使用贝叶斯逻辑建模,估计在NBA比赛中第四季度的胜率
Feng Wang1,2, Guohua Zheng1, Hua Li3
1School of Economics and Management, Shanghai University of Sport, Shanghai, China.
Frontiers in psychology
|May 20, 2024
概括
这项研究分析了近距离的NBA比赛,发现球队的第四季度节奏和射门百分比准确地预测了比赛结果. 这种洞察力有助于教练在关键时刻制定胜利策略.
科学领域:
- 运动分析 运动分析
- 量化体育研究 量化体育研究
- 篮球表现分析 篮球表现分析
背景情况:
- 紧密的NBA比赛 (定义为第四季度的特定积分差异) 对比赛结果至关重要.
- 了解影响这些游戏的因素可以提高预测建模和教练策略.
研究的目的:
- 确定关键因素,决定第四季度紧密的NBA比赛的结果.
- 开发和评估贝叶斯逻辑建模方法来预测游戏获胜者.
主要方法:
- 分析了2013-14赛季至2022-23赛季的2,295场密切的NBA比赛.
- 从NBA的盒子得分中利用了高级游戏统计数据 (步伐,射门百分比).
- 使用贝叶斯逻辑建模与伯努利分布来预测结果.
主要成果:
- 开发的模型准确地预测了游戏结果,真正比率为0.93和假正比率为0.07.
- 第四季度的速度和射击率被确定为重要的预测指标.
结论:
- 贝叶斯逻辑模型有效地估计了在密切的NBA比赛中获胜的概率.
- 调查结果为教练提供了可操作的见解,以改进游戏策略和战术决策.
相关概念视频
01:15Binomial Probability Distribution
10.4K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.4K
01:24Testing a Claim about Population Proportion
3.3K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.3K
01:14Probability in Statistics
12.7K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
12.7K
01:03Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K
01:14Parametric Survival Analysis: Weibull and Exponential Methods
418
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
418
01:20Actuarial Approach
75
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
75