPE) test was applied 30 minutes after the sessions and used to quantitate the individualized training intensities. The training volume was determined by the duration of the session. Monotony and strain were calculated by derivations of the training load. The lactate minimum test consisted of three phases: (a) hyperlactatemia induction; (b) 8-min passive recovery; and (c) incremental test (3 min stages/intensities of 8, 9, 10, 11 and 12 km h −1 ). Two non-linear (cubic spline and 2 order polynomial) and two linear (linear 1 and linear 2) mathematical functions were used to calculate the lactate minimum intensity, [Lac] at lactate minimum intensity and time at lactate minimum intensity. Statistical significance was set at P Results Only the first week presented higher load, monotony and strain values than those in the other weeks. No interaction (moment × mathematical model) was found for the lactate minimum intensity ( P = 0.685; power = 0.145), [Lac] at lactate minimum intensity ( P = 0.753; power = 0.061) and time at lactate minimum intensity ( P = 0.835). Significant relationships were not obtained for time at lactate minimum intensity before and after the training period. Similar results were obtained for the linear 1 model when compared with the other models. Conclusions The results of the present investigation demonstrate that lactate minimum test parameter determination after seven weeks of training is not dependent on the mathematical modelling method used; however, further investigations are required regarding the linear 1 model because significant relationships were not observed with the other models both before and after the training period.