Super Bowl 42 NFL Spread Pick

The Super Bowl between the New York Giants and the perfect New England Patriots will be on Feb. 3, 2008 at Arizona. The spread stands at 11 on some websites and up to 12 on others favoring the Patriots. It is a hard bet to place because New England is unbeatable, but in the past 8 games they have only covered the spread once averaging 7 points under the spread. The Giants are 10-0 on the road and they are 7-1 ATS in the past 8 games averaging 6.6 points above the spread. So clearly, the spread has been underrating the Giants offense and overestimating the Patriots' strength. What does that tell us?

Not much, yet. One could argue that, for this game, the spread has adjusted for these biases (leading to a Patriots pick) or that this trend will continue (leading to a Giants pick). Below is a graph of these spread trends for both teams:

To avoid my emotions and trend biases from hurting my Super Bowl pick, I consulted my statistical model as I always do. This model is built in the following way: 1) considers offensive and defensive strength patterns, 2) builds team rankings according to historical scores, 3) adds a home field advantage, 4) creates an unbiased prediction of the spread, and 5) creates a prediction confidence or probability if you will (compares this prediction and the current spread to its performance in the past). A bet or wager (and the amount) is placed depending on the confidence of the prediction. Below is a graph of the offensive strength of these two teams in the past 8 games. It shows the Giants very effective running game and the Patriots #1 passing game:

Super Bowl Pick
For the Super Bowl, the home field advantage was removed, i.e. I subtracted the 2.7 points the model was giving to the home team. The model results are not as opportunistic as I have seen in other situations. Still, there is a slight advantage for the Giants to keep the Patriots close enough from the 11.5 spread we currently have (that would lead me to wager a lesser amount in order to keep my winning returns over 100% for the year, money management mumbo jumbo). The model predicts the game will end with the Patriots winning by 9 points. That is 2.5 points below the spread. For the previous 10 years, this situation (where the spread is more than 9 for a team, but the prediction is 2.5 points less) 57% of the time it has predicted this correctly. The majority is favoring the Giants and the line has dropped significantly. I do not like bets where I side with the majority, but my trading plan does not allow me to go against my predictions.

Below is the table I usually display with picks and past performance:

Giants +11.5
Good luck and go Giants!

Super Bowl Squares

Super Bowl Squares is a well-known party game many of us play with friends and co-workers during the Big Game. Here's a quick explanation: A 10-by-10 matrix (=100 squares) is made with one team on the top and the other is on the side. Each square on the grid is sold. Put the sold tickets in a hat, randomly select a ticket and fill up the squares in order. At the end of the quarter, if the last two digits of the score corresponds to one of your squares you win (usually 1/5 of the pool for a quarter and 2/5 for the final score).

A Variation of the Betting Squares Super Bowl Game
My friends and I like to introduce a bit of skill into this game so that is not completely determined by randomness. We all get together to watch the game. Our names are written in a piece of paper and selected randomly from a hat. One by one the draft order is selected. We then pass around a piece of paper in the order the names were selected (like a fantasy football draft) with the 10x10 grid to pick a non-selected square. Since it is usually 10-15 of us, we only use the lower diagonal of the grid (=50 squares, that makes 0-7 or 7-0 the same square). If it is 10 of us, each one gets to select 5 squares.

Last year, I was not given time to look at my data in order to best select the squares. Everyone would of course pick 7-0 if they had the first pick, but what will you select in your 2nd, 3rd, 4th, and 5th pick in order to maximize your chances of winning? Below I breakdown the frequency percentages for all the final and quarter by quarter football game scores in the past 3 years (all the quarter score data I was able to obtain for free), and for all the 41 Super Bowls prior to this.

Final Scores Breakdown
The frequency on single numbers suggests to stay away from 2-5-9-8 in that order. 8 leading that pack with 6% and 2 is the least seen in the final score with only 3.7%. On the other hand, 0-7-4-3 are all above 14% with 0 and 7 close to 1st place with 17%. That is, in the past 3 years, 17% of the games ended with one of the scores, visiting or home team, with a 7. But I need to pick squares not single number, which ones should I pick?

