IDEAS home Printed from https://ideas.repec.org/p/hig/wpaper/129-ec-2016.html
   My bibliography  Save this paper

Seeding the UEFA Champions League Participants: Evaluation of the Reform

Author

Listed:
  • Dmitry Dagaev

    (National Research University Higher School of Economics)

  • Vladimir Yu. Rudyak

    (National Research University Higher School of Economics)

Abstract

We evaluate the sporting effects of the seeding system reform in the major football club tournament -- the Champions League -- organized by the Union of European Football Associations (UEFA). In the UEFA Champions League, before the 2015-16 season, the teams were seeded in the group stage with respect to their ratings. Starting from the 2015-16 season, national champions of the Top-7 countries are seeded in the first pot, whereas other teams are seeded by their rating as before. We propose a probabilistic model for predicting the score of a single match in UEFA tournaments as well as the whole UEFA season. This model uses clubs' ratings as inputs. Applying Monte-Carlo simulations, we show that the expected rating of the UEFA Champions League winner, as well as the sum of the finalists' ratings, slightly decreased after the reform. At the same time, the difference in the finalists' ratings, which is a measure of competitive balance, increased. The UEFA Europa League became stronger and less balanced. We check the robustness of the results by introducing local fluctuations in the clubs ratings. Also, we study which national associations took advantage of the reform. For seeding rules before and after the reform, we estimate the transition matrix (pij), where pij is the probability of i-th strongest national association moving to j-th position after the season. The effect of reform on a single national association measured by the change in probability to increase or decrease the association's UEFA rank is not more than 3%

Suggested Citation

  • Dmitry Dagaev & Vladimir Yu. Rudyak, 2016. "Seeding the UEFA Champions League Participants: Evaluation of the Reform," HSE Working papers WP BRP 129/EC/2016, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:129/ec/2016
    as

