Altitude, Attitude & Denver's Home Field Advantage

With NFL teams scrambling for playoff positioning -- sports analysts have been talking about the Broncos and Seahawks trying to clinch home field advantage -- as they march towards to the Super Bowl.  Most sports fans know that home teams have a home field advantage.  But how much of an edge is home field?  We took a look at statistics over several decades worth of data:

• In the NFL, home teams win 57.3% of the time.
• In MLB, home teams win 53.9% of the time.
• In the NBA, home teams win 60.5% of the time.  

Success at home can be attributed to the impact of the crowd, getting favorable calls from officials (related impact of crowds and peer pressure) -- and the players being in familiar surroundings.  This could include idiosyncrasies of the playing field -- or merely being in the comfort of their homes (and less travel).  

Home Field Advantage for Individual Teams: Denver

To study home field advantage for individual teams -- and to adjust for stronger and weaker teams -- we compare team records at home versus their records away.  Over the longer-term time-frame, we see that:

• NFL teams win 57.3% of the time at home, thus winning 42.7% on the road -- for a 14.6% difference.  
• Similarly, we see that the difference for baseball is 53.9% - 46.1% = 7.8%, and 
• For the NBA: 60.5% - 39.5% = 21.0%.  

When you add high altitude to the mix, it is clear that teams that are based in Denver may have a significant advantage over their opponents.   ...   The Rockies, the Nuggets and the Broncos all have strong records at home. Over the past decade, the Colorado-based teams have combined for one of the best home-field advantages of all major professional sports.

In the NBA, the Nuggets are about 30% better than the league average for home-field advantage (+27.6% home-field edge). In baseball, the Rockies almost double the league home-field advantage at +13.8%. Interestingly, the Broncos are only about average in terms of home-field advantage, at +12.5% over the past decade - although previously, the Broncos home-field advantage was notably strong.

Over the past decade, the Rockies and Nuggets have consistently placed at the top of their respective leagues in terms of home-field advantage, and in total the Colorado-based teams can boast "attitude at home," in addition to the "altitude advantage."

Read more here: http://EzineArticles.com/8211155

Seattle Seahawks: Noise

In recent years, the Seattle Seahawks have had one of the largest home field advantages in the NFL.  This has been attributed to the noise levels of their home crowds, exacerbated by their stadium, which seems to funnel the noise levels.

The noise routinely wreaks havoc on opposing offenses as quarterbacks struggle to call plays or audible at the line scrimmage without the use of non-verbal communication. Offenses are often baited into false-start and delay-of-game penalties due to the noise at CenturyLink.

Read more here:
http://www.nola.com/saints/index.ssf/2013/11/extreme_decibel_levels_give_th.html


Home Field Advantage and Confidence

No matter what NFL playoff teams clinch home field advantage, they will have a decided edge.  And -- home field advantage for the Broncos and Seahawks can go a long way in determining this year's Super Bowl participants.

Home field advantage for these teams are related to attitude, confidence and mental toughness -- concepts of sports psychology that can improve teams' chances of winning games and winning championships.


Please visit our "Who Will Win" blog for a Monte Carlo simulation of the college football BCS game. 

Congrats to Red Sox; Quant Facts now 36-22 (62.1%)

Congratulations to the Boston Red Sox, who have now won three World Series in the past ten years!   Although our quant facts article in the New York Times gave the edge to the underdog St. Louis Cardinals, several people (including co-author Jay Granat) pointed out the emotional high and mental toughness related to "Boston Strong."  That factor is hard to measure, but certainly helped with the Red Sox drive to the championship.

I (Carlton) was torn with my loyalties in this World Series, because our article pointed to the Cardinals, but my heart was with the Red Sox, having been up in Boston (well, in Cambridge) during my college years.  At least in spirit, I was with my friends up in New England, at "Little Fenway."  :)

Red Sox fans might like some of these pictures and the party at Little Fenway.

http://www.burlingtonfreepress.com/article/20131030/NEWS02/310300022/Chills-thrills-Little-Fenway?gcheck=1

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Congrats also to the St. Louis Cardinals, who had a great season; the Cards have won two World Series in the past ten years.

