DR BOB
SUPER BOWL ANALYSIS
New England (-12) 37 New York Giants 20
The line on this game opened with the Patriots as a 14 point favorite and quickly went down to 12 points. Apparently, New England ’s lack of recent pointspread success (5 straight spread losses and 2-8 ATS after starting the season 8-0 ATS), combined with the Giants’ 10 consecutive wins away from home, have generated a lot of interest in betting on the big underdog in this game. The question is if that interest in taking the surging Giants plus the 12 points is prudent. Let’s start by finding a fair line for this game.
New England Offense versus New York Defense
The Patriots’ offense is one of the best in NFL history, averaging 409 yards at 6.3 yards per play and 35.6 points per game. Running back Laurence Maroney leads a rushing attack that averaged a solid 4.4 ypr (against teams that would allow 4.2 ypr to an average team) and Tom Brady has averaged an incredible 7.7 yards per pass play despite facing a schedule of teams that would combine to allow only 5.8 yppp to an average quarterback. Overall, the Patriots averaged 6.3 yards per play with Brady in the game – against teams that would allow 5.1 yppl to an average offensive unit. Presented with the task of slowing that offense down is a Giants’ defense that has yielded just 4.8 yppl since week 2 and has been good against both the run (3.9 ypr allowed to teams that would averaged 4.3 ypr) and against the pass (5.5 yppp allowed to quarterbacks that would average 6.4 yppp against an average defense). I excluded the Giants’ week 1 game against Dallas because Michael Strahan and cornerback Sam Madison did not start. Overall, the Giants stop unit rates at 0.7 yppl better than average (4.8 yppl allowed to teams that would average 5.5 yppl against an average team), which is not as good as New England ’s +1.2 yppl offensive rating. New England’s attack looked unstoppable early in the season, but slowed down some as they faced tougher defenses and played in worse weather in the second half of the season and the playoffs. Having this game in a domed stadium will most likely bring out the best in Tom Brady, who has been 1.0 yards per pass play better in domed stadiums than he’s been overall in his career. Without wind and cold weather to affect Brady I expect the Patriots to move the ball easier than they did in their week 17 contest at New York in which they averaged 6.1 yppl and scored 38 points. New York ’s great pass rush (3.1 sacks per game since week 2) only got to Brady 1 time and the Giants’ questionable secondary simply doesn’t match up with the Patriots’ stable of great receivers. Brady averaged 8.1 yppp in that game and I expect New England ’s running attack to be better in this game than it was in the first meeting (just 48 yard at 2.2 ypr).
New York Offense versus New England Defense
The Giants’ offense and Eli Manning are getting a lot of praise heading into this game, but New York was only 0.1 yards per play better than average this season (5.2 yppl with Manning in the game, against teams that would allow 5.1 yppl to an average team) and that unit was no better at moving the ball in their 3 playoffs games. New York averaged only 4.9 yppl in road wins over Tampa Bay , Dallas , and Green Bay – teams that would combine to allow 4.8 yppl at home against an average team. The difference in the post-season for the Giants was the ZERO offensive turnovers in those 3 victories, which is more random good luck than anything else. It is not likely that the Giants will continue to avoid turnovers and they are likely to turn it over at a normal rate in this game despite their spotless turnover number in the playoffs (their one fumble was a fumble by a defensive player on an interception return). After all, fumbles are 90% random in the NFL and Eli Manning has been one of the most interception prone quarterbacks in the NFL in recent seasons and has thrown 20 picks this season. New York has a good rushing attack (4.6 ypr against teams that would allow 4.1 ypr) and the Giants should have success running the football against a Patriots’ defense that allowed 4.4 ypr this season to teams that would average 4.2 ypr against an average team. However, Manning’s season numbers (and his career numbers) are worse than average (5.7 yards per pass play this season against teams that would allow 5.9 yppp to an average QB) and New England is good defending the pass (5.4 yppp allowed to teams that would combine to average 6.1 yppp against an average team), so Manning should struggle in this game despite his recent improved play. Manning did have a very good game in the Giants’ close 35-38 loss to the Patriots in week 17 (7.2 yppp) but one game does not outweigh a season of mediocrity and Patriots’ coach Bill Belichick has two weeks to prepare his defense and fix the problems that hurt them in the earlier meeting. Overall, New England’s defense (0.3 yppl better than average) has a slight edge over New York ’s offense (0.1 yppl better than average), but the Giants should move the ball at a decent clip in the perfect conditions inside the dome in Arizona .
