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From Noob to Smurf: Advanced Analytics for League of Legends

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dc.contributor.author Maymin, Philip Z.
dc.date.accessioned 2017-03-30T18:54:44Z
dc.date.available 2017-03-30T18:54:44Z
dc.date.issued 2017-03-24
dc.identifier.uri https://scholarworks.bridgeport.edu/xmlui/handle/123456789/1858
dc.description.abstract Standard metrics for multiplayer online battle arena (MOBA) games like League of Legends (LoL) are very simple: kills, deaths, and the like. At Vantage Sports, we use a proprietary method to generate unique metrics that are more useful for professional players. These metrics are then calculated for hundreds of thousands of amateur player games, and the results used to determine which ones most contribute to winning. Some of the most important ones are worthless deaths and smart kills, which refine the standard metrics based on whether the team overall benefited from the activity. A new player rating model described here correlates strongly with winning even though it is essentially based on just one individual's contribution to a five-on-five game. en_US
dc.language.iso en_US en_US
dc.subject Data analysis en_US
dc.subject Multiplayer online battle arena (MOBA) en_US
dc.title From Noob to Smurf: Advanced Analytics for League of Legends en_US
dc.type Presentation en_US
dc.institute.department School of Business en_US
dc.institute.name University of Bridgeport en_US
dc.event.location Bridgeport, CT en_US
dc.event.name Faculty Research Day en_US

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