Our quant fact predictions now stand at 36-22, or 62.1% -- using sports psychology factors that are often overlooked by sports analysts.  This is a decent result, because we sometimes go against the grain and pick underdogs (like this year's World Series).


Carlton Chin, CFA, enjoys applying quantitative techniques to study everything from sports analytics to the financial markets and asset allocation.  His work has been used by sports organizations, institutional investors and college universities.  Dr. Jay Granat is a psychotherapist and founder of StayInTheZone.com.  Dr. Granat works with athletes of all levels, from high school athletes up to Olympic gold medalists, and has been named one of America's Top 10 Mental Gurus.  

Who Will Win the 2013 World Series

Here is our analysis for this year's World Series, published in the New York Times.  

 In particular, our work relates key statistical factors to concepts of sports psychology like leadership, consistency and minimizing errors. Based on this research, we focused on factors that might help predict the winner of the World Series between the Boston Red Sox and the St. Louis Cardinals, which begins Wednesday night.


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 tournament, the N.B.A. finals and theN.H.L. Stanley Cup finals.



The sports psychology factors point to the St. Louis Cardinals, even though the Boston Red Sox are a slight favorite.  The Cardinals will count in our official "quant fact" predictions.  

Read more here: 
http://bats.blogs.nytimes.com/2013/10/23/keeping-score-statistics-to-watch-at-the-world-series/

Quant Facts now 36-21 (63.2%)

With the tennis U.S. Open predictions completed, our "quant fact" sports predictions are now 36-21, for a 63.2% winning percentage.   Our U.S. Open predictions were based on the application of Monte Carlo techniques applied to each player's ability to hold and break serve, as mentioned in our New York Times article.

The tennis model built on other Monte Carlo research for New York Times football and basketball articles -- and other projects.  In addition to the Monte Carlo tennis research, we recently applied methods used by sabermetricians to baseball and other sports -- to an in-depth study of the all-time tennis greats (discussed briefly, here).

Our quant fact predictions are based on statistical and quantitative models that study factors related to sports psychology, where possible.  We sometimes key in on factors that sports analysts may undervalue -- so we sometimes find value on the underdog.  Thus, a 63% winning percentage is respectable, considering that we sometimes go against the grain (like we did, incorrectly, in the Nadal- Djokovic U.S. Open Final).


Carlton Chin is a portfolio strategist and fund manager.  An MIT-trained "quant," Carlton likes to apply statistical and probabilistic models to the financial markets, portfolio construction, and sports.  
Dr. Jay Granat is a psychotherapist and has worked with athletes of all levels.  Jay is the founder of StayInTheZone.com.    

Djokovic Celebrates 100 Weeks at #1

Novak Djokovic maintained his number one ranking in the world -- and recently joined eight other all-time greats, with over 100 weeks as the number 1 men's tennis player in the world (since the ATP computed rankings).

1. Federer (302 weeks)
2. Sampras (286)
3. Lendl (270)
4. Connors (268)
5. McEnroe (170)
6. Borg (109)
7. Nadal (102)
8. Agassi (100)

October includes two major tennis tournaments that will decide this year's number one player.  In addition, the article below discusses the intricacies of the ATP rating and ranking system -- and how Rafael Nadal is hot on the trail of Novak Djokovic for the number one ranking.  

Please read more here:

http://www.atpworldtour.com/News/Tennis/2013/09/38/Djokovic-100-Weeks-At-No-1.aspx

2013 US Open Men's Final - Nadal vs. Djokovic

Based on our Monte Carlo simulations, we made a quant fact prediction for the women's champion early in the tournament, that turned out to be correct.  Congratulations to Serena Williams, as well as Victoria Azarenka, who made it a much tougher match than many predicted.  Azarenka is a worthy opponent -- and former number one player in the world, and at age 24, looks like she is poised to regain the top ranking in the world as Serena Williams gets further into her thirties.

