Match forecasts in UEFA club competitions: Elo ratings versus Transfermarkt valuations
Abstract
The pre-season strengths of European football clubs are usually measured by two proxies in the literature. Football Club Elo Ratings provide strictly performance-based Elo ratings from the early days of the European Cups, while Transfermarkt valuations are crowd-based estimates of squad market values. This paper compares them by evaluating their ability to forecast the results of matches played in the UEFA Champions League and the UEFA Europa League between the seasons 2020/21 and 2024/25. The two indicators yield almost identical out-of-sample accuracy when used separately. Combining the two measures leads to a modest improvement, but the best aggregation procedure is sensitive to the forecast target. Our results suggest that seeding based on Elo ratings would be (closely) optimal.
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BibTeX
@misc{csurilla2026match,
title = {{Match forecasts in UEFA club competitions: Elo ratings versus Transfermarkt valuations}},
author = {Gergely Csurilla and László Csató},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.21674},
eprint = {2609.21674},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.21674},
}
RIS
TY - UNPB
TI - Match forecasts in UEFA club competitions: Elo ratings versus Transfermarkt valuations
AU - Gergely Csurilla
AU - László Csató
PY - 2026
DA - 2026/09/18
PB - arXiv
DO - 10.48550/arxiv.2609.21674
UR - https://arxiv.org/abs/2609.21674
AB - The pre-season strengths of European football clubs are usually measured by two proxies in the literature. Football Club Elo Ratings provide strictly performance-based Elo ratings from the early days of the European Cups, while Transfermarkt valuations are crowd-based estimates of squad market values. This paper compares them by evaluating their ability to forecast the results of matches played in the UEFA Champions League and the UEFA Europa League between the seasons 2020/21 and 2024/25. The two indicators yield almost identical out-of-sample accuracy when used separately. Combining the two measures leads to a modest improvement, but the best aggregation procedure is sensitive to the forecast target. Our results suggest that seeding based on Elo ratings would be (closely) optimal.
ER -