From the above chart, we see our top 10 would be:
0-3, 0-7, 1-4, 4-7, 0-4, 3-7, 6-7, 0-1,... the only surprise for me here is the number 4. But more useful is to know to stay away from 2-2, 9-5, 9-9 or just have this chart handy when your turn to draft a square in the 3rd round and above.

First Quarter Breakdown
Having a first quarter win is enough to profit from such an activity, so one might just go for the win in the first round. As you will see, some squares are showing much higher frequencies than others. Below is the same grid, but only for first quarter scores. The usual suspects are there, but there is one which stands out much more in first quarter than in the final scores, can you guess which one?Q1 Football Squares Scores

In quarter 2, there is not much difference in the orders except that 7-7 stands out more, the top 10 for the 2nd quarter were: 7-0, 7-3, 3-0, 0-0, 4-7, 7-7, 4-0, 4-3 again also that #4 surprising me.

In quarter 3 there is really nothing significantly different, so when looking for a winner in Q3, look at the final score grid.

Just Super Bowl
Let's look at the percentages for all the 41 previous Super Bowl games. Should there be any difference in these 41 games from the other 289 I looked at? No, but there will be because of the rather small sample size. It should still be fun to look at. Below are the final scores grid for all the 41 Super Bowl games.

Most of you are playing the random version of the betting squares so this information is irrelevant. The only thing I could say is good luck.
For those of you like me playing the strategic version, play with the odds. Someone should build a Fantasy Squares and have people go to a site at a specific date and time to pick squares. Stay tuned for Super Bowl picks coming this Sunday!

Psychological Edge in Football Gambling

What makes a gambler bet and go to casinos? Many bettors believe it's fun and worth losing the money, but most believe they have an edge over the house and believe they can profit with their predefined strategies. Gamblers that bet on the roulette for example, might study the roulette and figure out that some numbers are called more than others thinking the wheel is not leveled. Blackjack player who count cards can spot when the deck is in their favor and make larger bets at this point and smaller bets when it is against them. Whichever the game, a good gambler sticks to a proven strategy and does not let his/her emotions affect decision making.

Human Emotions are Your Worst Enemy
Before I started putting real money on NFL games, I spent two years gathering data, analyzing different systematized strategies, and making gambling decisions in real time, but not with real money. It was easy sticking with what the computer said since my emotions and biases were not playing a role. After finding a methodology that was statistically robust, I decided it was time to put my emotions and decision making to test in the real market.

NFL gambling is somewhat similar to trading. One follows historical data and available information to make decisions that win and lose money. Due to this environment, people tend to distort their perception of reality and suffer from what psychologists call cognitive biases. Here are some biases that affected me at the time of placing a wager and deciding on the amount of money to place:

  • Outcome bias: Judging a decision (after the fact) by its outcome (win/lose) rather than by the method and quality at the time the decision was made

  • Recency bias: Weighing recent data or outcomes more than the earlier ones

  • Anchoring: Relying too heavily, or anchor, on a specific piece of information

  • Herd Effect: To believe what the majority believes

  • Small sample effect: Drawing unscientific conclusions based on limited information

Even with the systematized gambling system I had been working for so long, at the time of truth, I suffered from the above biases.

Outcome Bias
After my first week of betting, I covered only 1 of 3 bets. In a Seattle @ Cleveland game, my model predicted Seattle to cover and at the current spread and model prediction, in 10 years of data, keeping this strategy would have earned 60% of the time. The circumstances were good, no key players injured or absurd weather. Unfortunately, after this outcome I decided to change my strategy completely only to begin to see my money decrease (fortunately only slowly). Good strategies result in losses, that is the natural game of probability, but doubting your strategy and changing behavior because of these recent outcome will in the long run affect you negatively.

Recency Bias
Making a decision based on how an NFL team has played in the past game or two is one of the biggest mistakes you can make. Take the New England @ Baltimore game on week 12. In the previous two weeks, Baltimore lost to Cleveland by 3 and San Diego by 18, New England beat Philadelphia by 3 and Buffalo by 45. What will you do with a spread of 23? Baltimore is worst than Buffalo so you bet New England cover? These two games are not sufficient to make a decision (small sample effect discussed below) and recent outcomes should be looked at with the same magnifying glass as previous games. Use ALL the information, find the trend, and make your bet.

