### Sports Analytics Video – Predictive Modelling

Victor Holman, The Sports Analytics Expert, presents Sports Analytics 3 Minute Drill – Predictive Modelling. Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models…

### Sports Analytics Video – Bipartite Graph Algorithms

__________________________________ Victor Holman, The Sports Analytics Expert, presents his Sports Analytics 3 Minute Drill – Bipartite Graph Algorithms. In the mathematical field of graph theory, a bipartite graph (or bigraph) is a graph whose vertices can be divided into two disjoint and independent sets {\displaystyle U} U and {\displaystyle V} V such that every edge…

### Sports Analytics Video – Predictive Model Weights

Victor Holman, The Sports Analytics Expert, presents his Sports Analytics 3 Minute Drill – Predictive Model Weights. Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights. Soccer is the world’s most popular sport, however, its statistics are not as sophisticated as those used in other sports. Players are evaluated using simple stats like…

### Sports Analytics Video – Frequency Distribution

Victor Holman, The Sports Analytics Expert, presents his Sports Analytics 3 Minute Drill – Frequency Distributions. Frequency distribution is a table that displays the frequency of various outcomes in a sample. Each entry in the table contains the frequency or count of the occurrences of values within a particular group or interval, and in this…

### Sports Analytics Video – Expected Rewards Technique

Victor Holman, The Sports Analytics Expert, presents his Sports Analytics 3 Minute Drill – Expected Rewards Technique. The ultimate goal of decision making is to find an optimal behavior subject to some optimality criterion. Optimizing for the infinite-horizon expected discounted total reward is one of the most studied such criteria. ———————— Find out how Sports…

### Sports Analytics Video – Esports Analytics and Encounter Detection Algorithms

Victor Holman, sports analytics expert, explains eSports Analytics and Encounter Detection Algorithms. The field of e-sports, or computer games played competitively, is growing around the world, with millions of competitors and millions of viewers. As a result, e-sports analytics have emerged, which relate to both sports analytics and digital game analytics. E-sports analytics have grown…

### Sports Analytics Video – Expected Possession Value (EPV)

Using film or player tracking data, a quantitative analysis representative of the entire possession will occur where each moment in the possession is summarized on the basis of the expected value of the possession at each moment. For each moment of a possession a value is assigned to each of the individual tactical moves a player can…

### Sports Analytics Video – Markov Chains

In this 5th installment of Victor Holman’s Sports Analytics 3 Minute Drill, Victor explains the Markov Chains. A Markov decision process (MDP) is a discrete time stochastic control process. It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs…

### Sports Analytics Video – Egocentric Ghosting Model

In this installment of Victor Holman’s Sports Analytics 3 Minute Drill, Victor explains egocentric ghosting models. The use of data-driven ghosting models is increasing as player tracking data becomes more widely available. The issue with the models that have been previously constructed is that their analysis of the players’ decisions is based solely on the…

### Sports Analytics Video – Convolutional Neural Networks

In this installment of Victor Holman’s Sports Analytics 3 Minute Drill, Victor explains Convolutional Neural Networks. In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery. Convolutional Neural Networks use a variation of multilayer perceptrons designed to require minimal preprocessing. They are…