Probability of winning and match length in Tiebreak Ten tennis

Peter O’Donoghue and Emma Simmonds

International Journal of Performance Analysis in Sport, 2019, vol. 19, issue 3, 402-416

Abstract: New formats of tennis have been developed to make matches more exciting and unpredictable than the traditional format of the game. The purpose of the current investigation was to compare the probability of winning between Tiebreak Ten matches and two other formats of the game; Fast4 tennis and traditional tennis. A probabilistic model of winning Tiebreak Ten tennis matches was created and compared with existing models of Fast4 and traditional tennis matches. This analysis was done for a full range of probabilities of players winning points when they are serving. This involved 100,000 simulations for each pair of probabilities for two players serving for multiple set matches in Fast4 tennis and traditional tennis. The probability of players beating higher ranked opponents was found to be higher in Tiebreak Ten matches than in Fast4 and traditional tennis matches. This confirms the claim that Tiebreak Ten matches are less predictable and hence more exciting than Fast4 and traditional tennis matches.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/24748668.2019.1615296 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rpanxx:v:19:y:2019:i:3:p:402-416

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RPAN20

DOI: 10.1080/24748668.2019.1615296

Access Statistics for this article

International Journal of Performance Analysis in Sport is currently edited by Peter O'Donoghue

More articles in International Journal of Performance Analysis in Sport from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().