2.4. Statistical Analysis

The statistical analysis was conducted using software IBM SPSS 26.0. (SPSS Inc. Chicago, IL, USA). Descriptive statistics included group means (M) and standard deviations (SDs). Normal distribution was checked using the Shapiro–Wilk test. Demographic and anthropometric data were compared between groups with an independent t-test or, if the data were not normally distributed, with a Mann–Whitney U test.

Hypothesis 1 was tested by comparing the groups without considering the dominance of the injured leg. Given that 15 of the 23 individuals in the ACL group sustained their injury on the non-dominant leg (Table 1), the injured leg of the ACL group was compared to the non-dominant leg of the control group and the contralateral leg of the ACL group was compared to the dominant leg of the control group. Independent t-tests or Mann–Whitney U tests, if the data were not normally distributed, were calculated for the TTS-ML, TTS-AP and TTS-V. The absence of within-subject differences between limbs in the control group in stabilization times were tested with paired t-tests or a Wilcoxon signed-rank test.

Hypothesis 2 was tested by distinguishing between dominant and non-dominant leg ACL injuries. Specifically, we compared the dominant leg of the control group to the dominant leg of the ACL group, which was the injured leg for some individuals and the uninjured contralateral leg for other individuals. Thus, this was an analysis of a between-subject factor with three levels: ACL leg, contralateral leg, control leg. The same procedure was repeated for the non-dominant leg. Non-parametric tests (Kruskal–Wallis) were selected to account for the small sample sizes in the sub-groups when comparing the TTS-ML, TTS-AP and TTS-V between ACL legs, contralateral legs, and control legs. Dunn–Bonferroni post hoc tests were applied to investigate pairwise comparisons. We rearranged the data in figures based on the dominance of the legs, with the aim of visualizing and comparing the effects of leg dominance regarding dynamic postural stability.

The significance level was set at alpha = 0.05. Effect sizes Cohen’s d and Rosenthal’s r [21] were calculated for parametric and non-parametric statistical comparisons. Cohen´s d was interpreted as follows: d = 0.20 for a small, d = 0.50 for a moderate and d = 0.80 for a large effect size and Rosenthal´s r was interpreted as follows: r = 0.10 for a small, r = 0.30 for a moderate and r = 0.50 for a large effect size.