On the men's side, our quant fact predictions (based on our Monte Carlo analysis) picks Djokovic in a very close match.  We are looking forward to a great match!  The final is a match-up between:

• ... a red-hot Nadal, who is the favorite based on oddsmakers -- and has been broken only once during the U.S. Open -- against... 
• Djokovic, who has been number one since his fantastic year in 2011 -- and maintains the best return game on hard courts this season.
• In many ways, this is a match between momentum (Nadal has been red-not!) against intermediate-term statistics and rankings (Djokovic maintains the best raw statistics, especially based on his return game).  
• In much of our research, momentum is sometimes overvalued, so our quant fact prediction is on Djokovic.    

We will update the record of our quant fact predictions after the U.S. Open.  

U.S. Open - Men's Quarterfinals

As a follow-up to our Monte Carlo analysis to the women's quarterfinals published in the New York Times yesterday, here is an analysis of the men's quarterfinals.  The research was performed by Carlton Chin, a portfolio strategist and fund manager, and Rose Wang, head of finance at a health care non-profit.  


Monte Carlo Model: Probability of Winning the U.S. Open

1. Novak Djokovic (1) 45.8%
2. Rafael Nadal (2) 25.8%
3. Andy Murray (3) 12.7%
4. David Ferrer (4) 6.6%
5. Richard Gasquet (8) 5.0%
6. Tommy Robredo (19) 1.9%
7. Stanislas Wawrinka (9) 1.8%
8. Mikhail Youzhny (21) 0.5%

The Monte Carlo model gives Novak Djokovic an edge over Rafael Nadal and Andy Murray. In addition, Djokovic has the easiest quarterfinal matchup of the three top seeds, at least statistically.


Read more here:
http://straightsets.blogs.nytimes.com/2013/09/04/keeping-score-monte-carlo-analysis-of-mens-draw/?_r=0

The U.S. Open (Women's Quarterfinals) and Monte Carlo Simulations

Below is an excerpt of quantitative analysis performed for this year's tennis U.S. Open, picked up by the New York Times.   The piece is entitled, "Using the Monte Carlo Method in Tennis" and is by Carlton Chin, a portfolio strategist and fund manager, and Rose Wang, head of finance for a health care non-profit.  

A Monte Carlo analysis uses a random process to assess a complicated problem. In the financial world, Monte Carlo methods can help study the risk of investment strategies or to evaluate derivatives. Sporting events can also show the power of Monte Carlo simulations because sports can be broken down into specific events like an at-bat in baseball, or a possession in football or basketball.

Tennis can be deconstructed into actions like holding serve and breaking serve. The game can be broken down further by analyzing statistics like first-serve percentage and the percentage of points won on first serve or second serve.

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1. Serena Williams (1) 62.3%
2. Victoria Azarenka (2) 16.2%
3. Li Na (5) 10.8%
4. Roberta Vinci (10) 6.4%
5. Ana Ivanovic (13) 1.6%
6. Ekaterina Makarova (24) 1.2%
7. Carla Suarez Navarro (18) 0.8%
8. Flavia Pennetta 0.5%
9. Daniela Hantuchova 0.2%


The piece has Serena Williams as a favorite to win another Grand Slam, and is an official quant fact prediction for the book's blog.

Read more here:
http://straightsets.blogs.nytimes.com/2013/09/03/keeping-score-using-the-monte-carlo-method-in-tennis/?_r=0#more-34506

Tennis Tips - Granat article

In one of his recent weekly columns for NorthJersey.com, "Who Will Win" co-author lists eleven tennis tips based on an interview with a tennis pro.  Here are some of those tips:

• Many players need to shorten their backswing. A compact swing can reduce errors.
• Players tend to not use their legs enough on their strokes. They play primarily with their arms. Macci suggests that players bend their knees as if they are about to sit in a chair and then push down and drive.
• Players can get too excited on a volley and they tend to take a too large of a backswing on their volley. Remain calm at the net and use a short compact motion.
• Weekend warriors abbreviate their follow through because they are afraid of hitting the ball out. They decelerate and stop the racket. Make a fluid full swing.
• Many players do not toss the ball high enough on their serve. Macci reminds players that the service motion is a lot like throwing a javelin. You want to hit up and out at the ball. You need a high toss to do this well.

