Nov
13
Ivy League Basketball: An Example of Market Evolution, by Nicholas Marchitto
November 13, 2006 | Leave a Comment
As an undergrad at Yale I entertained two passions-Ivy League athletics (particularly basketball) and markets. The former drew me to nearly every contest in New Haven and its vicinity while the latter compelled me to keep a close eye on game lines and eventually pursue a career in investing. After following Ivy League Basketball for nearly two years and always being cognizant of each game’s spread, I began to find wild inefficiencies in certain contests. My thesis was that because Ivy League Athletics, particularly basketball, were not televised or particularly well covered in the press, the market was relatively inefficient. Having followed the teams for nearly two years and watching each team play in New Haven, I believed that I had a fair amount of differential insight and could take advantage of the inefficiencies offered. For the next two years I played specific contests where I thought the spread to be wildly inaccurate and was successful to the point that I was able to pay for my textbooks in both my Junior and Senior years with my winnings.
After graduation, I decided to revisit my thesis, with the belief that I would continue to bet on contests. However, I noticed that during the 2005-2006 season, spreads seemed to be relatively fair and I was having trouble finding those ridiculous spreads that screamed of opportunity. I attributed this to increasing media coverage of Ivy League contests-particularly television coverage on YES and ESPNU of many Ivy League games. In an effort to test my thesis, I compiled empirical data. Unfortunately, I had a rather limited data set (the last 20 contests of each Ivy League team) and so could not look at the relative efficiency of the market pre-coverage and post-coverage; interestingly, however, the data suggested another opportunity. Eliminating overlapping contests and including contests outside the league, I have 104 observations. Collectively, Ivy League teams won 48.1% of games vs. the spread, roughly in-line with the 50% you would expect in an efficient market. Yet, in — of the observations, the collective score of the game exceeded the Over/Under line (estimate of total number of points to be scored in the game) published prior to the game. This is an important observation, one that leads me to believe that deep-seated biases, particularly the belief that Ivy League affairs are always low-scoring defensive battles, are manifesting themselves in the spread makers over/under decision.
Markets will always evolve, but it is important to remember that the demise of the status quo does not portend a similar fate for opportunity.
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