Tuesday, January 29, 2013

Super Bowl Square Probabilities - updated through 1/29/13

by Carlton Chin, Don La Fronz & Paul Lacher

A few years ago, we took a look at the probabilities of the digits winning at the end of each quarter – based on every Super Bowl ever played.  The results were published by the New York Times, here. Below is the entire link:

This year, we refreshed the results to reflect the NFL’s adoption of the two-point conversion since 1994.  We used every Super Bowl – along with Conference Championship games – since 1994.   Similar to three years ago, we computed the probabilities, or odds, at the end of each quarter.  Our findings include information on which team was favored to win the game.   

So, what numbers are good?  Here are some tidbits:
  • For the team that is favored (San Francisco, this year), the best numbers to have for the final score are: 1, 4, and 7.  These numbers each have a 17.9% chance of hitting, based on our data sample. 
  • The best numbers for the underdog’s final score (Baltimore) are 4, 7 and 0 – in that order.
  • The best overall numbers, to win at the end of any quarter – favorite or underdog – are 0, 7, 4, and 3, in that order. 
  • The 0 and 3 are particularly good to have at the end of the first quarter and first half.
  • By the end of the game, the 4 and 7 are the best.
  • The worst numbers are the 2 and 5, but by the end of the game, every number has won in our sample size, since 1994.  
Note that if there is a 0.0% in a given square, it does not mean that this event is impossible.  It just means that during our sample size, that set of numbers has not occurred for the given quarter.  Please keep an eye out for our “Who Will Win” analysis and Monte Carlo simulation of this year’s Super Bowl. Enjoy the game!

(Please click on the charts to enlarge.)

First Quarter - Probabilities

First Half - Probabilities

Third Quarter - Probabilities

Final Score - Probabilities

Special thanks to Don La Fronz who thought of the idea and helped devise the methodology -- and to Paul Lacher, who helped to put this year's article together.  Carlton has been good friends with Don and Paul for many years.

Don La Fronz is a financial advisor at Pell Wealth Partners.  Paul Lacher is a Wall Street veteran with over 20 years in financial services working with brokerage firms, banks, mutual fund companies and transfer agents.  Born and raised in Brooklyn, NY, Paul is a lifelong sports fan who still counts down the days until pitchers and catchers report for spring training -- and wonders, at times, if the NY Jets will ever win another Super Bowl.  Carlton Chin, CFA, is a managing director at Price Asset Management and principal at Adamah/CARAT Capital, specializing in portfolio strategy, quant research, and alternative investment strategies.

This article and the Final Score chart is also here:

Friday, January 18, 2013

Quant Facts now 30-19 (1/18/13)

With Alabama's victory over Notre Dame in this year's college football's national championship (BCS) game, our quant fact predictions improve to 30-19 (61.2%).  Math, statistics, and probabilities can be powerful tools in knowledge discovery -- and researching methods to optimize the chances of victory and winning championships.

Stay tuned for our upcoming analysis of the Super Bowl.  

Carlton Chin, CFA, is a quantitative researcher and portfolio strategist for Price Asset Management  and Adamah Capital, a hedge fund specializing in alternative assets & Computer Aided Research & Trading (CARAT).  Jay Granat, PhD is a psychotherapist and founder of StayInTheZone.com.  

Jay and Carlton are particularly interested in certain factors that can be coached and practiced.  Their research has shown that these traits can help sports organizations improve performance -- and win championships.  

Monday, January 7, 2013

College Football's 2013 BCS: Alabama vs. Notre Dame

Here is an excerpt from our "Who Will Win?" analysis on the BCS game between Alabama and Notre Dame, that was published by the NY Times.  

We typically apply a quantitative analysis of sports psychology concepts to predict the winner of various sports championships.  In this article, we took this a step further and used quant investment techniques (including probabilistic Monte Carlo methods) to develop a football simulator to take a look at the big game between Alabama and Notre Dame in this year's college football national championship BCS game.

Here is an excerpt from the article in the NY Times.
... our work relates key statistics to sports psychology concepts like leadership, consistency and minimizing errors. We have also developed a football simulator based on a probabilistic Monte Carlo model to use in conjunction with our championship factors. 
Simulation: We developed a football simulator that plays out thousands of games relatively quickly. The simulator is a probabilistic Monte Carlo model that uses statistics and results from the regular season.

... football games can be modeled based on certain random variables, statistics and our championship factors. The final score that came up most frequently on our simulator was Alabama 27, Notre Dame 14. As expected, we got a cloud of widely varying results, but this is the center of the model's probability distribution.
Edge: Alabama

Read more here:

Carlton J. Chin, a portfolio strategist and fund manager, and Jay P. Granat, psychotherapist, are authors of "Who Will Win the Big Game? A Psychological & Mathematical Method." They have previously written about the N.C.A.A. men's basketball tournamentthe N.B.A. finals and the Super Bowl.