## 4 Discussion  
To our knowledge, this study was the first to investigate the accuracy and the inter-unit reliability of an UWB system for monitoring the positions of players in indoor conditions. The results confirmed that this UWB model (WIMU PRO(tm)) was a suitable system to monitor position data with high accuracy (x = 5.2 \(\pm\) 3.1 cm; y = 5.8 \(\pm\) 2.3 cm) and good inter-unit reliability, with a large ICC for the x-coordinate (0.65), a very large ICC for the y-coordinate (0.85) and a good % TEM (2%). There is limited comparability of the accuracy and reliability with studies on other sport-related positioning techniques. Nevertheless, the results of average speed and the distance covered measurements reported [2; 17; 30; 31; 32; 17] allow the conclusion that this UWB model outperforms GNSS results. LPS reported better accuracy results than GNSS [5], with a mean absolute error of 23.4 \(\pm\) 20.7 cm, which is nonetheless outperformed by the present results. Considering that position measurement systems are mainly used for time-motion analyses in sport [1], this result seems acceptable [5]. It has been discussed that for tactical analyses, the estimation error of position sensing \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Designed Travel**} & \multirow{2}{*}{**Device**} & \multicolumn{3}{c}{**Differences**} & \multicolumn{3}{c}{**Percentage of Differences**} \\ \cline{3-6}  & & **X** & **Y** & **X** & **Y** \\ \hline \multirow{2}{*}{Perimeter of court} & 1 & 5.8 & 6.2 & 0.39\% & 0.41\% \\  & 2 & 5.1 & 5.1 & 0.34\% & 0.34\% \\ \hline \multirow{2}{*}{Center line of the court} & 1 & 7.4 & 7.2 & 0.53\% & 0.51\% \\  & 2 & 11 & 10.8 & 0.79\% & 0.77\% \\ \hline \multirow{2}{*}{Perimeter of the paint} & 1 & 0.3 & 4.4 & 0.05\% & 0.76\% \\  & 2 & 3.3 & 3.6 & 0.57\% & 0.62\% \\ \hline \multirow{2}{*}{6.75 m line} & 1 & 1.9 & - & 0.28\% & - \\  & 2 & 8.6 & - & 1.27\% & - \\ \hline \multirow{2}{*}{Center circle} & 1 & 5 & 5.9 & 3.03\% & 3.58\% \\  & 2 & 4.1 & 3.9 & 2.48\% & 2.36\% \\ \hline \multirow{2}{*}{Mean \(\pm\) SD} & 5.2 \(\pm\) 3.1 & 5.8 \(\pm\) 2.3 & 0.97 \(\pm\) 1 & 0.94 \(\pm\) 1.14 \\  & LOA (L to U) & 2.1 to 8.3 & 3.5 to 8.2 & \(-\)0.03 to 1.98 & \(-\)0.21 to 2.08 \\ \hline \hline \end{tabular} Note. LOA: Limits of agreement (L: Lower; U: Upper); SD: Standard deviation.  
\end{table} 
Table 1: Accuracy in mean differences (cm) and percentage of differences of x- and y-position coordinates. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Axis** & **Unit 1 (Mean \(\pm\) SD)** & **Unit 2 (Mean \(\pm\) SD)** & **ICC** & **90\% CI** & **\% TEM** \\ \hline \multirow{2}{*}{x} & 4.1 \(\pm\) 2.9 & 6.4 \(\pm\) 3.3 & 0.65 & \(\begin{array}{c}-0.15\text{ to}\\ 0.94\end{array}\) & 2 \\  & 5.9 \(\pm\) 1.2 & 5.9 \(\pm\) 3.4 & 0.88 & 0.26 to 0.99 & 2 \\ \hline \end{tabular} Note. ICC: Intra-class correlation coefficient; CI: confidence interval; TEM: Typical error of measurement; SD: Standard deviation.  
\end{table} 
Table 2: Inter-unit reliability of x- and y-position coordinates. should be below the natural sway of the body's center of gravity (15 to 20 cm) in the observed movements [1]. Therefore, the accuracy results in this study seem to be sufficient for such applications. Most sport applications of location systems focus on the analyses of time-motion parameters, such as covered distances or speeds [1]. The validation methods used in earlier studies, using standard courses and time gates, are sufficient for such analyses [17; 19; 30; 34]. Yet, other implications of position measurement systems (e.g., tactical analysis) require more accurate data. As a consequence, other studies have applied video analysis systems to satisfy these requirements for accuracy [5; 21; 35; 36]. However, these video analysis systems are expensive and time consuming. Moreover, given that each court venue should be evaluated for accuracy, these methods are not appropriate. For this main reason, an extended validation method seemed to be necessary.