Stochastic Programming and Optimization in Horserace Betting

William T. Ziemba

Chapter 19 in Sports Analytics, 2022, pp 303-335 from World Scientific Publishing Co. Pte. Ltd.

Abstract: This chapter discusses the stochastic optimization approach to racetrack betting pioneered by the author with the help of Donald Hausch and Mark Rubinstein and used by the professional syndicate teams in Hong Kong, the US and elsewhere. The ideas are from financial theory and portfolio theory applications. One prices the bets and then wagers intelligently on the good ones. I discuss key topics such as the importance of good mean estimates, the favorite-longshot bias, various wagers such as place and show, and the Pick 2, 3, 4, 5 and 6.

Keywords: Sports Analytics; Statistical Analysis of Sports Decisions; NFL Football; Thoroughbred Racing; Basketball; Baseball; Hockey; Jai Alai; Optimal Betting Strategies; Mean Reversion Risk; Arbitrage; Decision Strategies by Coaches (search for similar items in EconPapers)
JEL-codes: C1 L83 Z2 (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.worldscientific.com/doi/pdf/10.1142/9789811250217_0019 (application/pdf)
https://www.worldscientific.com/doi/abs/10.1142/9789811250217_0019 (text/html)
Ebook Access is available upon purchase.

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:wsi:wschap:9789811250217_0019

Ordering information: This item can be ordered from

Access Statistics for this chapter

More chapters in World Scientific Book Chapters from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().