Abstract
This study aimed to assess within-match performance fluctuations in table tennis by utilising a dynamic performance indicator, a tailored version of a double moving average. This performance indicator applied to the sequence of wins and losses per rally, modelled a player's momentary point-winning probability or playing strength. Binomial distribution and Monte Carlo simulations were employed to obtain the expected distributions of double moving averages and their kurtosis. A total of two hundred and eleven single matches from the 2020 Tokyo Olympic Games were examined to characterise the extent of empirical fluctuations and to test for deviations from the expected fluctuations. Results showed that there were large within-match fluctuations (average IQR per match = 0.27). In addition, only one out of the two hundred and eleven matches exhibited a significant deviation from the stochastically expected double moving average distribution. This deviation was observed in the kurtosis of sixteen matches (7.6%). These findings underline the importance of considering within-match dynamic changes when conducting theoretical or practical performance analyses. This consideration should also extend to other performance indicators and various sports games.