Academy & Industry Research Collaboration Center (AIRCC)

Volume 10, Number 18, December 2020

Automatic Generation of Text for Match Recaps using Esport Caster Commentaries


Oluseyi Olarewaju, Athanasios V. Kokkinakis, Simon Demediuk, Justus Roberstson, Isabelle Nölle, Sagarika Patra, Daniel Slawson, Alan P. Chitayat, Alistair Coates, Ben Kirman, Anders Drachen, Marian Ursu, Florian Block and Jonathan Hook, University of York, UK


Unlike traditional physical sports, Esport games are played using wholly digital platforms. As a consequence, there exists rich data (in-game, audio and video) about the events that take place in matches. These data offer viable linguistic resources for generating comprehensible text descriptions of matches, which could, be used as the basis of novel text-based spectator experiences. We present a study that investigates if users perceive text generated by the NLG system as an accurate recap of highlight moments. We also explore how the text generated supported viewer understanding of highlight moments in two scenarios: i) text as an alternative way to spectate a match, instead of viewing the main broadcast; and ii) text as an additional information resource to be consumed while viewing the main broadcast. Our study provided insights on the implications of the presentation strategies for use of text in recapping highlight moments to Dota 2 spectators.


Esport, Data-Driven Storytelling, Dota 2, Game Analytics, Broadcasting, social viewing, Linguistic Resources, Natural Language Generation.