Please read more here:
http://www.northjersey.com/community/family/reflections/215942991_Top_tennis_pro_reveals_11_common_mistakes_in_tennis.html?page=all

Please vote in our POLL to the left.

Or Click Here.

Quant Fact Predictions now 35-20 (63.6%)

With our predictions for both the Stanley Cup Finals and NBA Finals correct, our quant fact predictions improve to 35-20, or 63.6%.  Our work shows the power of quantifying concepts related to sports psychology.  Sometimes our championship factors agree with the general consensus, but sometimes we pick against generally-accepted favorites.  As one of our readers said, "I'll take 65% all day long!"

The factors we focus on are more easily coached -- and can help improve results.  These include a focus on the fundamentals, minimizing errors, and methods to improve confidence.  

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Stay tuned for our work focusing on baseball pitching -- 

and how pitchers can improve their results.  

Please vote in our POLL to the left.
Or Click Here.

Who Will Win author quoted in NY Observer

The New York Observer had a fun article on home run trots, tracked by Tater Trot Tracker.  If you're interested in how long it takes for your favorite batters to round the bases on a home run, check it out.

Some tidbits:

• David Ortiz & Todd Helton are slow on their home run trots (around 30 seconds).
• Adam Rosales, Carlos Gomez, Yasiel Puiz and Angel Pagan are fast (around 17-19 seconds).

Granat was quoted in the article, saying that personality traits and how athletes play the game can be mirrored in their home run trots.  

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Please vote in our POLL on the lefthand side!  Thank you!  

***

Read more here:

http://observer.com/2013/07/going-yard-breaking-down-all-of-2013s-long-balls-with-tater-trot-tracker/ 

Andy Murray takes Wimbledon!

Less than a year ago, we had a popular post on our blog about Andy Murray's win at the U.S. Open -- and his relationship with new coach, Ivan Lendl.  The blog post talks about their relationship, Lendl's history -- and tennis tactics.

At the time, it appeared that Andy Murray had "gotten over the hump" -- and that perhaps the added confidence could take him to other Grand Slam titles.  Fast forward nine months -- and that is, indeed, the case.  This past week, Murray continued the stretch of confidence that has now brought him the Wimbledon crown -- and perhaps will challenge for the #1 spot in the tennis world.

Andy Murray's story is great for sports psychology and persistence -- and in particular, the power of:

• Confidence,
• Mental toughness, and
• Coaching.

Sports & Tennis fans: please complete our poll on the left-hand-side!

MacroSports Conference - July 6-7, 2013

If you are in Las Vegas -- or would like to head there -- for the July 4th weekend, check out:

MacroSports Conference 

A Conference on Macroeconomics and Sports Analytics.

 

Several big names are scheduled to speak -- including Nate Silver, as well as some big names in the poker world.  Check it out:

http://macrosports.co/schedule/

http://macrosports.co/speakers/.

2013 Stanley Cup Finals (NY Times)

Here's an excerpt from our analysis in the New York Times.  

 Based on this research, we focused on several championship characteristics that might predict the winner of this year’s Stanley Cup finals.  We also applied a Monte Carlo simulation to compute series probabilities for the finals.

In particular, we focused on factors related to sports psychology like big game experience, leadership and consistency. These concepts have proven to be common themes across all sports we have studied.

Big Game Experience: Across all sports, we have found a meaningful relationship between big game experience and winning championships.  In our work, big game experience is measured by appearances in finals over the past three years. In the N.H.L., the team with an edge in this area has gone 11-2 (84.6 percent) in Stanley Cup finals series over the past 33 years.  Both the Blackhawks and Bruins have made finals appearances over the past three years. Edge: Even

Read the complete article here:
http://slapshot.blogs.nytimes.com/2013/06/12/keeping-score-which-statistics-show-path-to-the-cup/ 

Who Will Win the 2013 NBA Finals?

