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Two clusterings to capture basketball players’ shooting tendencies using tracking data: clustering of shooting styles and the shots themselves Cover

Two clusterings to capture basketball players’ shooting tendencies using tracking data: clustering of shooting styles and the shots themselves

Open Access
|Mar 2025

Figures & Tables

Figure 1:

An overview of the proposed method
An overview of the proposed method

Figure 2:

Scatterplots on the feature space of shots whose features are reduced to two dimensions by UMAP; left: all shots, right: 3-pointers.
Scatterplots on the feature space of shots whose features are reduced to two dimensions by UMAP; left: all shots, right: 3-pointers.

Figure 3:

Mean Silhouette Coefficients in Clustering of Shooting Styles
Mean Silhouette Coefficients in Clustering of Shooting Styles

Figure 4:

Mean Silhouette Coefficients in Clustering of the Shots Themselves
Mean Silhouette Coefficients in Clustering of the Shots Themselves

Figure 5:

Distance between the shooter and the rim 3 seconds before shot in two clusters as examples. Normalized frequencies are displayed. On the left is Cluster 1, which tends to have the shortest distance from the rim 3 seconds before the shot. On the right is Cluster 2, which also tends to have a shorter distance from the rim 3 seconds before the shot.
Distance between the shooter and the rim 3 seconds before shot in two clusters as examples. Normalized frequencies are displayed. On the left is Cluster 1, which tends to have the shortest distance from the rim 3 seconds before the shot. On the right is Cluster 2, which also tends to have a shorter distance from the rim 3 seconds before the shot.

Figure 6:

2D histogram of shot location, in two clusters as examples. Normalized frequencies are displayed. On the left is Cluster 1, with shot locations concentrated near the rim. On the right is Cluster 2, which exhibits shots well distributed from the rim to mid-range.
2D histogram of shot location, in two clusters as examples. Normalized frequencies are displayed. On the left is Cluster 1, with shot locations concentrated near the rim. On the right is Cluster 2, which exhibits shots well distributed from the rim to mid-range.

Figure 7:

Visualization of shooting style clusters by t-SNE
Visualization of shooting style clusters by t-SNE

Figure 8:

Percentage of each shot cluster for Stephen Curry, Kevin Durant, Anthony Davis, and Dirk Nowitzki. Note that the total number of shot data is 216, 248, 280, and 262, respectively.
Percentage of each shot cluster for Stephen Curry, Kevin Durant, Anthony Davis, and Dirk Nowitzki. Note that the total number of shot data is 216, 248, 280, and 262, respectively.

Shooting Style Cluster Description

Cluster NameDescriptionMean Height [cm]Example Players
Close-Range BigBig Men who attempt most shots from close-range.210.6Andre Drummond
Dwight Howard
Mid-Range BigBig Men who can shoot from close-range as well as mid-range.209.9Pau Gasol
LaMarcus Aldridge
Mid-Range All-RounderPlayers who play offense from mid-range and often shoot from near the high post.208.9Kevin Garnet
Dirk Nowitzki
Mid-Range SlasherPlayers who attack the rim from mid-range through post-play or drive.206.5Shaun Livingston
DeMarcus Cousins
Driving All-RounderPlayers who begin offense from beyond the arc and aim to shoot from anywhere with their versatile skills.198.6Stephen Curry
Kevin Durant
Pull-up Ball-HandlerPlayers who often drive and aim for many pull-up jumpers.189.9Kyle Lowry
Damian Lillard
Driving Ball-HandlerPlayers who often drive from the perimeter, but also attempt threes moderately.190.7Russell Westbrook
James Harden
Stretch FourBig shooter who often attempts corner threes or threes from the top position.205.2Nikola Mirotic
Meyers Leonard
Corner ShooterShooter attempting mainly three-pointers from the corner.198.6Patrick Beverley
Jason Terry
Pure ShooterShooter who attempts 3-pointers from any location.194.4Eric Gordon
Kyle Korver
Slashing FinisherPlayers who do not shoot many threes and prefer to drive from beyond the arc.199.9DeMar DeRozan
Tony Parker
Driving ShooterSimilar to Corner Shooter, but shooter with a slight preference for drive.201.5Klay Thompson
Vince Carter
Stretch All-RounderPlayers who shoot from close-range to midrange, stretch and shoot 3-pointer as well.205.7Kristaps Porzingis
Kevin Love

Shot features and their units

Shot FeatureUnit
x, y coordinates on the court of the shooter at the time of the shotmeter
x, y coordinates on the court of the shooter 1 second before the shotmeter
x, y coordinates on the court of the shooter at the time of receiving the ballmeter
distance to the rim at the time of the shotmeter
distance to the rim 0.5 seconds, 1 second, 1.5 seconds, 2 seconds, 2.5 seconds, and 3 seconds before the shotmeter
distance to the rim when the ball was receivedmeter
distance traveled while holding the ballmeter
speed at the time of the shotmeter / second
time of holding the ballsecond

Shot cluster names and examples of shots in each cluster_ The red and blue lines in the image represent the shooter's trajectory from 3 seconds before the shot to the time of the shot when holding the ball and when not holding the ball, respectively; the lighter the color, the later the time series_

Cluster NameExample Images
3-pointer from the right corner or right wing
3-pointer from the left corner
3-pointer from the top of the key or left wing
Mid-range shot near the high-post
Shot from a mid-post move
Close-range shot from a post move
Cutting layup/dunk
Mid-range shot from the right side
Mid-range shot from the left side
Driving layup/dunk

Top 5 players for Close-Range Big, Driving All-Rounder, Stretch All-Rounder, Slashing Finisher and Driving Shooter in TS%

Close-Range Big
Player Name (Team)FGATS%
Hassan Whiteside (MIA)68262.9
DeAndre Jordan (LAC)50862.8
Cole Aldrich (LAC)22562.6
Andrew Bogut (GSW)27962.3
Steven Adams (OKC)42662.1
Language: English
Page range: 35 - 55
Published on: Mar 2, 2025
Published by: International Association of Computer Science in Sport
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2025 Kazuhiro Yamada, Keisuke Fujii, published by International Association of Computer Science in Sport
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.