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A Deep Learning Approach Based on Interpretable Feature Importance for Predicting Sports Results

Messaoud Bendiaf

Messaoud Bendiaf

Department of Computer Science, University Mohamed El Bachir El Ibrahimi of Bordj Bou ArreridjBordj Bou Arreridj, Algeria
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Bendiaf, Messaoud
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Hakima Khelifi

Hakima Khelifi

Department of Computer Science, University Mohamed El Bachir El Ibrahimi of Bordj Bou ArreridjBordj Bou Arreridj, Algeria
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Khelifi, Hakima
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Djamila Mohdeb

Djamila Mohdeb

Department of Computer Science, University Mohamed El Bachir El Ibrahimi of Bordj Bou ArreridjBordj Bou Arreridj, Algeria
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Mohdeb, Djamila
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Mouhoub Belazzoug

Mouhoub Belazzoug

Department of Computer Science, University Mohamed El Bachir El Ibrahimi of Bordj Bou ArreridjBordj Bou Arreridj, Algeria
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Belazzoug, Mouhoub
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Abdelhamid Saifi

Abdelhamid Saifi

Department of Computer Science, University Mohamed El Bachir El Ibrahimi of Bordj Bou ArreridjBordj Bou Arreridj, Algeria
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Saifi, Abdelhamid
  
19 mar 2025
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Data publikacji: 19 mar 2025
Zakres stron: 56 - 72
DOI: https://doi.org/10.2478/ijcss-2025-0004
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© 2025 Messaoud Bendiaf et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

The proposed methodology.
The proposed methodology.

Figure 2.

Receiver Operating Characteristic (ROC) curves of the six models.
Receiver Operating Characteristic (ROC) curves of the six models.

Figure 3.

Confusion matrix of the MLP model with values −1 (Away Win), 0 (Draw), and 1 (Home Win).
Confusion matrix of the MLP model with values −1 (Away Win), 0 (Draw), and 1 (Home Win).

Figure 4.

SHAP summary plot.
SHAP summary plot.

Figure 5.

Force plot for the first prediction's explanation.
Force plot for the first prediction's explanation.

Figure 6.

Correlation matrix between features.
Correlation matrix between features.

Description of features_

Feature Name Description
HomeTeam Home Team
AwayTeam Away Team
FTR Full Time Result (H=Home Win, D=Draw, A=Away Win)
HS Home Team Shots
AS Away Team Shots
HST Home Team Shots on Target
AST Away Team Shots on Target
HC Home Team Corners
AC Away Team Corners
HF Home Team Fouls Committed
AF Away Team Fouls Committed
HY Home Team Yellow Cards
AY Away Team Yellow Cards
HR Home Team Red Cards
AR Away Team Red Cards

Performance comparison of the six models in our study_

Classifiers Accuracy Precision Recall F1-score AUC
Logistic Regression 0.64 0.62 0.64 0.63 0.81
Naïve Bayes 0.60 0.60 0.60 0.60 0.75
Support Vector Machine 0.64 0.63 0.64 0.64 0.82
Multilayer Perceptron 0.67 0.66 0.67 0.67 0.83
Random Forest 0.64 0.62 0.64 0.62 0.81
XGBoost 0.66 0.63 0.66 0.64 0.82
Język:
Angielski
Częstotliwość wydawania:
2 razy w roku
Dziedziny czasopisma:
Informatyka, Bazy danych i eksploracja danych, Informatyka, inne, Sport i rekreacja, Wychowanie fizyczne, Sport i rekreacja, inne
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