    Download full text from publisher

    File URL: https://www.hse.ru/data/2016/03/24/1127939222/129EC2016.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dominik Schreyer & Sascha L. Schmidt & Benno Torgler, 2018. "Game Outcome Uncertainty in the English Premier League," Journal of Sports Economics, , vol. 19(5), pages 625-644, June.
    2. Scarf, Philip & Yusof, Muhammad Mat & Bilbao, Mark, 2009. "A numerical study of designs for sporting contests," European Journal of Operational Research, Elsevier, vol. 198(1), pages 190-198, October.
    3. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
    4. Dries Goossens & Jeroen Beliën & Frits Spieksma, 2012. "Comparing league formats with respect to match importance in Belgian football," Annals of Operations Research, Springer, vol. 194(1), pages 223-240, April.
    5. Buraimo, Babatunde & Simmons, Rob, 2009. "A tale of two audiences: Spectators, television viewers and outcome uncertainty in Spanish football," Journal of Economics and Business, Elsevier, vol. 61(4), pages 326-338, July.
    6. Jeff Horen & Raymond Riezman, 1985. "Comparing Draws for Single Elimination Tournaments," Operations Research, INFORMS, vol. 33(2), pages 249-262, April.
    7. Koning, Ruud H. & Koolhaas, Michael & Renes, Gusta & Ridder, Geert, 2003. "A simulation model for football championships," European Journal of Operational Research, Elsevier, vol. 148(2), pages 268-276, July.
    8. Jaume García & Plácido Rodríguez, 2002. "The Determinants of Football Match Attendance Revisited," Journal of Sports Economics, , vol. 3(1), pages 18-38, February.
    9. Ryvkin, Dmitry, 2011. "The optimal sorting of players in contests between groups," Games and Economic Behavior, Elsevier, vol. 73(2), pages 564-572.
    10. R. A. Hart & J. Hutton & T. Sharot, 1975. "A Statistical Analysis of Association Football Attendances," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 24(1), pages 17-27, March.
    11. Tim Pawlowski & Georgios Nalbantis & Dennis Coates, 2018. "Perceived Game Uncertainty, Suspense And The Demand For Sport," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 173-192, January.
    12. Siem Jan Koopman & Rutger Lit, 2015. "A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 167-186, January.
    13. M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Corona, Francisco & Forrest, David & Tena, J.D. & Wiper, Michael, 2019. "Bayesian forecasting of UEFA Champions League under alternative seeding regimes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 722-732.
    2. Oliver Engist & Erik Merkus & Felix Schafmeister, 2021. "The Effect of Seeding on Tournament Outcomes: Evidence From a Regression-Discontinuity Design," Journal of Sports Economics, , vol. 22(1), pages 115-136, January.
    3. László Csató, 2020. "The UEFA Champions League seeding is not strategy-proof since the 2015/16 season," Annals of Operations Research, Springer, vol. 292(1), pages 161-169, September.
    4. László Csató, 2020. "Optimal Tournament Design: Lessons From the Men’s Handball Champions League," Journal of Sports Economics, , vol. 21(8), pages 848-868, December.
    5. Csató, László & Petróczy, Dóra Gréta, 2022. "Hogyan számszerűsíthető az ösztönzéskompatibilitás? Esettanulmány a sport világából [Quantifying incentive compatibility: a case study from the world of sports]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 841-852.
    6. Chen Cohen & Ishay Rabi & Aner Sela, 2023. "Optimal seedings in interdependent contests," Annals of Operations Research, Springer, vol. 328(2), pages 1263-1285, September.
    7. L'aszl'o Csat'o & D'ora Gr'eta Petr'oczy, 2020. "Bibliometric indices as a measure of performance and competitive balance in the knockout stage of the UEFA Champions League," Papers 2005.13416, arXiv.org, revised Sep 2023.
    8. Lapré Michael A. & Palazzolo Elizabeth M., 2022. "Quantifying the impact of imbalanced groups in FIFA Women’s World Cup tournaments 1991–2019," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 18(3), pages 187-199, September.
    9. Lapré Michael A. & Palazzolo Elizabeth M., 2023. "The evolution of seeding systems and the impact of imbalanced groups in FIFA Men’s World Cup tournaments 1954–2022," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 19(4), pages 317-332, December.
    10. L'aszl'o Csat'o, 2023. "Club coefficients in the UEFA Champions League: Time for shift to an Elo-based formula," Papers 2304.09078, arXiv.org, revised Oct 2023.
    11. Lunander Anders & Karlsson Niklas, 2023. "Choosing opponents in skiing sprint elimination tournaments," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 19(3), pages 205-221, September.
    12. Csató, László, 2023. "How to avoid uncompetitive games? The importance of tie-breaking rules," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1260-1269.
    13. Girish Ramchandani & Daniel Plumley & Adam Davis & Rob Wilson, 2023. "A Review of Competitive Balance in European Football Leagues before and after Financial Fair Play Regulations," Sustainability, MDPI, vol. 15(5), pages 1-15, February.
    14. Csató, László, 2022. "Quantifying incentive (in)compatibility: A case study from sports," European Journal of Operational Research, Elsevier, vol. 302(2), pages 717-726.
