## 3 Results  
Significant differences were found in total distance covered in splits 0-15, 30-45 and 60-75, where more metres are covered in defeat matches (\(p<0.05\)). Furthermore, many sprints were shown in defeat matches in the splits 60-75 and 75-90 (\(p<0.05\)). The descriptive and statistical inference results for each variable and split time are presented in Table 1.  
Figure 1: Labelling mapping of membership function of fuzzy set Successful. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**Success**} & \multicolumn{4}{c}{**Unsuccess**} & \multicolumn{4}{c}{**Defeat**} & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(q^{2}\)} \\ \cline{2-13} \multicolumn{1}{c}{} & \multicolumn{4}{c}{**M \(\pm\) SD**} & \multicolumn{4}{c}{**Clips5**} & \multicolumn{4}{c}{**M \(\pm\) SD**} & \multicolumn{4}{c}{**Clips5**} & \multicolumn{4}{c}{**M \(\pm\) SD**} & \multicolumn{4}{c}{**Clips5**} & \multicolumn{4}{c}{**M \(\pm\) SD**} & \multicolumn{4}{c}{**Clips5**} \\ \hline \multirow{3}{*}{**C**} & 0-15 & 153.485 & \(\pm\) & 179.35 & 1426.47 & - & 1643.23 & 1560.78 & \(\pm\) & 192.36 & 1497.55 & - & 1824.00 & 1658.52 & \(\pm\) & 216.19 & 1593.57 & - & 1723.47 & 0.043 & 0.065 \\  & 15-30 & 1547.21 & 110.58 & 1480.29 & - & 1613.94 & 1557.24 & \(\pm\) & 181.96 & 1477.43 & - & 1597.05 & 1652.11 & \(\pm\) & 777.89 & 1418.41 & - & 18858.82 & 0.606 & 0.011 \\  & 30-45 & 1541.16 & \(\pm\) & 123.14 & 1466.75 & - & 1615.58 & 1442.35 & \(\pm\) & 176.41 & 1384.36 & - & 1500.33 & 1563.40 & \(\pm\) & 196.68 & 1504.31 & - & 1622.49 & 0.010 & 0.094 \\  & 45-60 & 1477.44 & \(\pm\) & 154.99 & 1383.78 & - & 1571.10 & 1500.49 & \(\pm\) & 157.38 & 1448.76 & - & 1552.22 & 1575.25 & \(\pm\) & 185.52 & 1519.51 & - & 16309.99 & 0.056 \\  & 60-75 & 1384.82 & \(\pm\) & 280.54 & 1215.29 & - & 1554.35 & 1440.79 & \(\pm\) & 165.60 & 1386.36 & - & 14952.22 & 1541.24 & \(\pm\) & 197.46 & 1481.92 & - & 1600.57 & 0.015 & 0.086 \\  & 75-90 & 1183.85 & \(\pm\) & 389.05 & 948.75 & - & 1418.94 & 1415.76 & \(\pm\) & 175.31 & 1358.13 & - & 1473.38 & 1402.68 & \(\pm\) & 184.70 & 1347.19 & - & 14568.18 & 0.114 & 0.102 \\ \hline \multirow{3}{*}{**C**} & 0-15 & 5.15 & \(\pm\) & 1.91 & 4.00 & - & 6.31 & 5.61 & \(\pm\) & 2.82 & 4.68 & - & 6.53 & 6.13 & \(\pm\) & 3.24 & 5.16 & - & 7.11 & 0.504 & 0.015 \\  & 15-30 & 4.31 & \(\pm\) & 1.38 & 3.48 & - & 5.14 & 5.13 & \A result of the movement patterns derived by the participating individuals of player was classified into three models for the different criteria considered (i.e., zones of velocity, sprint and acceleration and deceleration number). It generated three decision trees for every criterion variable with regard to six 15-min intervals (I; 1 to 6), ranging from 0-90 min to the identified cut-off values in relation to the mined six split times that differentiated the factors of win, draw and lost in competitive matches. A decision tree was created (Figure 2) categorising work rate movement patterns into six speed zones, ranging from 0 to \(>\)21.0 km\(\cdot\)h\({}^{-1}\) The attributes were codified hierarchically into 16 [root nodes (RNs) 1-16], which could conduct the performed (cut-off) in each split time into 16 levels. Statistical tendency for differences showed: Success (S\({}_{1,2,3,6,8,9,12,13,14}\)), Unsuccess (U\({}_{4}\)) and Defeat (D\({}_{5,7,10,11,15,16}\)). However, the number-sprint abilities decision tree (Figure 3) was characterised inducing sprinting performance during match play according to attributes, which were codified hierarchically into 12 (RNs 1-12), which could conduct the performed cut-off in each split time into of 12 levels. The statistical tendency was: Success (S\({}_{1,6,7,10,11,12}\)), Unsuccess (U\({}_{3}\)) and Defeat (D\({}_{2,4,5,8,9}\)). Finally, the number of accelerations and decelerations decision tree (Figure 4) was labelled into profile markers' capacity during match play and were codified hierarchically into 10 (RN 1-10), which could conduct the performed cut-off in each split time into 10 levels.