# The Effect of Situational Variables on Women's Rink Hockey Match Outcomes
## 3 Results
As an example, the first prediction can be interpreted as follows: When a team of the same level plays an away game against an opponent of the same level and loses at halftime, the probability of winning the match is estimated to be 0.105 (95% CI: 0.075 to 0.145). This specific scenario was the most frequently observed in the analyzed competition, occurring 91 times, which accounts for 5.42% of the total occurrences. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**95\% CI for \(\beta\)**} & \multicolumn{6}{c}{**95\% CI for \(\beta\)**} \\ \cline{3-10}
**Predictors** & \(b\) & \(LL\) & \(UIL\) & OR & \(LI\) & \(LS\) & \(p_{\text{Wald}}\) & \(p_{\text{LR}}\) \\ \hline \multicolumn{10}{l}{Match status at halftime} & & & & & & \(<\)0.001 \\ \multicolumn{10}{l}{Loses (base)} \\ \multicolumn{10}{l}{Draws} & 1.496 & 1.124 & 1.868 & 4.462 & 3.076 & 6.473 & \(<\)0.001 \\ \multicolumn{10}{l}{Wins} & 3.023 & 2.665 & 3.381 & 20.556 & 14.370 & 29.406 & \(<\)0.001 \\ \multicolumn{10}{l}{Constant} & \(-4.991\) & \(-5.560\) & \(-4.422\) & 0.009 & 0.004 & 0.012 & \(<\)0.001 & \(<\)0.001 \\ \hline \multicolumn{10}{l}{Note. \(b\) = regression coefficient \(b\); \(LL\) = lower limit; CI = confidence interval; \(UL\) = upper limit; \(p_{\text{Wald}}\) = significance of parameter \(\beta\) with the Wald test; OR = odds ratio (exponential of coefficient \(b\)); \(p_{\text{LR}}\) = significance of parameter \(\beta\) with the partial likelihood ratio test.} \\ \end{tabular}
\end{table} 
Table 4: _Cont._ \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & & & & & \multicolumn{3}{c}{**95\% CI for Pr**} & \\ \cline{4-9}
**Situation** & **MatLoc** & **TeaLev** & **OppLev** & **MatStaHal** & **Pr(MatOut = Won)** & \(LL\) & \(UL\) & \(n\) & \% \\ \hline
1 & Away & Remained & Remained & Loses & 0.105 & 0.075 & 0.145 & 91 & 5.42 \\
2 & Home & Remained & Remained & Wins & 0.790 & 0.733 & 0.838 & 90 & 5.36 \\
3 & Away & Champions & Remained & Wins & 0.910 & 0.875 & 0.936 & 85 & 5.06 \\
4 & Home & Remained & Champions & Loses & 0.040 & 0.026 & 0.061 & 85 & 5.06 \\
5 & Home & Champions & Remained & Wins & 0.940 & 0.915 & 0.959 & 85 & 5.06 \\
6 & Away & Remained & Champions & Loses & 0.026 & 0.017 & 0.041 & 84 & 5.00 \\
7 & Away & Remained & Remained & Wins & 0.707 & 0.638 & 0.767 & 55 & 3.27 \\
8 & Away & Champions & Relegation & Wins & 0.975 & 0.961 & 0.985 & 55 & 3.27 \\
9 & Home & Relegation & Champions & Loses & 0.010 & 0.006 & 0.018 & 55 & 3.27 \\
10 & Home & Remained & Remained & Loses & 0.155 & 0.114 & 0.207 & 55 & 3.27 \\
11 & Away & Relegation & Champions & Loses & 0.007 & 0.004 & 0.012 & 54 & 3.21 \\
12 & Home & Champions & Relegation & Wins & 0.984 & 0.974 & 0.990 & 53 & 3.15 \\
13 & Home & Remained & Remained & Draws & 0.450 & 0.372 & 0.530 & 51 & 3.04 \\
14 & Away & Remained & Remained & Draws & 0.344 & 0.274 & 0.421 & 50 & 2.98 \\
15 & Away & Remained & Relegation & Wins & 0.904 & 0.860 & 0.935 & 45 & 2.68 \\
16 & Home & Relegation & Remained & Loses & 0.044 & 0.027 & 0.071 & 45 & 2.68 \\
17 & Away & Relegation & Remained & Loses & 0.028 & 0.018 & 0.047 & 42 & 2.50 \\
18 & Home & Remained & Relegation & Wins & 0.936 & 0.905 & 0.958 & 42 & 2.50 \\ \hline \hline \end{tabular} Note. Pr(MatOut = Won) = probability of winning a match; CI = confidence interval; \(LL\) = lower limit; \(UIL\) = upper limit; \(n\) = number of observations.  
\end{table} 
Table 5: Predictions of the probability of winning a match in 18 frequent situations. The optimal cut-off point, determined by the ROC curve, was found to be \(\pi=0.4396\). At this cut-off point, a high ability to detect both match victories (Sensitivity, Se = 85.6%) and non-victories (Specificity, Sp = 82.6%) was achieved, resulting in an overall correct classification rate of 83.9%. Therefore, the sensitivity and specificity values were more balanced for the \(\pi=0.4396\) cut-off point (Se = 85.6, Sp = 82.6%) compared to the \(\pi=0.5\) cut-off point (Se = 78.9%, Sp = 88.1%).