    15. Csató, László & Bodnár, Gergely, 2023. "Mérhetnénk jobban a csapatok erejét a Bajnokok Ligájában? Fontos megjegyzés az Európai Labdarúgó-szövetség számára [How to better measure team strength in the Champions League. An important message," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 813-827.
    16. Csató, László & Petróczy, Dóra Gréta, 2020. "Miért igazságtalan a 2020-as labdarúgó-Európa-bajnokság kvalifikációja? [Why is qualification for the 2020 European association football championship unfair?]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 734-747.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Scarf, Phil & Parma, Rishikesh & McHale, Ian, 2019. "On outcome uncertainty and scoring rates in sport: The case of international rugby union," European Journal of Operational Research, Elsevier, vol. 273(2), pages 721-730.
    2. Dominik Schreyer, 2019. "Football spectator no-show behaviour in the German Bundesliga," Applied Economics, Taylor & Francis Journals, vol. 51(45), pages 4882-4901, September.
    3. Csató, László, 2023. "How to avoid uncompetitive games? The importance of tie-breaking rules," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1260-1269.
    4. László Csató, 2020. "Optimal Tournament Design: Lessons From the Men’s Handball Champions League," Journal of Sports Economics, , vol. 21(8), pages 848-868, December.
    5. Trung Minh Dang & Ross Booth & Robert Brooks & Adi Schnytzer, 2015. "Do TV Viewers Value Uncertainty of Outcome? Evidence from the Australian Football League," The Economic Record, The Economic Society of Australia, vol. 91(295), pages 523-535, December.
    6. Besters, Lucas, 2018. "Economics of professional football," Other publications TiSEM d9e6b9b7-a17b-4665-9cca-1, Tilburg University, School of Economics and Management.
    7. Schreyer, Dominik & Schmidt, Sascha L. & Torgler, Benno, 2016. "Against all odds? Exploring the role of game outcome uncertainty in season ticket holders’ stadium attendance demand," Journal of Economic Psychology, Elsevier, vol. 56(C), pages 192-217.
    8. Dominik Schreyer & Sascha L. Schmidt & Benno Torgler, 2019. "Football Spectator No-Show Behavior," Journal of Sports Economics, , vol. 20(4), pages 580-602, May.
    9. Georgios Nalbantis & Tim Pawlowski & Dominik Schreyer, 2023. "Substitution Effects and the Transnational Demand for European Soccer Telecasts," Journal of Sports Economics, , vol. 24(4), pages 407-442, May.
    10. Corona Francisco & Wiper Michael Peter & Horrillo Juan de Dios Tena, 2017. "On the importance of the probabilistic model in identifying the most decisive games in a tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(1), pages 11-23, March.
    11. Geenens, Gery, 2014. "On the decisiveness of a game in a tournament," European Journal of Operational Research, Elsevier, vol. 232(1), pages 156-168.
    12. Nicholas King & P. Dorian Owen & Rick Audas, 2012. "Playoff Uncertainty, Match Uncertainty and Attendance at Australian National Rugby League Matches," The Economic Record, The Economic Society of Australia, vol. 88(281), pages 262-277, June.
    13. Jiří LahviÄ ka, 2015. "The Impact of Playoffs on Seasonal Uncertainty in the Czech Ice Hockey Extraliga," Journal of Sports Economics, , vol. 16(7), pages 784-801, October.
    14. Uribe, Rodrigo & Buzeta, Cristian & Manzur, Enrique & Alvarez, Isabel, 2021. "Determinants of football TV audience: The straight and ancillary effects of the presence of the local team on the FIFA world cup," Journal of Business Research, Elsevier, vol. 127(C), pages 454-463.
    15. Alexander John Bond & Francesco Addesa, 2020. "Competitive Intensity, Fans’ Expectations, and Match-Day Tickets Sold in the Italian Football Serie A, 2012-2015," Journal of Sports Economics, , vol. 21(1), pages 20-43, January.
    16. Pedro Garcia-del-Barrio & J. James Reade, 2023. "The Impact of Uncertainty on Fan Interest Surrounding Multiple Outcomes in Open European Football Leagues," Economics Discussion Papers em-dp2023-02, Department of Economics, University of Reading.
    17. Dmitry Dagaev & Alex Suzdaltsev, 2015. "Seeding, Competitive Intensity and Quality in Knock-Out Tournaments," HSE Working papers WP BRP 91/EC/2015, National Research University Higher School of Economics.
    18. Jiří LahviÄ ka, 2015. "Using Monte Carlo Simulation to Calculate Match Importance," Journal of Sports Economics, , vol. 16(4), pages 390-409, May.
    19. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
    20. Dominik Schreyer & Sascha L. Schmidt & Benno Torgler, 2018. "Game Outcome Uncertainty in the English Premier League," Journal of Sports Economics, , vol. 19(5), pages 625-644, June.

    More about this item

    Keywords

    tournament; design; seeding; competitive balance; UEFA Champions League; Monte-Carlo simulations;
    All these keywords.

    JEL classification:

    • Z20 - Other Special Topics - - Sports Economics - - - General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hig:wpaper:129/ec/2016. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Shamil Abdulaev or Shamil Abdulaev (email available below). General contact details of provider: https://edirc.repec.org/data/hsecoru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.