This study aimed to investigate the reliability, validity, and sensitivity of spatiotemporal parameters, during sprint skating, of bandy players. Thirty-two well-trained male bandy players (age: 17.8 ± 1.2 years; height: 1.80 ± 0.06 m; body mass: 75.7 ± 1.2 kg) participated in this study. They performed two 80 m linear skating sprints. To calculate the velocities and obtain glide-by-glide spatiotemporal variables, nine timing gates and two skate-mounted inertial measurement units (IMUs) were synchronized and used. The spatiotemporal variables at each step included the glide time, glide length, double support time, double support length, step length, and step frequency. All the spatiotemporal variables were analyzed separately: averaged over 80 m, during the acceleration, and the maximal steady-state phases. The relative and absolute reliability of the spatiotemporal parameters were good (ICC > 0.70; CV < 10%), except for the step frequency during the steady-state phase. The spatiotemporal parameters showed “good” to “satisfactory” sensitivity during the acceleration phase and whole sprint, and “marginal” sensitivity during the steady-state phase. Content validity was confirmed by a low percentage of the shared variance (17.9–34.3%) between the spatiotemporal parameters obtained during the acceleration and steady-state phases. A “stepwise” regression significantly predicted the steady-state skating velocity from the spatiotemporal metrics obtained during the acceleration [F(5,26) = 8.34, p < 0.001, adj. R2 = 0.62] and steady-state phases [F(5,26) = 13.6, p < 0.01, R2 = 0.67]. Only the step frequency obtained in the acceleration phase significantly predicted the maximal skating velocity (p < 0.01), while the glide length and step frequency derived during the steady-state phase significantly added to the prediction (p < 0.01). In conclusion, the spatiotemporal parameters, obtained by two skate-mounted IMUs, were shown to be reliable and sensitive measures of sprint skating, and they could be used to provide independent information for the different skating phases. The maximal skating velocity could be predicted from the spatiotemporal parameters, with longer gliding and more frequent steps as the most significant determinants.