Quantifying player death impact in League of Legends

Ferreira, Ruben (author), Faganeli Pucer, Jana (author)

League of Legends is one of the world’s most played and watched e-sports. We study how the death of an individual player affects team win probability. From Diamond-tier matches, we construct minute-level snapshots to train a calibrated win-probability model. We formalize a death window based on the state just before death until the first state after the respawn. We attribute the team-level win-probability change to players via a role/time standardized Performance Score weighted by SHAP feature scores. Results across 150,472 death windows show, the team of the deceased player loses on average 2.03% of win probability; probability decreases in 58% of death windows and increases in 42%. The approach enables fast identification of impactful deaths and targeted learning opportunities.

• Language: English
• Keywords: esports analytics, win probability, player performance attribution, League of Legends
• Typology: 1.08 - Published Scientific Conference Contribution
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2025
• Number of pages: Str. 51-54
• PID: 20.500.12556/RUL-177555
• UDC: 004.9
• COBISS.SI-ID: 262492419
• Publication date in RUL: 24.12.2025

Record is a part of a monograph

• Title: Proceedings of the 11th Student Computing Research Symposium : (SCORES'25)
• Editors: Uroš Čibej, Luka Fürst, Lovro Šubelj, Jure Žabkar
• Place of publishing: Ljubljana
• Publisher: Založba UL FRI, = Faculty of Computer and Information Science
• Year: 2025
• ISBN: 978-961-7059-18-2
• COBISS.SI-ID: 261672195

Licences

• License: CC BY-SA 4.0, Creative Commons Attribution-ShareAlike 4.0 International
• Link: http://creativecommons.org/licenses/by-sa/4.0/
• Description: This Creative Commons license is very similar to the regular Attribution license, but requires the release of all derivative works under this same license.

Secondary language

• Language: Slovenian
• Keywords: analitika e-športa, verjetnost zmage, pripisovanje uspešnosti igralcev, League of Legends