Basketball Analytics with R
Chapter 1 Introduction
1.1 Who is this book for?
While other people will no doubt find useful tools here, I’m primarily writing this book for fantasy basketball players, in all formats including daily fantasy sports (DFS). I’ve found that the best I can do with publicly-available tools is break even, and that’s not sustainable.
Moreover, the publicly-available tools are for the most part black boxes. And only one - SaberSim (https://www.sabersim.com/) - provides any information about the distribution of projected performance. So I decided to write my own, and share them as open-source code.
1.2 Why R?
R is the programming language I know best; I’ve been writing R code since 2000 and the language has grown in capability and popularity since then. Out of the box it’s always been the open source platform of choice for scientific and statistical computing, and it’s only gotten better.
1.3 Some books to get started
If you’re totally new to basketball analytics, I’d recommend starting with these four books:
- Langville and Meyer (2012): This is an undergraduate-level book on the mathematics of sports ranking and rating systems. It’s very well written and covers the basics of linear algebra.
- Oliver (2004): This is the fundamental reference for basketball player and team box score analytics. If you’ve heard of “The Four Factors”, this is where the concept came from!
- Shea and Baker (2013): This is a more visual and detailed collection of tools for describing basketball player performance.
- Shea (2014): This is a follow-on to Shea and Baker (2013), with added tools based on the spatial tracking data now available.
Basketball Analytics with R by M. Edward (Ed) Borasky is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Based on a work at https://github.com/znmeb/basketball-analytics-with-r.
Langville, A.N., and C.D. Meyer. 2012. Who’s Number One?: The Science of Rating and Ranking. Princeton University Press.
Oliver, D. 2004. Basketball on Paper: Rules and Tools for Performance Analysis. Brassey’s, Incorporated.
Shea, S.M., and C.E. Baker. 2013. Basketball Analytics: Objective and Efficient Strategies for Understanding How Teams Win. Createspace Independent Pub.
Shea, S.M. 2014. Basketball Analytics: Spatial Tracking. CreateSpace Independent Publishing Platform.