"Anchoring is the tendency for people to rely too heavily on readily available information when making a decision involving uncertainty." (Curtis Faith, Way of the Turtle) Take an NFL game where a team is favorite by 10 points. You look at the historical data and notice that this team has never been favorite by this much, is that sufficient information to place a bet? Only when you are anchoring. Using one piece of information to gauge the relative strength of a decision will lead you to use false information. If you really think that one piece of information is useful, why not use it every week? It is unlikely that one statistic will determine a profitable strategy in NFL gambling. Combine the factors, systematize your strategy, test, and keep your emotions away.

Herd Effect
Following the NFL spreads opening and closing lines for these years has convinced me to just ignore them. I researched the NFL gambling literature on this topic and found a paper that looked at 10 years of data. The conclusion of the paper was that betting the opposite way of the line move yields 54%. Is 10 years enough? Is this statistically significant? They claim it is, but it is rather close to braking even. Before reading that paper (and learning of these biases), I would check the betting percentages on to make sure my strategies coincided with other gamblers. If they didn't, I would hold off on amounts or the bet completely. To make the story short, I lost good opportunities because of the herd effect on me.

Developing a strategy, testing it, sticking with your proved system regardless of the present consequences is smart gambling or like I like to call it investing. After reading The Way of the Turtle (great book, I recommend it) , I realized I was hurting my strategy due to these cognitive biases. Then putting all emotions apart, I stuck to my guns and after a 2-4 ATS week I came up big in the last few weeks of the season and during the playoffs. The only loss in the playoffs was last week's Green Bay bet. Although my loss was low because my wagering amount is proportional to my percentage of confidence, I am sticking with my system and continuing to finding opportunities in the NFL spread.

Conference Championships

Looking back at my posts I had:
Wild Card: SEA (-3) over WAS
Divisional: GB (-8) over SEA and SD (+10.5) over IND
THIS WEEK'S SPREAD PICK: Conference: 1 pick this week
Perfect Record in the 2007 playoffs so far...

NYG @ Green Bay Packers

This Sunday, the favorite (by -7) young guys at Green Bay face a hopeful Giants team for the NFC Championship. The Vegas line posted on Monday has remained steady at -7, although some sites have raised the odds from 110 to up to 130. Many bettors (about 65% according to are favoring the Packers and some sites predict that the line will move half a point before Sunday.

What will the Giants have to do to beat the Packers? Stop Ryan Grant, pressure Favre all day, and get a great game from all its key players including: Manning, Jacobs, and Burress. The weather will be close to 5 degrees fahrenheit which might favor the Giants to cover, still the odds of keeping the Packers withing 7 points are small. In cold it is easier to run, so keeping Grant from running more than 100 yards will be key, can they do that? They have to stop the fast offense. Green Bay can go so fast from one side of the field to the other it's scary. The Packers have scored more than 30 points in 10 games this season, that's 59% of the games.

In the past 4 weeks, my model has predicted the opposite of what has seemed to be the favorite bet. In the wild card, the model went against the majority of the experts by picking San Diego over Washington and San Diego's cover over the Colts. Now, the most popular bet is Green Bay. Against a team with the Giants' strength, my predictive model predicts:

Packers -7 but unfortunately, it goes along with a big trend, so I would think about this pick twice.


Be careful with this game, it seems to be very volatile meaning luck will play a bigger role than past performance. Many players are injured and it is very hard to predict the influence this will have on the San Diego offense. Be even more careful of people using "trends" to predict this game. For example, New England's ATS mark in the past 8 games or San Diego's perfect ATS record in the past 8 games. There is little statistical (but some authors claim they have) evidence that once a team covers many games in a row, it is least likely it will again. Therefore if anything, these trends would lead me to conclude that it is time San Diego will fail to cover and the Patriots' will.

My NFL predictor has New England falling a bit short of 14, but this uses data from the past 10 weeks. This data is useless since it would assume all players, or at least key players, will play this week. Not bet this week: if I were investing in NFL spreads, I would put my money on Green Bay and keep this game out.

San Diego @ Indianapolis Divisional Playoff Pick

The spread has shifted 2.5 points for the Colts since I wrote the predictions and picks for this week on my previous post. Bodog has the Colts winning by -10.5. I ran my model again to see if the increase in the point spread would increase the percentage of wins significantly. It did increase the percentage from 56% to 58%, that is, when the home team is favorite by more than 9 points and my prediction is lower than the spread by 4-6 points is have gotten a 58% ATS.

