{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T12:55:35Z","timestamp":1770468935731,"version":"3.49.0"},"reference-count":21,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T00:00:00Z","timestamp":1726704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In the dynamic realm of golf, where every swing can make the difference between victory and defeat, the strategic selection of golf clubs has become a crucial factor in determining the outcome of a game. Advancements in artificial intelligence have opened new avenues for enhancing the decision-making process, empowering golfers to achieve optimal performance on the course. In this paper, we introduce an AI-based game planning system that assists players in selecting the best club for a given scenario. The system considers factors such as distance, terrain, wind strength and direction, and quality of lie. A rule-based model provides the four best club options based on the player\u2019s maximum shot data for each club. The player picks a club, shot, and target and a probabilistic classification model identifies whether the shot represents a birdie opportunity, par zone, bogey zone, or worse. The results of our model show that taking into account factors such as terrain and atmospheric features increases the likelihood of a better shot outcome.<\/jats:p>","DOI":"10.3390\/e26090800","type":"journal-article","created":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T04:59:54Z","timestamp":1726721994000},"page":"800","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Golf Club Selection with AI-Based Game Planning"],"prefix":"10.3390","volume":"26","author":[{"given":"Mehdi","family":"Khazaeli","sequence":"first","affiliation":[{"name":"School of Engineering and Computer Science, University of the Pacific, Stockton, CA 95211, USA"}]},{"given":"Leili","family":"Javadpour","sequence":"additional","affiliation":[{"name":"Eberhardt School of Business, University of the Pacific, Stockton, CA 95211, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,19]]},"reference":[{"key":"ref_1","first-page":"123","article-title":"The role of analytics in football: The rise of data-driven approaches","volume":"6","author":"Anderson","year":"2020","journal-title":"J. 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