### Super Bowl

The cumulative stats for the 2015 regular season are:

This gives us the basis to generate playoff values based on my playoff formula. Playoff Odds are calculated according to this model:

logit P = 0.668 + 0.348*(delta SOS) + 0.434*(delta Playoff Experience)

and the results are:

2015 NFL Playoff Teams, C&F Worksheet.
NFC
Rank Name Home Field Adv Playoff Experience SOS Total Score
1 Carolina Panthers 0.406 0.434 -1.35 -0.51
2 Arizona Cardinals 0.406 0.434 0.456 1.296
3 Minnesota Vikings 0.406 0.0 0.654 1.06
4 Washington Redskins 0.406 0.0 -0.866 -0.46
5 Green Bay Packers 0.0 0.434 0.863 1.297
6 Seattle Seahawks 0.0 0.434 0.769 1.203
AFC
1 Denver Broncos 0.406 0.434 0.727 1.567
2 NE Patriots 0.406 0.434 -0.839 0.001
3 Cinncinnati Bengals 0.406 0.434 0.661 1.501
4 Houston Texans 0.406 0.0 -0.828 -0.422
5 Kansas City Chiefs 0.0 0.0 0.564 0.564
6 Pittsburgh Steelers 0.0 0.434 0.696 1.130

The total score of a particular team is used as a base. Subtract the score of the opponent and the result is the logit of the win probability for that game. You can use the inverse logit (see Wolfram Alpha to do this easily) to get the probability, and you can multiply the logit of the win probability by 7.4 to get the estimated point spread.

For the first week of the 2014 playoffs, I’ve done all this for you, in the table below. Odds are presented from the home team’s point of view:

First Round Playoff Odds
Home Team Visiting Team Score Diff Win Prob Est. Point Spread
Minnesota Vikings Seattle Seahawks -0.143 0.464 -1.05
Washington Redskins Green Bay Packers -1.757 0.147 -13.0
Cinncinnati Bengals Pittsburgh Steelers 0.371 0.591 2.75
Houston Texans Kansas City Chiefs -0.986 0.271 -7.30

So the system suggests that Minnesota – Seattle should be close, perhaps unbettable. Cinncinnati-Pittsburgh is an even match, with Cinncinnati’s factors amounting to a typical home field advantage. Houston-Kansas City and Washington-GB are predicted to be easy wins for the visiting team.

To start, a summary of the 2014 regular season data:

This gives us the basis to generate playoff values based on my playoff formula. Playoff Odds are calculated according to this model:

logit P = 0.668 + 0.348*(delta SOS) + 0.434*(delta Playoff Experience)

and the results are:

2014 NFL Playoff Teams, C&F Playoff Model Worksheet.
NFC
Rank Name Home Field Advantage Prev. Playoff Experience Strength of Schedule Total Score
1 Seattle Seahawks 0.406 0.434 0.275 1.115
2 Green Bay Packers 0.406 0.434 -0.118 0.722
3 Dallas Cowboys 0.406 0.0 -0.630 -0.224
4 Carolina Panthers 0.406 0.434 -0.292 0.548
5 Arizona Cardinals 0.0 0.0 0.449 0.449
6 Detroit Lions 0.0 0.0 -0.132 -0.132
AFC
1 NE Patriots 0.406 0.434 0.438 1.278
2 Denver Broncos 0.406 0.434 0.550 1.390
3 Pittsburgh Steelers 0.406 0.0 -0.703 -0.297
4 Indianapolis Colts 0.406 0.434 -0.393 0.447
5 Cinncinnati Bengals 0.0 0.434 -0.202 -0.602
6 Baltimore Ravens 0.0 0.0 -0.724 -0.724

The total score of a particular team is used as a base. Subtract the score of the opponent and the result is the logit of the win probability for that game. You can use the inverse logit (see Wolfram Alpha to do this easily) to get the probability, and you can multiply the logit of the win probability by 7.4 to get the estimated point spread.

For the second week of the 2014 playoffs, I’ve done all this for you, in the table below. Odds are presented from the home team’s point of view.

Second Round Playoff Odds
Home Team Visiting Team Score Diff Win Prob Est. Point Spread
Seattle Seahawks Carolina Panthers 0.567 0.638 4.2
Green Bay Packers Dallas Cowboys 1.352 0.795 10.0
New England Patriots Baltimore Ravens 2.002 0.881 14.8
Denver Broncos Indianapolis Colts 1.349 0.794 10.0

Baltimore is not given much of a chance by these techniques, but an interesting analysis by Benjamin Morris of Skeptical Sports (featured now on fivethirtyeight.com) is worth paying attention to. Though the divisional round is hard on teams without a bye, those that survive appear to have a superior chance to go forward in the playoffs. Benjamin has always struck me as an incisive analyst, so he’s absolutely worth paying attention to.

