UEFA EURO 2020 Forecast via Nested Zero-Inflated Generalized Poisson Regression
This report is devoted to the forecast of the UEFA EURO 2020, Europe's continental football championship, taking place across Europe in June/July 2021. We present the simulation results for this tournament, where the simulations are based on a zero-inflated generalized Poisson regression model...
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| creator | Gilch, Lorenz A |
| description | This report is devoted to the forecast of the UEFA EURO 2020, Europe's
continental football championship, taking place across Europe in June/July
2021. We present the simulation results for this tournament, where the
simulations are based on a zero-inflated generalized Poisson regression model
that includes the Elo points of the participating teams and the location of the
matches as covariates and incorporates differences of team-specific skills. The
proposed model allows predictions in terms of probabilities in order to
quantify the chances for each team to reach a certain stage of the tournament.
We use Monte Carlo simulations for estimating the outcome of each single match
of the tournament, from which we are able to simulate the whole tournament
itself. The model is fitted on all football games of the participating teams
since 2014 weighted by date and importance. |
| doi_str_mv | 10.48550/arxiv.2106.05174 |
| format | Article |
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continental football championship, taking place across Europe in June/July
2021. We present the simulation results for this tournament, where the
simulations are based on a zero-inflated generalized Poisson regression model
that includes the Elo points of the participating teams and the location of the
matches as covariates and incorporates differences of team-specific skills. The
proposed model allows predictions in terms of probabilities in order to
quantify the chances for each team to reach a certain stage of the tournament.
We use Monte Carlo simulations for estimating the outcome of each single match
of the tournament, from which we are able to simulate the whole tournament
itself. The model is fitted on all football games of the participating teams
since 2014 weighted by date and importance.</description><identifier>DOI: 10.48550/arxiv.2106.05174</identifier><language>eng</language><subject>Statistics - Applications</subject><creationdate>2021-06</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,781,886</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2106.05174$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2106.05174$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Gilch, Lorenz A</creatorcontrib><title>UEFA EURO 2020 Forecast via Nested Zero-Inflated Generalized Poisson Regression</title><description>This report is devoted to the forecast of the UEFA EURO 2020, Europe's
continental football championship, taking place across Europe in June/July
2021. We present the simulation results for this tournament, where the
simulations are based on a zero-inflated generalized Poisson regression model
that includes the Elo points of the participating teams and the location of the
matches as covariates and incorporates differences of team-specific skills. The
proposed model allows predictions in terms of probabilities in order to
quantify the chances for each team to reach a certain stage of the tournament.
We use Monte Carlo simulations for estimating the outcome of each single match
of the tournament, from which we are able to simulate the whole tournament
itself. The model is fitted on all football games of the participating teams
since 2014 weighted by date and importance.</description><subject>Statistics - Applications</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj81OwkAUhWfjwoAP4Mp5gdY7_-2SkBZJiDUENm6aS-eWTFJbM0OI-vQCujrnfIuTfIw9Csh1YQw8Y_wK51wKsDkY4fQ9a_ZVveDVfttwCRJ4PUXqMJ34OSB_pXQiz98pTtl67Ae8rhWNFHEIP5f-NoWUppFv6RgppTCNc3bX45Do4T9nbFdXu-VLtmlW6-Vik6F1OsPOm4MoC5Id9s5Zhb06aGdLEF5YXXoNRWktFRKsKixo4_vS04UAgtVGzdjT3-3NqP2M4QPjd3s1a29m6hc-MUal</recordid><startdate>20210609</startdate><enddate>20210609</enddate><creator>Gilch, Lorenz A</creator><scope>EPD</scope><scope>GOX</scope></search><sort><creationdate>20210609</creationdate><title>UEFA EURO 2020 Forecast via Nested Zero-Inflated Generalized Poisson Regression</title><author>Gilch, Lorenz A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a674-acd5b198e2caf7763af3b476901d1649d408966e8206386045df9de66e0a06453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Statistics - Applications</topic><toplevel>online_resources</toplevel><creatorcontrib>Gilch, Lorenz A</creatorcontrib><collection>arXiv Statistics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gilch, Lorenz A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>UEFA EURO 2020 Forecast via Nested Zero-Inflated Generalized Poisson Regression</atitle><date>2021-06-09</date><risdate>2021</risdate><abstract>This report is devoted to the forecast of the UEFA EURO 2020, Europe's
continental football championship, taking place across Europe in June/July
2021. We present the simulation results for this tournament, where the
simulations are based on a zero-inflated generalized Poisson regression model
that includes the Elo points of the participating teams and the location of the
matches as covariates and incorporates differences of team-specific skills. The
proposed model allows predictions in terms of probabilities in order to
quantify the chances for each team to reach a certain stage of the tournament.
We use Monte Carlo simulations for estimating the outcome of each single match
of the tournament, from which we are able to simulate the whole tournament
itself. The model is fitted on all football games of the participating teams
since 2014 weighted by date and importance.</abstract><doi>10.48550/arxiv.2106.05174</doi><oa>free_for_read</oa></addata></record> |
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| title | UEFA EURO 2020 Forecast via Nested Zero-Inflated Generalized Poisson Regression |
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