Are Sports Betting Markets Efficient?
Sports betting and financial markets have a lot in common. The wisdom of the crowd is setting prices and the markets are highly efficient, making it difficult to outperform.
In economic terms, a market in which it is difficult to persistently exploit mispricings after the expenses of the effort is called “efficient.” Markets are made efficient by the “wisdom of crowds.” As James Surowiecki demonstrated in his book, The Wisdom of Crowds, the evidence from many fields is that under the right circumstances, large groups of people are collectively smarter than individual experts when it comes to problem-solving, decision-making, innovating and predicting. The four requirements of wise crowds are (1) diversity of opinion, (2) independence of members from one another, (3) decentralization and (4) a good method for aggregating opinions.
An overwhelming body of evidence supports the view that while the financial markets are not perfectly efficient, they are highly efficient, with fewer active managers able to generate statistically significant alphas than would be randomly expected. The annual S&P Active Versus Passive Scorecard has been demonstrating this for almost 20 years. The reason is that the four requirements for the wisdom of crowds to prevail exist in financial markets.
Financial markets are not the only ones that are highly efficient. Betting markets have long been viewed as a testing ground for Eugene Fama’s efficient market hypothesis (EMH). Testing the EMH is more straightforward in betting markets than in typical financial markets because there is a fixed time when a bet’s value is revealed, i.e., when an event ends. Because most of us don’t know anyone who has become rich betting on sports, we know intuitively that sports betting markets are efficient. However, intuition is often incorrect. It helps to have evidence supporting your intuition. Before we look at the evidence, however, we need a definition.
Point spreads and random errors
An “unbiased estimator” is a statistic that is, on average, neither too high nor too low. The method of estimation does not always produce estimates that correspond to reality, but errors in either direction are equally likely. It turns out that the point spread is an unbiased estimate of the outcome of sporting events – while it is not expected to be correct in every instance, when it is incorrect the errors are randomly distributed with a zero mean.