WITHDRAWN Efficiency of live betting markets in tennis

Music City Center 

Tennis, traditionally relies on coach observations and pre-match analysis for player development and performance prediction. While sports analytics has revolutionised many aspects of the game, in-game betting strategies remain largely unexplored. This article attempts to fill the gap in the extant literature, by proposing a novel Markov Decision Process (MDP) framework that provides real-time betting recommendations during a match. The proposed model assesses the evolving match dynamics and generates recommendations for the bettor after every game of a tennis match. These recommendations include:
a) Bet/No-Bet Decision: Advising whether to place a bet on any player or abstain.
b) Optimal Betting Fraction: Determining the optimal proportion of the available betting capital to allocate to the bet.
Unlike pre-game strategies based on rankings, this approach adapts to in-game dynamics. Tested on WTA matches, the MDP-based model outperforms traditional betting strategies, demonstrating its potential for optimising in-game tennis betting. Robustness checks are done to establish that the method works well across various scenarios.

OR is sports

Markov decision process

Betting in tennis

In-game forecasting 

Section on Statistics in Sports