A Statistician Plays Darts



Ryan Tibshirani, Andrew Price and Jonathan Taylor



Darts is a popular game, played both in the pub and at a professional level. Yet most players aim for the highest scoring region of the board (triple 20), regardless of their skill level. It turns out that this is not always the optimal strategy! We describe a method for a player to obtain a customized heatmap of the dartboard. In this heatmap, the bright regions correspond to aiming locations which yield high (expected) scores. We also investigate alternate arrangements of the numbers 1 through 20, in an attempt to make scoring more difficult.

Get a personalized heatmap!

Ever wonder where you should be aiming your dart throws? We've developed an algorithm so that you can enter the scores of 50 or so dart throws aimed at the double bullseye, and get a personalized heatmap in return.

Movies

Here are some movies showing the path of optimal aiming locations, for the various dartboard arrangements discussed in the supplementary paper. The path is defined by increasing the marginal variance in the simple Gaussian model. It works best to save them to your computer and then play them.

standard

standard
Curtis

Curtis
linear

linear
high-quality MPEG high-quality MPEG high-quality MPEG
low-quality MPEG low-quality MPEG low-quality MPEG


About us

Ryan Andy Jon
Ryan Andy Jon
ryantibs at cmu dot edu adp162 at gmail dot com jtaylo at stanford dot edu

Ryan Tibshirani and Andy Price were graduate students at Stanford, with Ryan in Statistics and Andy in Electrical Engineering. Jon Taylor is a Professor of Statistics at Stanford and was Ryan's Ph.D. advisor. Ryan is now in the Statistics department at Carnegie Mellon and Andy is at Lab126.

We'd like to thank Rob Tibshirani for his many great suggestions during the development of the project. We'd also like to thank Patrick Chaplin for his eager help concerning the history of the dartboard's arrangement.


Click here to go back to Ryan's research page.