Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer
Ordinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred to a draw and a draw being preferred to a loss...
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| Format: | Article |
| Language: | English |
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Sciendo
2017-07-01
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| Series: | International Journal of Computer Science in Sport |
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| Online Access: | https://doi.org/10.1515/ijcss-2017-0004 |
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| _version_ | 1850060911037906944 |
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| author | Hvattum L. M. |
| author_facet | Hvattum L. M. |
| author_sort | Hvattum L. M. |
| collection | DOAJ |
| description | Ordinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred to a draw and a draw being preferred to a loss. However, the often used ordinal models have an assumption of proportional odds: the influence of an independent variable on the log odds is the same for each outcome. This paper illustrates how ordinal regression models therefore fail to fully utilize independent variables that contain information about the likelihood of matches ending in a draw. However, in practice, this flaw does not seem to have a substantial effect on the predictive accuracy of an ordered logit regression model when compared to a multinomial logistic regression model. |
| format | Article |
| id | doaj-art-78b46b7977a04bfbb230a24e1eb4cc99 |
| institution | DOAJ |
| issn | 1684-4769 |
| language | English |
| publishDate | 2017-07-01 |
| publisher | Sciendo |
| record_format | Article |
| series | International Journal of Computer Science in Sport |
| spelling | doaj-art-78b46b7977a04bfbb230a24e1eb4cc992025-08-20T02:50:26ZengSciendoInternational Journal of Computer Science in Sport1684-47692017-07-01161506410.1515/ijcss-2017-0004Ordinal versus nominal regression models and the problem of correctly predicting draws in soccerHvattum L. M.0Faculty of Logistics, Molde University College, Molde, NorwayOrdinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred to a draw and a draw being preferred to a loss. However, the often used ordinal models have an assumption of proportional odds: the influence of an independent variable on the log odds is the same for each outcome. This paper illustrates how ordinal regression models therefore fail to fully utilize independent variables that contain information about the likelihood of matches ending in a draw. However, in practice, this flaw does not seem to have a substantial effect on the predictive accuracy of an ordered logit regression model when compared to a multinomial logistic regression model.https://doi.org/10.1515/ijcss-2017-0004association footballforecastingordered regression |
| spellingShingle | Hvattum L. M. Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer International Journal of Computer Science in Sport association football forecasting ordered regression |
| title | Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer |
| title_full | Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer |
| title_fullStr | Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer |
| title_full_unstemmed | Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer |
| title_short | Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer |
| title_sort | ordinal versus nominal regression models and the problem of correctly predicting draws in soccer |
| topic | association football forecasting ordered regression |
| url | https://doi.org/10.1515/ijcss-2017-0004 |
| work_keys_str_mv | AT hvattumlm ordinalversusnominalregressionmodelsandtheproblemofcorrectlypredictingdrawsinsoccer |