NBA Player Stat Multi-Output Prediction Model (Random Forest)
type: SoftwareApplication
type: Model
description: A multi-output regression model trained using scikit-learn's MultiOutputRegressor wrapping a RandomForestRegressor. It predicts 6 key end-of-season player statistics (pts, reb, stl, tov, fg3a, fga) based on historical aggregated box-score data from NBA regular seasons and playoffs (2012-13 to 2023-24). Input features undergo preprocessing including dropping identifiers and one-hot encoding.
keywords: NBA
keywords: basketball
keywords: player statistics
keywords: prediction
keywords: random forest
keywords: multi-output regression
keywords: scikit-learn
keywords: FAIR4ML
author: Burak Baltali
license: https://creativecommons.org/licenses/by/4.0/
application category: Machine Learning
application sub category: Regression
programming language: Python
runtime platform: scikit-learn>=1.4.2
software requirements: https://github.com/bubaltali/nba-prediction-analysis/blob/main/requirements.txt
code repository: https://github.com/bubaltali/nba-prediction-analysis/
date modified: 2025-04-26
version: 1.0
has input: regular_train.csv
  type: Dataset
  description: For training purposes, the seasons 2012-2013 through 2021-2022 were selected.
has input: regular_test.csv
  type: Dataset
  description: For testing purposes, the 2022-2023 season was selected.
has input: playoff_train.csv
  type: Dataset
  description: For training purposes, the seasons 2012-2013 through 2022-2023 were selected.
has input: playoff_test.csv
  type: Dataset
  description: For testing purposes, the 2023-2024 season was selected.
has feature: age
  type: PropertyValue
  description: Player age during the season.
has feature: gp
  type: PropertyValue
  description: Games played during the season.
has feature: mp
  type: PropertyValue
  description: Minutes played during the season.
has feature: fg3a_last
  type: PropertyValue
  description: Three-point field goal attempts in the previous season.
has feature: fga_last
  type: PropertyValue
  description: Field goal attempts in the previous season.
has feature: team
  type: PropertyValue
  description: Player's team (one-hot encoded).
predicts: pts
  type: PropertyValue
  description: Predicted points per season.
predicts: reb
  type: PropertyValue
  description: Predicted rebounds per season.
predicts: stl
  type: PropertyValue
  description: Predicted steals per season.
predicts: tov
  type: PropertyValue
  description: Predicted turnovers per season.
predicts: fg3a
  type: PropertyValue
  description: Predicted 3-point field goal attempts per season.
predicts: fga
  type: PropertyValue
  description: Predicted field goal attempts per season.
associated media: Plf-LAL_evaluation_plots.png
  type: ImageObject
  description: Evaluation plots for the Playoffs - LAL Subset scenario.
  encoding format: image/png
associated media: Plf-Whole_evaluation_plots.png
  type: ImageObject
  description: Evaluation plots for the Playoffs - Whole Dataset scenario.
  encoding format: image/png
associated media: Reg-LAL_evaluation_plots.png
  type: ImageObject
  description: Evaluation plots for the Regular Season - LAL Subset scenario.
  encoding format: image/png
associated media: Reg-Whole_evaluation_plots.png
  type: ImageObject
  description: Evaluation plots for the Regular Season - Whole Dataset scenario.
  encoding format: image/png
uses algorithm: sklearn.ensemble.RandomForestRegressor
  type: SoftwareApplication
  software version: 1.4.2
  hyperparameters:
    n estimators: 100
    random state: 42
uses algorithm: sklearn.multioutput.MultiOutputRegressor
  type: SoftwareApplication
  software version: 1.4.2
training procedure: Trained on regular-season data (2012–2023) with a single train/test split. Fitting used MAE minimization without additional cross-validation.
has evaluation measure: R² Score (Regular Season - Whole Dataset - Points)
  type: QuantitativeValue
  value: 0.992233
  description: R² score evaluated on the regular season test set for the 'pts' target.
has evaluation measure: MAE (Regular Season - Whole Dataset - Points)
  type: QuantitativeValue
  value: 25.801855
  unit text: points
  description: Mean Absolute Error evaluated on the regular season test set for the 'pts' target.
has evaluation measure: R² Score (Playoffs - LAL Subset - Points)
  type: QuantitativeValue
  value: 0.860259
  description: R² score evaluated on the LAL playoff test subset for the 'pts' target.
is part of: NBA Prediction Analysis
  type: ResearchProject
  description: Project analyzing historical NBA data to predict player and team performance, following FAIR principles.