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Microsoft uses R for Xbox matchmaking

If you've ever played online multiplayer games like Halo on the Xbox console, you'll know that being matched up with the right teammates and opponents is a critical part of the experience. Getting matched with an opponent that's way above your skill level isn't just demoralizing for you; it's also a waste of time for them (you generally don't advance in the game unless you beat a player that's of a higher level than you). The problem is even more complex for team games: there's nothing worse than being in a team with a bunch of newbies and then being pwned by a bunch of veterans on the other side. Microsoft sets up online players into the best games for their skill level using the TrueSkill system, which is a Bayesian generalization of the Elo system used in chess matches. The basic methodology is described in this 2007 Microsoft Research paper, which used C# and F# for the data analysis and R for the visualizations. In the chart below, we see how the TrueSkill system performs compared to the Elo system for various kinds of games. An ideal matching system would generate the most number of drawn (tied) games, on the basis that players of equal skill are most likely to tie. According to the chart, the TrueSkill system works best for "Free for All" (e.g. Halo "Slayer") and "Head-to-Head" (one-on-one) matches, but not so for "Small Team" matches (which according to the paper are mostly capture-the-flag games). The methodology has certainly progressed since 2007, and the new XBox One console features an all-new ranking system. Still, it's interesting to see the foundations of the system that matches players in Microsoft games. Thanks to reader Mikhail Popov for the tip, and to Microsoft's Tom Minka for some additional background on the paper. Microsoft Research: TrueSkill(TM): A Bayesian Skill Rating System

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More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid

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