## 4 Discussion  
The aim of the study was to determine the intra-rater reliability and validity of the PlayerScore, as well as the influence of the rater's degree of expertise level. As expected, we found a high intra-rater reliability, determined by the test-retest reliability (ICC = 0.97) in the twice-rated matches of Spain against Germany. This high intra-rater reliability was also found in a similar study determining the validity and reliability in a live match analysis in soccer [40]. As shown by the linear regression plot of the PlayerScore team statistics between the first and second rating of Spain against Germany (Figure 3A), most players were rated very similarly, if not identically. We suggest that the raters were able to replicate their ratings very well after familiarizing themselves with the PlayerScore rating procedure. Consequently, the PlayerScore is a reliable rating tool for determining the individual players' performance in team handball. To determine the validity, whether the better-placed team in the final ranking of the tournament had a higher PlayerScore compared to the worst-placed team was analyzed. Figure 4: PlayerScore team performance (mean values) separated by raters and games. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Game**} & **Rater \#1** & **Rater \#2** & **Rater \#3** & **Rater \#4** & **Rater \#5** & **Rater \#6** \\  & **Mean \(\pm\) SD** & **Mean \(\pm\) SD** & **Mean \(\pm\) SD** & **Mean \(\pm\) SD** & **Mean \(\pm\) SD** & **Mean \(\pm\) SD** \\  & **(95\% CI)** & **(95\% CI)** & **(95\% CI)** & **(95\% CI)** & **(95\% CI)** & **(95\% CI)** & **(95\% CI)** \\ \hline Brazil–Poland & \(2.65\pm 5.66\) & \(1.26\pm 4.24\) & \(3.23\pm 9.64\) & \(1.39\pm 4.69\) & \(4.10\pm 4.56\) & \(2.77\pm 3.48\) \\  & (\(-0.62\)-\(5.92\)) & (\(-1.19\)-\(3.70\)) & (\(-2.33\)-\(8.80\)) & (\(-1.32\)-\(4.10\)) & (\(-1.46\)-\(6.73\)) & (\(0.76\)-\(4.77\)) \\ \hline Brazil–Hungary & \(2.90\pm 8.74\) & \(1.22\pm 5.77\) & \(2.40\pm 8.04\) & \(1.99\pm 6.56\) & \(5.09\pm 6.74\) & \(5.72\pm 10.28\) \\  & (\(-2.14\)-\(7.95\)) & (\(-2.11\)-\(4.55\)) & (\(-2.24\)-\(7.04\)) & (\(-1.80\)–\(5.78\)) & (\(1.20\)–\(8.98\)) & (\(-0.21\)–\(11.66\)) \\ \hline Spain–Germany & \(6.15\pm 11.10\) & \(4.64\pm 8.53\) & \(8.96\pm 13.81\) & \(6.87\pm 11.89\) & \(12.48\pm 9.73\) & \(-0.87\pm 5.30\) \\  & (\(-0.26\)-\(12.56\)) & (\(-0.28\)-\(9.56\)) & (\(0.99\)–\(16.93\)) & (\(0.01\)–\(13.74\)) & (\(6.86\)–\(18.10\)) & (\(-3.93\)–\(2.19\)) \\ \hline Spain–Poland & \(7.43\pm 10.78\) & \(6.69\pm 8.78\) & \(11.27\pm 16.01\) & \(7.83\pm 12.85\) & \(15.68\pm 10.82\) & \(2.66\pm 6.32\) \\  & (\(1.20\)–\(13.65\)) & (\(1.62\)–\(11.76\)) & (\(2.03\)–\(20.51\)) & (\(0.41\)–\(15.25\)) & (\(9.43\)–\(21.93\)) & (\(0.99\)–\(6.31\)) \\ \hline Spain–Hungary & \(6.16\pm 7.66\) & \(5.28\pm 7.07\) & \(8.38\pm 8.82\) & \(5.63\pm 7.12\) & \(8.73\pm 8.46\) & \(4.59\pm 8.04\) \\  & (\(1.74\)–\(10.58\)) & (\(1.74\)–\(10.58\)) & (\(3.29\)–\(13.48\)) & (\(1.51\)–\(9.74\)) & (\(3.85\)–\(13.62\)) & (\(-0.05\)–\(9.23\)) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._The paired sample T-test revealed a highly significant difference (\(p<0.001\)) between the summarized team PlayerScore of Brazil and Spain in their matches against Germany, Poland, and Hungary. The calculated very large effect size ([PERSON]'s d = 19.2) supported the conclusion that the PlayerScore is well-suited to determine the match performance in team handball and to discriminate between teams and players due to their performance in the team handball match. These results agree with the results of a previous study utilizing a simplified version of the PlayerScore in the IHF 2019 [29], because they also found a high difference in the PlayerScore between Denmark (PlayerScore: 51.1), who won the final 31:22 against Norway (PlayerScore: 16.7). Additionally, the authors also found a high relationship between the PlayerScore best-ranked players and the all-star team, nominated by the IHF.