## 2 Materials and Methods
### Statistical Analysis  
First, a descriptive analysis with mean and standard deviation was performed to describe the measurements obtained by the algorithm and video recording (Table 1). The agreement of the algorithm was evaluated using the Bland-Altman method [28], with a limit of agreement (LoA) of 95%, calculating the mean difference between the angle detected by the algorithm and the video recording at each angle (Figure 6). The percentage mean differences and the effect size between means of both instruments were also calculated, using Cohen's d, following the classification of [PERSON], (2006) [29]: trivial (0.2), small (0.2-0.6), medium (0.6-1.2), long (1.2-2.0), and very long (2.0-4.0). A one-way ANOVA together with the Games-Howell post hoc text was used to determine differences between the angulations recorded by both instruments at each angulation (Table 1). \(p\) > 0.01 was selected to mark the level of significance. To calculate the reproducibility of the algorithm, the %CV was used, where % < 10% has been defined as \"poor\" in the interpretation of reproducibility in the use of technology in sport [30]. A T test for paired samples, together with Cohen's d with a 95% confidence interval, and the Bonferroni post hoc test, were used to determine differences at each of the angulations at 13 km/h and 18 km/h (Table 2). A descriptive analysis was carried out with mean and standard deviation of the speed before and after CoD as well as the duration of the action (Figure 7a-c). Lastly, the effect size between the average recorded by each IMMU at each angulation was analyzed, as well as the mean differences (Table 3). All analyzes were carried out using Jamovi (V1.6.7.0, Sydney, Australia; The Jamovi project, 2021). Figure 5: Example of a 90\({}^{\circ}\) left CoD during video analysis in Kinovea®. \begin{table}
\begin{tabular}{c c c c c c c c} \hline
**CoD** & **Video Criterion** & **Algorithm Criterion** & **Mean Bias** & **\% Diff** & **Effect Size** & **CI 95\%** & **CV (\%)** \\
**Angle** & **(Mean \(\pm\) SD)** & **Mean \(\pm\) SD** & \(\pm\) SD** & **\% Diff** & **(Cohen’s d)** & **(Lower/Upper)** & **CV (\%)** \\ \hline
**45L** & \(45\pm 2.7\) & \(44.1\pm 5.2\) & \(-0.9\pm 0.4\) & \(2.0\) & \(-0.21\) & \(-0.43/0.01\) & \(11.7\) \\ \hline
**45R** & \(46.2\pm 1.4\) & \(47.6\pm 4.8\) & \(1.3\pm 0.4\) & \(2.9\) & \(0.31\) & \(0.10\)//\(0.51\) & \(10.0\) \\ \hline
**90L** & \(90.4\pm 1.7\) & \(90.9\pm 3.1\) & \(0.5\pm 0.3\) & \(0.5\) & \(0.17\) & \(-0.02/0.37\) & \(3.4\) \\ \hline
**90R** & \(91.7\pm 1.1\) & \(95.0\pm 3.8\)*** & \(3.3\pm 0.3\) & \(3.4\) & \(0.94\) & \(0.72/1.16\) & \(4.0\) \\ \hline
**135L** & \(140.2\pm 10.3\) & \(140.7\pm 4.0\) & \(0.5\pm 1.1\) & \(0.3\) & \(0.04\) & \(-0.14/0.24\) & \(2.8\) \\ \hline
**135R** & \(137.4\pm 1.2\) & \(143.2\pm 5.5\)*** & \(5.7\pm 0.5\) & \(3.9\) & \(1.00\) & \(0.79/1.28\) & \(3.8\) \\ \hline
**180L** & \(181.8\pm 3.5\) & \(184.4\pm 5\)*** & \(2.5\pm 0.5\) & \(1.4\) & \(0.47\) & \(0.26/0.68\) & \(2.7\) \\ \hline
**180R** & \(180.9\pm 2.4\) & \(182.7\pm 4.3\)*** & \(1.7\pm 0.5\) & \(0.9\) & \(0.35\) & \(0.17/0.54\) & \(2.3\) \\ \hline \end{tabular} Note: \({}^{***}\)\(p<0.001\).  
\end{table} 
Table 1: Validity, reproducibility, and precision of the algorithm to measure CoDs at different angulations, compared to high-resolution video.