Now there is a catch, injuries are not taken into account. Since I only take into account team statistics, if a player is injured, there is currently no way to account for that. I argue that if a bench player or a player not selected for the Pro Bowl is injured, the pick is still valid. On the other hand, if a player like Antonio Gates (leader in receiving yards for San Diego) is injured the model should be ignored. So, although I like San Diego covering a spread of +10.5, if Gates does not play which is still a game-time decision but likely not to play, I would ignore this game and not place a bet.

NFL Divisional Playoffs Picks

Quick Picks:
Green Bay -8

This week the statistical model is identifying one game with a great opportunity to bet on. Although the prediction favors Green Bay by 9 (only one point more of the Vegas spread), in 37 games dating back to 2000, this prediction favors the home team 70% of the time. That is, when the spread is between 6 and 8 points for the home team and the prediction favors the home team slightly (less than 2 points), betting for the home team has produced a 70% success rate. In this case, we are identifying games where the Vegas spread is under-rating the home team when they should be more heavily favorite. Favre's last chance at a Super Bowl ring, at a noisy Lambeu Field, no key injuries, I like this bet. The recent shaky performances by the Packers are keeping the spread at 8 and gamblers are split 50-50.

One other possible opportunity I have highlighted in yellow is the Indianapolis/San Diego game. Both team have playoff experience and a spread of 8 seems rather high to the statistics at hand. The defending champions will probably win the game, but the prediction states it will not be by more than a TD.

In last 2 weeks the model has performed very well and an overall season percentage of 59% ain't bad at all. Below I have included the usual table with predictions and success percentages. Disregard the Dallas game since TO, a key offensive player for the Cowboys, is out. If you read more, you will see graphs of these teams statistics against each other and their performance in the past 5 games.

NFL Divisional Playoffs Spread Picks

Seattle @ Green Bay
Below is a graph of the Vegas line and the outcome of games where these two teams have faced each other. The last game these two teams faced each other was in November 27, 2006 where the Seahawks were favorites by 12, but did not cover the spread since they won, but only by 10. How things have changed! At the time, GB was 4-7 and Seattle was 5-1 with Alexander at almost the top of his game. The previous game was on week 17 of the 2005 season where Favre's pass at the end made GB win by 6 and make the bet a push. At this point Seattle was already in the playoffs and the Packers were going home with a 4-12 record for the season.

In the past 5 games, both teams have outperformed their opponents in rushing and passing yards, Green Bay outperforming its opponents by a bigger number of yards. Seattle on average runs about 9 yards more than its opponents and passes about 15 yards more. Green Bay on the other hand is running on average more than 30 yards per game than its opponents and passing more than 12 yards.
This makes me more comfortable in saying that Green Bay will cover -8.

NFL Wild Card Spread Picks

Quick NFL Picks:
Seattle -3.5

Last week the statistical predictions only included one game and one winner! KC came back in the 4th quarter to tie it and lose the game but to cover the spread of 6 against the Jets.

This week, of the 4 NFL wild card games, only 1 seems like a good bet and I personally like it because the spread has moved 1.5 points in the other direction. The game is Washington @ Seattle which bettors favor Seattle by 3.5 but originally it was a 5 point spread. The model has a solid 61% success rate of games with the spread between 2-4 for the home team and the estimate being within 2 points of the Vegas spread. Seattle if predicted to win by 5.

Journalists are favoring Washington because they have "momentum", something that has been scientifically proven to be a fallacy. It is just random that a basketball player makes 50 free throws in a row or a team wins 4 games in a row. The relevant statistic is that the player is a 90% free throw shooter or a team has a 60% winning percentage not how you got there. For example, a coin has 50-50 chance of showing up heads-tails. If you flip a coin and get 10 heads in a row, is it more likely that your next toss will be a head? No.

I have included bets for all the other games, but none of the other 3 seem significantly good, meaning the estimate is as good as flipping a coin. But the Seattle pick is significant and although it is as good as throwing a coin with 61% probability heads and 39% tails, following this strategy through 7 years, would be a very profitable strategy for bettors.

Wild Card Picks against the Vegas spread