Math Model Projection
Overall my math model projects New England to gain 374 yards at 6.0 yppl to New York ’s 317 yards at 5.3 yppl with Manning throwing 1.05 interceptions to Brady’s 0.72 picks. The stats projected for this game, which also include projected fumbles, penalties and special teams, would yield a line of New England by 5.9 points with a total score of 46.0 points under normal circumstances. However, New England is not a normal team. The Patriots turn yards into points much better than any other team because they’re so good when they get in scoring territory. If New England were a normal team their stats (i.e. yardage, yards per play, turnovers, penalties, special teams, etc) would equate to a scoring margin of +12.8 points per game but the Patriots out-scored their opponents by 18.6 points per game (35.6 to 17.0) this season. Most of the time the difference between a teams actual scoring margin and their projected scoring margin based on their stats is nothing more than random variance, but that is not the case with a few teams (Indianapolis is another team that out-plays their stats) and I believe that New England’s better than forecasted scoring margin is due to Tom Brady’s efficiency in the red-zone rather than random variance (New England has always out-played their stats with Brady at quarterback). If New England is indeed 5.8 points per game better than what their stats suggest (and New York continues to be 0.1 points better than their stats) then we get Patriots by 11.6 points instead of by 5.9 points. Most of the Patriots additional scoring margin comes from the offensive side of the football and comparing both teams total points per game with what is expected from their stats shows that this game should be 5.4 points higher scoring than my math model projects – which gives us a projected total of 51.4 points instead of 46.0 points. So, my math prediction is New England by 11.6 points with a total of 51.4 points.
Super Bowl Math
The Super Bowl cannot be looked at the same as other games. Unlike the regular season, when teams in control often relax, teams on the verge of a Super Bowl championship tend to maintain their high intensity level. At the same time, the spirits of the trailing team diminish as their hopes of a championship are dashed. The past Super Bowls, and the NFL and AFL Championship games that preceded the first Super Bowl, have long had a history of blowout wins. The winning team in the Super Bowl has won by 14 points or more 21 times in 41 games and there were 7 blowout wins of 14 points or more in the 12 NFL Championship games prior to the inaugural Super Bowl in 1967. The oddsmakers are aware of that trend and usually make the line on the Super Bowl higher than it would be under normal circumstances to adjust for the blowout phenomenon, which is why they opened the line on this game at 14 points. Blowouts haven’t been as prevalent in recent years (due to more competitive match-ups), but the lines have still had a tendency to be higher than they would be in a regular season match-up between the same teams.
Each year I calculate an equation based on the fair line for each Super Bowl and the actual Super Bowl margin of victory and I use that equation to forecast a “Super Bowl margin of victory” that is based on what the line on each Super Bowl game would be under normal circumstances. I use the mathematically fair line for all Super Bowls since 1987 (based on my math projections on the game) and I use the actual pointspread for all Super Bowls from the AFL-NFL merger in Super Bowl 4 through Super Bowl 21 in 1987 (the adjusting of the Super Bowl spreads to higher numbers didn’t actually start until the 90’s so using the actual lines in earlier games is fair). The equation I come up with certainly suggests that teams that are clearly better should certainly be favored by more points in the Super Bowl than they would be favored by under normal circumstances and the higher the fair line is the more the adjustment should be. If the fair line on this game under normal circumstances is New England by 11.6 points then the equation forecasts an average win of 21.6 points if the Patriots win the game. The same equation predicts an average win of just 3.6 points if the Giants happen to win. The next step is to calculate the chance that each team has of winning straight up, which depends on more than simply what the fair line is since every team has a different variance in their results (i.e. some or more consistent in their performance than others).
New England was unbeaten, but they got away with a few mediocre performances that would lead to a loss if the Giants played one of their better games. To incorporate variance into finding a fair line and the chance that each team has of winning straight up I use a matrix of game ratings for each team. For each team I assign a game rating that is based on each team’s statistics, the level of opponent they faced and whether the game was home, road or neutral (in the case of New York’s game against Miami in London). I used all 18 games for New England and I disregarded New York ’s game rating from their week 1 loss at Dallas when two defensive starters didn’t start. I now have 18 game ratings for each team and I can use those individual game ratings to form an 18 by 18 matrix with 324 cells that correspond to potential results for this game. I can find the median cell value to find what the pointspread should be and also calculate the percentage of cells that have New York with a higher game rating than New England , which would represent the Giants’ chance of an upset. The median cell was 12 ½ points and New York had a higher game rating in 18.2% of the cells. That number is in line with the posted odds for the Giants to win this game, as an 18.2% chance of winning corresponds to odds of 4.50 to 1 and the current line at Pinnacle is -4.65 for the Pats to win and +4.25 for the Giants.
