Information Cascades and Sports Gambling
The sports gambling industry, and the gambling industry in general, has been performing extremely well over the last few months. The start continuation of some of America’s most watched sports leagues has resulted in a large uptick in American’s gambling. Other catalysts, such as the pandemic, the election, and legislation changes have all been contributing factors to the continuing growth of the gambling industry. With this in mind, I wanted to explore the connection between networks and the gambling world. I was already aware that gambling was solely successful because of predictable mass human behaviour, so I was sure I could relate it to the course.
Sure enough, one article I found discussed the way that people’s behavioral biases, including information cascades, impact the surprisingly consistent gambling trends. For context, sports gambling involves an individual putting money on certain ‘odds’. For example, someone could hypothetically bet 50 dollars to win 100 on an underdog winning a given game. These ‘odds’ work sort of like a market, and are shifted based on what people are betting on. The article describes how ‘informed betting’ tends to happen long before the games. These gamblers are people who tend to be more experienced and have additional information. In otherwards, they are able to follow their strong signals and do well. The article continues by describing how closer to the sport games’ start times, amateur betters simply bet on a team for arbitrary reasons. Perhaps they are more familiar with this team, or have heard of them winning in the past. Regardless, the mass of less informed individuals place their “public money” as the article describes into one of the two teams, so much so that they are able to shift the odds to make a clear favorite. Because people tend to bet for favorites, the bets for the given team start to cascade in. This phenomenon represents an information cascade that is often wrong, or at least uneducated. Overall, the fact that people are willing to give up their personal signals to follow what the majority of people are doing portrays the same behavioral bias represented by classic information cascades. Of course, this real world example is a bit different from the models we observe in class, and there are some inconsistencies. For example, in gambling people aren’t able to directly see what other people are doing, but rather make their decisions based on the betting odds, which generally represent how other people are leaning. Another complication in the real world is that people’s signals are sometimes stronger in one’s mind than the mass’ opinion– things simply aren’t as clean cut.
All in all, I enjoyed reading the gambling portion of the article as it really exemplified a recent portion of the coursework in a straightforward way and introduced me to the nuances of applying these principles to the real world.
Source: https://www.sportstradingnetwork.com/article/wisdom-of-the-crowds-applied-to-betting/