*2.4. Statistical Analysis*

We assessed all variables for normality with the Shapiro–Wilk test and considered a variable to have a normal distribution if the probability value for a test was greater than or equal to 0.05. To describe riders' demographic characteristics, we computed the means, standard deviations, and 95% confidence intervals of rider age, BMI, Spanish foot size, height, and weight.

We measured intra-trial reliability with the three records for each CFI for each rider. To evaluate reliability within trials in each rider, we computed intra-class correlation coefficients. For interpreting ICC values, we considered values less than 0.40 as poor, values between 0.40 and 0.59 as fair, values between 0.60 and 0.74 as good, and values 0.75 or greater as excellent [30,31]. Portney and Watkins [32] proposed that reliability coefficients greater than 0.90 were sufficient for clinical measurement. We also calculated the mean scores and the standard error of measurement (SEM) [30]. We used Brand and Altman's [33] formula for the SEM as follow: SEM = SD × sqrt (1 − ICC).

The minimal detectable change (MDC) can be used to assess the minimal magnitude of change required to be 95% confident that the observed change between the 2 tests reflects the true change and not measurement error [34]. The MDC was calculated as: 1.96 <sup>×</sup> SEM <sup>×</sup> <sup>√</sup>2.

For demonstrating the effect size of the comparisons, the Cohen d coefficient was calculated. Cohen's d effect size can be interpreted as follows: values ≤0.20 indicate slight effects, values between 0.20 and 0.49 indicate fair effects, values between 0.50 and 0.79 indicate moderate effects, and values larger than 0.79 indicate large effects [35].

We computed nonparametric Mann–Whitney U tests to assess differences among CFIs groups. For all tests, we considered *p* values < 0.05 to be statistically significant. We used SPSS 19.0 for Windows (IBM, Chicago, IL, USA) to perform all analyses.