New England has an 81.8% chance of winning this game and their average margin of victory if they win is 21.6 points based on the Super Bowl margin of victory formula I discussed above. The Giants have an 18.2% chance of winning and they’d be expected to win by only 3.6 points if they win. The resulting math projects an average margin of New England by 17 points (.818 x 21.6 - .182 x 3.6 = 17.0).
Based on the 37 past Super Bowls since the NFL-AFL merger a team that would be favored by 11.6 points in a regular season game should be favored to win by 17 points in the Super Bowl if the distribution of past Super Bowl margins is representative of future Super Bowl games. Of course, having a sample size of just 37 Super Bowls does not give us a big enough sample size to make the assumption that future Super Bowls will have the same distribution of margins of victory as past Super Bowls have had. With a limited sample size the projection of a 17 point win is likely too high, although it is certainly possible that future Super Bowl margins will have a similar distribution as in the past (especially given that NFL Championship games prior to the Super Bowl had a similar pattern). The other extreme is that the phenomenon of blowout wins in the Super Bowl is due simply to chance and that the distribution of Super Bowl results is actually the same as in the regular season. If that were the case then New England by 11 ½ points would be the fair line on this game, which still gives the Patriots close to a 50% chance of covering even if the pattern of blowouts in Super Bowls is simply random variance (and the median cell of the matrix makes them a 12 ½ point choice with a slightly better than 50% chance of covering). There is enough statistical evidence to suggest that Super Bowls do have a somewhat higher variance of margin of victory than regular season games do but not enough evidence to suggest that future Super Bowls will have the same distribution as past Super Bowls. The true answer of what the line should be lies somewhere in between the two extremes and I have come up with a realistic equation for converting regular season margins into Super Bowl margins. I will not describe that process in detail for you, but a team that would be favored by 11 ½ points in the regular season should be favored by 14 points in the Super Bowl – which is where this line opened in the first place.
My analysis suggests that the opening line of New England by 14 points is a fair line for a Super Bowl meeting between these two teams even though 11 ½ points would be a fair line in a regular season game. If the fair line is 14 points then New England is a profitable 54.5% play at -12 points (56.3% at -11 ½) and I’ll lean with New England a -13 ½ points or less, consider New England a Strong Opinion at -11 or less and a 2-Star Best Bet if the line gets down to -10. I’m inclined to believe that the tendency of blowouts by superior teams in past Super Bowls and Championship games is real and will continue. If that is the case then Patriots by 17 points would be the most likely outcome.
Super Bowl Angles
Super Bowl favorites of more than 7 points are 7-3-1 ATS and teams with a win-loss percentage that is at least .080 higher than their opponent (i.e. more than 1 game better in regular season win-loss record) are 12-5-1 ATS since the AFL-NFL merger, which coincides with the past tendency of clearly superior teams to win by big margins.
Favoring the Giants is the fact that teams on a 3 game or more pointspread win streak are 10-3-2 ATS since 1981 when not facing a team that is also on a 3 game or more spread win streak.
Over/Under
My math projected a total score of 51 ½ points for this game but Super Bowls tend to be higher scoring, especially when the teams had an extra week off to game plan. Since 1981 there have been 7 Super Bowls that were played the week following the conference championship games and those 7 games averaged 43.1 points while the 20 Super Bowls since 1981 in which the game was played two weeks after the championship games averaged 53.0 points. I also have calculated an equation that takes a predicted total and turns it into a Super Bowl total based on the tendency for higher scoring games in the Super Bowl. A game that would total 51 ½ points if it were a regular season game would result in a Super Bowl total of 59 points if past Super Bowl totals are representative of future Super Bowl totals. Once again, there is certainly a good chance that high scoring games in past Super Bowls are just a fluke but with this game being played indoors in perfect conditions I expect a high scoring game. I will lean with the Over in this game at 55 points or less.
Super Bowl Props
There were no Super Bowl Props that grabbed my attention, but I'll email everyone later in the week if I find any that do.
--------------------
2008 College: 50-40-1
2008 NFL: 20-13
2008-2009 Season: 71-52
2007-2008 Season: 186-133-9
|
Previous
Index
Next
Flat
Re: SUPER SERVICES!!!!
Edit
Reply
Quote
