This is a review of the baseball Pythagorean Theorem research conducted by Jay Heumann. In baseball, the general belief is that a team’s ratio of runs scored to runs allowed is actually a better predictor of a team’s future performance than their winning record. This is based on the baseball Pythagorean Theorem, which uses the…
DetailsThis is a review of the sports analytics curling research conducted by Paul Brenzel, William Shock, and Harvey Yang. Curling enjoys great popularity in Canada and is on the rise in the United States. This study models curling as a Markov process to estimate win probabilities of different states during a curling match. In this…
DetailsIt’s a great day in sports analytics! Today, we will look at another method of analytics that is widely used in sports—and that is uplift and persuasion modeling. Uplift and persuasion modeling is an aspect of data science which uses data aggregation to create predictive models for performance analysis. Sports analysts build predictive models, and…
DetailsIt’s a great day in sports analytics! Today we are going to discuss network analytics and how it’s applied in sports. Network analytics has been used by various fields for a very long time. It is used in process control networks which run across the manufacturing sector, utilities, health, and even in sports. The effectiveness…
DetailsIt’s a great day in sports analytics! Today, we will be looking at three critical phases of sports analytics: Descriptive, Predictive, and Prescriptive Analytics. Before we go on, let’s briefly discuss what each of the analytics mean. Descriptive analytics is a method used by analysts to understand what has happened within the field in the…
DetailsIt’s a great day in sports analytics! Our topic of discussion for today is supervised and unsupervised learning. Within machine learning, there are two main types of tasks: supervised and unsupervised. Today, we’ll learn what is supervised learning and how it relates to unsupervised learning. Coaches and sports analysts use the data mining process of supervised and unsupervised learning techniques to group players or…
DetailsIt’s a great day in sports analytics! Today, we’re going to discuss the use of populations and samples, which are an integral part of probability and statistics. And we will examine populations and samples, as they are used in empirical research as a method of analyzing sports. Establishing populations and samples through an empirical approach…
DetailsIt’s a great day in sports analytics! Today, we will discuss two similar sports analytics methods called the Wilcoxon Signed Rank Test and Kruskal Wallis H Test. In the application of Wilcoxon Signed Rank Test and Kruskal Wallis H Test, coaches and sport analysts employ tests to compare two or more independent samples that are…
DetailsIt’s a great day in sports analytics! Today, I will discuss another technique of sport analytics which looks quite simple, but is very effective in enhancing the performance of a player or a team—and that is Deductive and Inductive Reasoning. Coaches often use this method to reach a particular conclusion—inductive reasoning is used to reach…
DetailsIt’s a great day in sports analytics! Today, we will be looking at another critical approach that is used in sport analytics, and that is simulation. Coaches, managers, and sports analysts employ simulation methods to predict the outcome of events or performances of particular players or teams. This allows the managers to predict the chances…
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