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The Betting Odds Rating System: Using soccer forecasts to forecast soccer

Overview of attention for article published in PLOS ONE, June 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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1 news outlet
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26 X users

Citations

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28 Dimensions

Readers on

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82 Mendeley
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Title
The Betting Odds Rating System: Using soccer forecasts to forecast soccer
Published in
PLOS ONE, June 2018
DOI 10.1371/journal.pone.0198668
Pubmed ID
Authors

Fabian Wunderlich, Daniel Memmert

Abstract

Betting odds are frequently found to outperform mathematical models in sports related forecasting tasks, however the factors contributing to betting odds are not fully traceable and in contrast to rating-based forecasts no straightforward measure of team-specific quality is deducible from the betting odds. The present study investigates the approach of combining the methods of mathematical models and the information included in betting odds. A soccer forecasting model based on the well-known ELO rating system and taking advantage of betting odds as a source of information is presented. Data from almost 15.000 soccer matches (seasons 2007/2008 until 2016/2017) are used, including both domestic matches (English Premier League, German Bundesliga, Spanish Primera Division and Italian Serie A) and international matches (UEFA Champions League, UEFA Europe League). The novel betting odds based ELO model is shown to outperform classic ELO models, thus demonstrating that betting odds prior to a match contain more relevant information than the result of the match itself. It is shown how the novel model can help to gain valuable insights into the quality of soccer teams and its development over time, thus having a practical benefit in performance analysis. Moreover, it is argued that network based approaches might help in further improving rating and forecasting methods.

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 21%
Student > Ph. D. Student 13 16%
Researcher 8 10%
Student > Bachelor 8 10%
Student > Doctoral Student 5 6%
Other 8 10%
Unknown 23 28%
Readers by discipline Count As %
Sports and Recreations 17 21%
Computer Science 16 20%
Social Sciences 5 6%
Mathematics 4 5%
Business, Management and Accounting 3 4%
Other 15 18%
Unknown 22 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 33. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 May 2023.
All research outputs
#1,219,563
of 25,722,279 outputs
Outputs from PLOS ONE
#15,400
of 223,918 outputs
Outputs of similar age
#25,858
of 344,153 outputs
Outputs of similar age from PLOS ONE
#289
of 3,257 outputs
Altmetric has tracked 25,722,279 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 223,918 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 344,153 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 3,257 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.