A Bayesian Framework for Rating Teams in Recreational Ultimate Frisbee Leagues
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Hi everyone, I am excited to be taking over organizing the Stan Users meetup in Boston/Camberville! Thanks very much to Lizzie for all of her hard work in making this a successful meetup.
As Lizzie mentioned, we are looking for speakers! Talks can be 5 minutes, 10 minutes, or 30 minutes in length. Please let me know if you are interested in giving a talk or know someone else who is interested.
To kick things off for our first meetup in 2018, I will give a talk on rating teams in recreational ultimate frisbee leagues. In this talk, I show how a Bayesian framework offers a simple, clear path to rating teams that has a number of benefits relative to alternative, more heuristic-based approaches. Specifically, the Bayesian framework (1) transparently incorporates strength of schedule into the ratings; (2) allows the use of priors to account for the fact that teams self-select into one of three divisions (i.e., skill levels); (3) makes model validation straightforward; and (4) can lead to fun topics like quantitatively predicting the outcome of the end-of-season tournament. I will present a Stan model that implements this Bayesian framework and apply it to data from the local ultimate frisbee league run by the Boston Ultimate Disc Alliance. I use ScalaStan (an open-source Scala DSL for Stan) to build and run the model and Evilplot (an open-source data visualization library written in Scala) to make plots.
Special thanks to CiBO Technologies (http://www.cibotechnologies.com/) for sponsoring this meetup and to Insight Data Science (https://www.insightdatascience.com/) for hosting the event!
Excited to see you there,
Shane