对于NFL比赛和点差评估的随机模型
Muhammad Mohsin1, Albrecht Gebhardt2
1College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan.
Journal of applied statistics
|March 13, 2024
概括
这项研究引入了一种新的随机模型来分析体育数据,特别是比赛中胜利率. 这种新模型是从比瓦里亚特关联线性指数分布中衍生出来的,为体育分析提供了更好的适配.
科学领域:
- 运动分析 运动分析
- 统计建模 统计建模
- 可能性分布的概率分布.
背景情况:
- 统计建模对于体育分析和战略决策至关重要.
- 现有的模型可能无法完全捕捉体育结果的细微差别.
研究的目的:
- 引入一种新的随机模型来分析体育比赛的胜利率.
- 评估拟议模型的性能和稳定性.
- 将模型应用于现实世界的体育数据,以获得实际见解.
主要方法:
- 基于从双变异的亲线指数分布中得出的差异开发一个随机模型.
- 一个模拟研究来评估参数稳定性 (偏差,标准误差,RMSE,置信区间).
- 使用国家足球联盟 (NFL) 数据对现有模型的模型的应用和比较.
主要成果:
- 建议的差异分布为建模胜利边际提供了充分的适合性.
- 模拟结果证明了模型参数的稳定性.
- 该模型在应用于真实NFL数据时显示了竞争性表现.
结论:
- 新的随机模型有效地捕捉了体育比赛中胜利的边际.
- 该模型的量子函数可用于评估投注点差.
- 这种方法可以增强体育分析和战略投注决策.
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