Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
95 tokens/sec
Gemini 2.5 Pro Premium
55 tokens/sec
GPT-5 Medium
22 tokens/sec
GPT-5 High Premium
29 tokens/sec
GPT-4o
100 tokens/sec
DeepSeek R1 via Azure Premium
82 tokens/sec
GPT OSS 120B via Groq Premium
469 tokens/sec
Kimi K2 via Groq Premium
210 tokens/sec
2000 character limit reached

Corporate Evidential Decision Making in Performance Prediction Domains (1302.1523v1)

Published 6 Feb 2013 in cs.AI

Abstract: Performance prediction or forecasting sporting outcomes involves a great deal of insight into the particular area one is dealing with, and a considerable amount of intuition about the factors that bear on such outcomes and performances. The mathematical Theory of Evidence offers representation formalisms which grant experts a high degree of freedom when expressing their subjective beliefs in the context of decision-making situations like performance prediction. Furthermore, this reasoning framework incorporates a powerful mechanism to systematically pool the decisions made by individual subject matter experts. The idea behind such a combination of knowledge is to improve the competence (quality) of the overall decision-making process. This paper reports on a performance prediction experiment carried out during the European Football Championship in 1996. Relying on the knowledge of four predictors, Evidence Theory was used to forecast the final scores of all 31 matches. The results of this empirical study are very encouraging.

Citations (9)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube