StatsMonkey: A data-driven sports narrative writer

Nicholas D. Allen, John R. Templon, Patrick Summerhays McNally, Larry Birnbaum, Kristian Hammond

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations


There are certain types of stories that are often told in very structured ways; sports stories or financial reports are two examples. Readers care about these narratives because they are passionately interested in the topic and want to read about the specific details of the event. In other words, they care about the data and want to read a story that presents that data to them. However, in order to be compelling these narratives cannot merely repeat the data, rather they must tell a story from the data. In this paper, we will present a model for data-driven story-telling and discuss StatsMonkey, a system that automatically writes baseball stories from raw baseball game numerical data available online. We will show that a machine can generate interesting, readable stories and that it can make editorial decisions about what aspects of a situation to highlight. Further we will show that a machine can determine in what manner those aspects should be shared.

Original languageEnglish (US)
Title of host publicationComputational Models of Narrative - Papers from the AAAI Fall Symposium, Technical Report
PublisherAI Access Foundation
Number of pages2
ISBN (Print)9781577354864
StatePublished - 2010
Event2010 AAAI Fall Symposium - Arlington, VA, United States
Duration: Nov 11 2010Nov 13 2010

Publication series

NameAAAI Fall Symposium - Technical Report


Other2010 AAAI Fall Symposium
Country/TerritoryUnited States
CityArlington, VA

ASJC Scopus subject areas

  • Engineering(all)


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