Here, the best-performing methods were the window estimators with window sizes of 5 and 50, both with an ensemble RMSE of 0.28 0.29 0.27 kcal mol -1 . The RMSE for the uncorrelated estimate and window size N n 0 methods were marginally worse (0.31 0.32 0.30 and 0.32 0.34 0.31 kcal mol -1 , respectively), while the RMSEs for the initial sequence methods were substantially higher (≈ 0.46 kcal mol -1 ) due to late truncation. Worryingly, the initial sequence methods showed strongly bimodal distributions of discard times, centred around 1.5 and 7 ns. Hence, the strong bias sensitivity of the initial sequence methods comes with an increased propensity to truncate all data but the final local trough or plateau.