Prediction Models with Sports Data
About this Course
In this course the learner will be shown how to generate forecasts of game results in professional sports using Python. The main emphasis of the course is on teaching the method of logistic regression as a way of modeling game results, using data on team expenditures. The learner is taken through the process of modeling past results, and then using the model to forecast the outcome games not yet played. The course will show the learner how to evaluate the reliability of a model using data on betting odds. The analysis is applied first to the English Premier League, then the NBA and NHL. The course also provides an overview of the relationship between data analytics and gambling, its history and the social issues that arise in relation to sports betting, including the personal risks.Created by: University of Michigan
Related Online Courses
In this guided project the learner will have the opportunity to learn how to create and sell templates created on Canva. Canva is an online graphic design program that allows you to create and... more
This specialization is intended for people working or aspiring to work in the field of public health at the local, regional, and national level. Over five courses taught by faculty from the... more
In diesem Kurs erfahren Sie, wie Sie mithilfe von Deep Learning ein Modell zur Bilduntertitelung erstellen. Sie lernen die verschiedenen Komponenten eines solchen Modells wie den Encoder und... more
In this project, we will analyze life expectancy data by performing data wrangling & exploratory data analysis (EDA). Pandas is a powerful open source data analysis tools in python. Exploratory... more
Through hands-on projects and expert-led instruction, you\'ll learn the entire UX design process, from conducting user research and creating wireframes to designing high-fidelity mockups and... more
Powered by
