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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | "Player Performance Prediction in Basketball Using AI" |
| Authors Name: | Augustine Tirkey , NA |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_211731
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| Published Paper Id: | IJRTI2605035 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | With the development of the Artificial Intelligence (AI) and data analytics, the sports performance evaluation has taken a new face, and its predictive capabilities are no longer reliant on the classic statistical method. This paper explores the use of AI-based models to forecast performance of a basketball player based on NBA 2024 per-game data. Using machine learning and deep learning algorithms, which are multiple linear regression, random forest regression, and artificial neural networks and applying them to the features of field goals, rebounds, assists, steals, blocked shots, turnups, and minutes played, the study predicts the efficiency of individual players during scoring. The data was pre-processed, formalized and the features were selected to ensure suitable accuracy of the model and avoid overfitting. The comparison showed that the AI-based models are far much better than the traditional tools of regression as they attain superior predictive validity and strength in evaluating the score and efficiency ratings of players. The outcomes of the study highlight the possibilities of AI as a potent decision-support instrument to coaches, analysts and talent scouts, which offers practical insights into player development, preparing game strategies and work organization. Besides, this study adds to the body of related literature on sports analytics because it shows that data-based intelligence can be used to optimize performance evaluation and resource distribution in professional basketball. Future studies can incorporate the contextual variables which can include fatigue of the player, team vibrations and the game circumstances and situational factors to bolster predictive accuracy. |
| Keywords: | Artificial Intelligence, Machine Learning, Basketball Analytics, Player Performance Prediction, Sports Analytics, NBA Data |
| Cite Article: | ""Player Performance Prediction in Basketball Using AI"", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.a288-a313, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605035.pdf |
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| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2605035
Registration ID:211731
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: a288-a313 Country: Ghaziabad, Uttar Pradesh, India Research Area: Other Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605035 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605035 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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