• Developed an advanced statistical model using Python to clean, manipulate, and analyze NBA player data, performing league-average normalization and data aggregation. • Applied statistical concepts to create a comprehensive player "Impact Score" by calculating per-game and per-100 possessions statistics, advanced metrics, and applying summation logic to derive player impact. • Created a new metric for evaluating player performance, aiding teams in prospect analysis, trade decisions, and free agency assessments by providing an objective measure of a player’s impact relative to league averages.
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Files used in code to generate findings, code, and associated visuals and research report
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