Past Meetup

A Bayesian Framework for Rating Teams in Recreational Ultimate Frisbee Leagues

This Meetup is past

40 people went

Insight Data Science Office

280 Summer St. · Boston, MA

How to find us

Enter through the main doors and proceed down to the mezzanine level. The doors are locked after 6pm, but someone will be on lobby duty to let people in. The talk will begin at 6:30pm -- please plan accordingly!

Location image of event venue


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 ( for sponsoring this meetup and to Insight Data Science ( for hosting the event!

Excited to see you there,