用4个关键数据预测疯狂三月比赛结果，模拟真实赛果
March Madness Tournament Predictions Model: A Mathematical Modeling Approach
- 仅用4个核心数据建模：攻防效率、强弱评级和两分防守命中率
- 通过逻辑回归生成胜率，模拟整轮赛事并验证准确率
- 适合对体育数据分析或机器学习建模感兴趣的研究者
本文基于2013年以来的NCAA篮球历史数据，提出一种简化版的疯狂三月赛程预测模型。该框架借鉴FiveThirtyEight的预测方法，仅保留四个关键预测变量：调整后进攻效率（ADJOE）、调整后防守效率（ADJDE）、实力评级（Power Rating）和两分投篮防守命中率。采用逻辑回归模型计算每支队伍在单场比赛中获胜的概率，并构建整轮锦标赛模拟系统。通过与真实世界中的锦标赛结果进行对比，评估模型表现，使用朴素方法和斯皮尔曼等级相关系数计算准确率。
原文摘要 · Abstract (English)
This paper proposes a model to predict the outcome of the March Madness tournament based on historical NCAA basketball data since 2013. The framework of this project is a simplification of the FiveThrityEight NCAA March Madness prediction model, where the only four predictors of interest are Adjusted Offensive Efficiency (ADJOE), Adjusted Defensive Efficiency (ADJDE), Power Rating, and Two-Point Shooting Percentage Allowed. A logistic regression was utilized with the aforementioned metrics to generate a probability of a particular team winning each game. Then, a tournament simulation is developed and compared to real-world March Madness brackets to determine the accuracy of the model. Accuracies of performance were calculated using a naive approach and a Spearman rank correlation coefficient.
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