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Table 1.

Results of the frame-based evaluation for detecting cuts and drives.

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Table 1 Expand

Fig 1.

The vector components of the defender’s relative position to the offensive player and the basket–the two basic geometrical features h (distance between the defender and the direct path from the potential cutter to the basket) and c (distance between the projection point of the position of the defender onto the direct path of the potential cutter and the basket).

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Fig 1 Expand

Fig 2.

Left side—vector plot of early or equal (both green) and late (red) detections. The filled circle shows the player’s position at the moment of model detection of a cut opening, while the empty circles mark the position at the starting moment of the cut. Right side–Box plot of the distribution of time differences between first detected cut opening and actual cut start by the player.

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Fig 2 Expand

Table 2.

Average feature values at the starting moment of the cut marks according to quartile groups.

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Table 2 Expand

Fig 3.

Single feature partial dependence plots (line plots) and feature importance according to the Gini index (bar plot—bottom right).

Note that the y-axes in partial dependence plots are unitless.

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Fig 3 Expand

Fig 4.

Two-feature partial dependence plots showing the interactions between the feature pairs.

Note that the scaling is different–the impact of the feature-combos was not equally strong.

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Fig 4 Expand

Table 3.

Average attribute values of cutters and spot up shooters in the analyzed data set.

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Table 3 Expand

Table 4.

Average attribute values according to model detection results.

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Fig 5.

Example action for the detection of cutting opportunities.

1) Drive starts off the ball screen; 2) the moment of detection during the drive—the defender is hasting to rotate for helping; 3) at the moment of the pass the whole right (upper) side of the court is free from defenders; 4) The unfolding of the action–the right side of the court is still an empty space, although the pass already left the paint area.

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Fig 5 Expand

Fig 6.

SHAP values of the features derived from Metta Sandiford-Artest’s movement at the moment of first detection of an opening in the case study example.

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Fig 6 Expand