The competitors are Denver and Seattle, and as stated previously, my model favors Seattle substantially.

Super Bowl
NFC Champion AFC Champion Score Diff Win Prob Est. Point Spread
Seattle Seahawks Denver Broncos 1.041 0.739 7.7

Of course by this point my model has been reduced to a single factor, as there is no home field advantage in the Super Bowl and both teams are playoff experienced. Since every season 8 of the 11 games are before the Conference chanpionships and Super Bowl, the model works best for those first eight games. Still, it’s always interesting to see what the model calculates.

At least as interesting is the Peyton Manning factor, a player having the second best season of his career (as measured by adjusted yards per attempt). I thought it would be interesting to try and figure out how much of the value above average of the potent Denver Broncos attack that Peyton Manning was responsible for. We’ll start by looking at the simple ranking of the team, divided into the offensive and defensive components. Simple rankings help adapt for the quality of opposition, which for Denver was below league average.

Denver Broncos Simple Ranking Stats
Margin of Victory Strength of Schedule Simple Ranking Defensive Simple Ranking Offensive Simple Ranking
12.47 -1.12 11.35 -3.31 14.65

Narrowed down to the essentials, how much of the 14.65 points of Denver offense (above average) was Peyton Manning’s doing? With some pretty simple stats, we can come up with some decent estimates of the Manning contribution to Denver’s value above average.

We’ll start by calculating Peyton’s adjusted yards per attempt, and do so for the league as a whole. We’ll use the Pro Football Reference formula. Later, we’ll use the known conversion factors for AYA to turn that contribution to points, and the subtract the league average from that contribution.

Passing Stats, 2013
Player(s) Completions Attempts Yards Touchdowns Interceptions AYA
Peyton Manning 450 659 5477 55 10 9.3
All NFL passing 11102 18136 120626 804 502 6.3

The difference between Peyton Manning’s AYA and the league average is 3 points. Peyton Manning threw 659 times, averaging about 41.2 passes per game. This compares to the average team passing about 35.4 times a game. To convert an AYA into points per 40 passes, the conversion factor is 3.0. This is math people can do in their head. 3 times 3 equals 9 points. In a game situation, in 2013, where Peyton Manning throws 40 passes, he’ll generate 9 points more offense than the average NFL quarterback. So, of the 14.65 points above average that the Denver Broncos generated, Peyton Manning is at least responsible for 61% of that.

Notes:

There is a 0.5 point difference between the AYA reported by Pro Football Reference and the one I calculated for all NFL teams. I suspect PFR came to theirs by taking an average of the AYA of all 32 teams as opposed to calculating the number for all teams. To be sure, we’ll grind the number out step by step.

The yards term: 120626
The TD term: 20 x 804 = 16080
The Int term: 45 x 502 = 22590

120626 + 16080 – 22590 = 114116

Numerator over denominator is:

114116 / 18136 = 6.29223… to two significant digits is 6.3.

I can’t say for certain if the 1991 Super Bowl (highlights here, DVD here) contains the oldest nickel front in the world, as there is a side of me that  thinks the Miami 4-3 is a thinly disguised 2-3-6 – think about it, using what kinds of players are placed where, as opposed to what kinds of names the positions are called. Isn’t a Miami 4-3 equivalent to this:

And not all that far removed from this:

Just sayin’.

In the book “Education of a Coach“, by David Halberstam, a book about Bill Belichick, and a decent read, Halberstam goes into great detail about  the base nickel front that Belichick used in the 1991 Super Bowl. And yes, isn’t this, the first offensive play of the Bowl, an argument that Belichick is your nickel front daddy?

I say, who is your nickel front daddy?

Halberstam says this defense was, in modern terms, a 2-3 dime. Of course,  with Lawrence Taylor as the rush linebacker, it was a rather stout 2-3.

Miami 4-3 notes..

• This thread from Football Futures, I think, is one of the better reads on the Miami 4-3.
• Coach Hoover: Miami 4-3 versus the flexbone.
• Coach Huey: Miami 4-3 compared to the K State 4-3.
• Fifth Down Blog on the 4-3 (including the Miami). The whole guide summarized here.
• Linebackers in the Miami 4-3.