Here's an excerpt from our analysis that was published in the New York Times.  Please click on the link below for the entire article.

Based on this research, we focused on several championship characteristics that might help predict the winner of the N.B.A. finals. We also applied a Monte Carlo simulation similar to methods used in our previous articles to compute series probabilities for the NBA finals between the Miami Heat and the San Antonio Spurs.

Big Game Experience: Over the past 23 years, the team with more finals appearances over the previous three years has 12 of 15 (80.0%) in N.B.A. finals. The Miami Heat are in their third consecutive finals, winning the title last year. Edge: Miami.

...We ran a Monte Carlo simulation based on our factors and the home-away schedule for this year’s N.B.A. finals. The simulation says that Miami has a 71.2 percent chance of winning, with the following probabilities:

Please click below for the probabilities and the whole article.  

http://offthedribble.blogs.nytimes.com/2013/06/06/keeping-score-key-statistics-favor-heat/

Quant Fact Predictions now 33-20 (62.3%)

After a slow start, Louisville won a relatively close game.  Our quant fact prediction for the NCAA Men's Basketball national championship game selected Louisville to win -- albeit in a close game.  This makes our quant fact predictions correct 62.3% of the time (33-20) -- since we started the book's blog several years ago.


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

Carlton and Jay are particularly interested in factors related to sports psychology -- traits that can be more readily coached and practiced.  Our research has shown that these traits can help sports organizations improve performance -- and win championships.  

NCAA Men's Basketball Championship Game (2013)

Below is an excerpt from our article in the NY Times, based on quant research of factors related to sports psychology, 

...we focused on factors that might help predict the winner of the N.C.A.A. tournament championship game between Louisville and Michigan. Last year’s article correctly selected Kentucky to win the national title.

With an eye toward key concepts of sport psychology, we looked at factors like big-game experience, leadership behind the bench, leadership on the court, error control and consistency. 

Consistency:  The team with the higher 3-point shooting percentage has won 11 of the last 14 title games.  Free-throw shooting percentage is also a measure of consistency, and teams with the higher free0throw percentage have gone 10-4 over the past 14 championship games.

In the table below, we list the performance of the Final Four teams in consistency categories like 3-point shooting and free-throw percentage.  We also included turnovers and a defensive measure because these are also championship traits.

	Louisville	Michigan
3-pt shooting%	32.9%	38.3%
Free-throw %	70.7%	70.0%
Turnovers per game	12.5	9.4
FG shooting defense	39.2%	42.3%

Who Will Win the Big Game?  Louisville has more championship factors in its favor, by a narrow 4-3 margin.  Based on our championship factors and season statistics, we developed a Monte Carlo simulator for college basketball, similar to the methodology we used for our football analyses.  The most frequently-occurring score was  Louisville 70, Michigan 69.

Read more here:

http://thequad.blogs.nytimes.com/2013/04/08/keeping-score-which-team-has-the-stats-of-a-champion/#more-46404

Quant Facts now 61.5% (32-20)

Our methods continue to perform particularly well in March Madness, with our quant facts correctly predicting the winners of both semifinal games of the Final Four.  Our Monte Carlo simulations also performed well, with predictions relatively close to the actual final scores.

Our model predicted a Louisville win of 69-62 (Louisville wins by 7), with the actual final score being 72-68 (Louisville by 4).  Similarly, our Monte Carlo simulations predicted Michigan to win by a score of 69-66 (Michigan by 3).  The actual final score was Michigan 61-56 (Michigan by 5).

Stay tuned for our analysis of the National Championship game on Monday.   

2013 Final Four (March Madness)

Based on quant research of factors related to sports psychology, we focused on several championship characteristics that might help predict the winner of the NCAA Men’s Basketball Tournament.  Last year’s article correctly selected Kentucky to win the national title.  

Consistency: Research has shown that consistency and error measures are also important to winning championships.  The team with the higher 3-point shooting percentage has won 11 of the last 14 title games.  Free throw shooting percentage is also a measure of consistency, and teams with the higher free throw percentage have gone 10-4 over the past 14 championship games. 

In the table below, we list the performance of the Final Four teams in consistency categories such as 3-point shooting and free-throw percentage.  We also include experience and leadership factors we discussed – as well as turnovers and a defensive measure, because these are also championship traits.

Who Will Win the Big Game?  Louisville has more championship factors in its favor than Wichita State, including big game experience and coaching leadership.  Wichita State has three-point shooting in its favor – while two factors (FG Shooting Defense and Turnovers per game) are very close.  In the other semifinal matchup, Michigan has more championship factors in its favor.  

Syracuse has coaching leadership and defense in its favor, but the other factors point to Michigan.

Based on our championship factors and season statistics, we developed a Monte Carlo simulator for college basketball, similar to the methodology we used for our football analyses.  The results for the simulations are centered around:  Louisville 69 – Wichita State 62 in the first semifinal game, and Michigan 69 – Syracuse 66 in the second semifinal game. 

Read more here:

http://seekingalpha.com/instablog/677712-carlton-chin/1728391-final-four-factors-march-madness-2013

March Madness Results by Seed for "Round 2"

Now that the field of 64 is all set, we wanted to take a look at how the seeds performed in Round 2, as it is now called.  We computed the results last year, here.

This year, this work was done for us.  Here are the results for the Seeds in Round 2 through last year's tournament.  

Seed	Wins	Losses	Win %
1	112	0	100%
2	106	6	95%
3	96	16	86%
4	89	23	79%
5	74	38	66%
6	74	38	66%
7	67	45	60%
8	54	58	48%
9	58	54	52%
10	45	67	40%
11	38	74	34%
12	38	74	34%
13	23	89	21%
14	16	96	14%
15	6	106	5%
16	0	112	0%

Read more here:
http://www.sportsquants.com/2013/03/20/march-madness-1-results-seed/

Quant Facts 30-20 (2/8/13)

The Super Bowl between San Francisco and Baltimore was truly an exciting game -- and we saw that the results of sporting events can turn on numerous events.  This game included everything from big plays and turnovers -- to power outages and momentum changes!

The power outage created a huge momentum swing, with the delay of greater than 30 minutes -- soon after Baltimore's huge kickoff return for a TD -- allowing San Francisco to compose themselves and get back in the game.  The 49ers actually looked like they would win the game, with a winning TD only 5 yards away, as time ticked down.  However, Baltimore's goal line stand won the Ravens a championship.

Our quant fact predictions are now 30-20 (60%) -- showing the power of sports psychology and quantitative analysis.  

Super Bowl Sims and Championship Characteristics - 2013

Here is an excerpt from our analysis and numerical simulations of this year's Super Bowl, between San Francisco and Baltimore, which is published in the New York Times.  Our quant facts have been correct more than 60% of the time.

Consistency: Ball control remains one of the more important offensive indicators studied in both professional and college football. The team with a better running game, as measured by average yards per rush, has won 57.8 percent of the Super Bowls. The 49ers averaged 5.1 yards per rush this season, compared to 4.3 for the Ravens. Edge: San Francisco.

Monte Carlo Simulations: Probabilistic models like Monte Carlo techniques can be used to solve complicated problems. Similar to our analysis for the B.C.S. national title game between Alabama and Notre Dame, we used regular-season statistics in combination with our championship factors to simulate thousands of football games between San Francisco and Baltimore.

Read more here:
http://fifthdown.blogs.nytimes.com/2013/02/02/keeping-score-what-stats-and-simulations-say-about-the-super-bowl/ 

In addition, our popular analysis of Super Bowl Square Odds -- by Quarter -- is published here:
http://ireport.cnn.com/docs/DOC-917541

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:

http://fifthdown.blogs.nytimes.com/2010/02/07/how-to-spot-a-winner-in-a-squares-pool/

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:

http://ireport.cnn.com/docs/DOC-917541

Selected Books

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.  

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:

http://thequad.blogs.nytimes.com/2013/01/07/keeping-score-characteristics-of-a-champion/#more-44985

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 tournament, the N.B.A. finals and the Super Bowl.