Okay, all you quants, wannabe quants, and sports fans, here’s a book for you! You liked Moneyball? Wayne L. Winston, the John and Esther Reese Professor of Decision Sciences at Indiana University’s Kelley School of Business, takes you farther into the world of sports math. In 51 short chapters he shows how to use statistics to tackle such diverse questions as when it’s wise to bunt, how to compare players from different eras, whether teams and players have “hot streaks,” and whether college basketball games are fixed.
Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football (Princeton University Press, 2009) is also a terrific read for anyone trying to model markets statistically and make trading decisions based on statistical data. Sports, I assume, are easier to model than markets because, among other things, every game has an agreed-upon beginning and end, the number of players is limited and their abilities quantifiable, and each sport is governed by a set of rules. Data don’t keep accumulating 24/7, more randomly than not, with a gazillion players who have different agendas and play by different rules, all bound together in a complex adaptive system. Nonetheless, traders are confronted with the same kinds of decisions as those who call plays for a football team. It’s third and six (this, by the way, was the glum situation in which the Yale football team always seemed to find itself when I was at a game, and it’s has become something of a metaphor around here) and you start the decision tree. Do you pass or run? If you decide to pass, is it a short pass or a long pass, down the middle or to the outside? Who’s the intended receiver? What’s the pattern? I don’t have to go through the drill. The point is, do you wing it or do you base your decision on statistically significant findings? Winston shows the merits of statistically based decisions in a highly structured system.
As readers of my blog should know by now, I’m not a quant. My most notable math achievement was winning a drafting set (which I still have and actually use on occasion) for placing first in a county-wide algebra contest in the ninth grade. It’s not that I stopped my math education in junior high; I just never stunned the world with my mathematical prowess. Nonetheless, I love numbers, I consider spreadsheets a powerful cross between aesthetics and math, and I respect those who can write the endless whiteboard equations that I will never understand. And I think that analogies, though often misleading, can also open paths to opportunities.
Reading Winston’s book is a mind-opening experience. He writes about some topics familiar to investors and traders such as the Kelly criterion and arbitrage opportunities. He explains how gamblers and bookmakers make money. And he shows how to ferret out opportunities and assess their probability of success. For instance, can a bettor make money by exploiting the fact that certain NBA officials influence the total points scored in a game by calling lots of fouls and the Total Line does not adjust for this fact?
Winston has a website that provides Excel files for many of his figures and is a learning experience in itself. (The book gives the wrong url, but it doesn’t take much imagination to discover the correct one.)