Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In this study, we employ a Monte Carlo simulation technique for estimating the conditional probability of victory at any stage in the first or second innings of a one-day international (ODI) cricket match. This model is then used to test market efficiency in the Betfair ‘in-play’ market for large sample of ODI matches. We find strong evidence of overreaction in the first innings. A trading strategy of betting on the batting team after the fall of a wicket produces a significant profit of 20%. We also find some evidence of underreaction in the second innings although it is less economically and statistically significant than the first innings overreaction. We also implement trades when the discrepancy between the probability of victory implied by current market odds differs substantially from the odds estimated by our Monte Carlo simulation model. We document a number of trading strategies that yield large statistically significant positive returns in both the first and second innings.