On the eve of the Super Bowl: What is the Peyton Manning contribution to Denver’s offense?

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.

 

2013 OSRS and DSRS quick hits: Denver Broncos and Indianapolis Colts

Enough data has been published previously on Denver and Indianapolis to do a direct comparison, but what do they look like historically?

Denver’s data set looks like this:

Denver Broncos 2005-2013
Year	Team	W	L	T	SRS	OSRS	DSRS	MOV	SOS
2005	DEN	13	3	0	10.79	6.30	4.49	8.56	2.23
2006	DEN	9	7	0	1.32	-0.72	2.04	0.88	0.44
2007	DEN	7	9	0	-3.95	-1.57	-2.38	-5.56	1.61
2008	DEN	8	8	0	-5.79	1.15	-6.94	-4.88	-0.91
2009	DEN	8	8	0	0.32	-1.09	1.41	0.12	0.20
2010	DEN	4	12	0	-8.91	-0.54	-8.37	-7.94	-0.97
2011	DEN	8	8	0	-5.30	-2.87	-2.43	-5.06	-0.23
2012	DEN	13	3	0	10.10	7.08	3.02	12.00	-1.90
2013	DEN	6	0	0	13.95	21.22	-7.26	17.83	-3.88

 

And Indianapolis’s data set looks like this:

Indianapolis Colts 2005-2013
Year	Team	W	L	T	SRS	OSRS	DSRS	MOV	SOS
2005	IND	14	2	0	10.80	6.82	3.98	12.00	-1.20
2006	IND	12	4	0	5.88	7.31	-1.43	4.19	1.69
2007	IND	13	3	0	12.01	6.44	5.57	11.75	0.26
2008	IND	12	4	0	6.49	1.58	4.91	4.94	1.55
2009	IND	14	2	0	5.93	3.65	2.28	6.81	-0.88
2010	IND	10	6	0	2.88	5.15	-2.27	2.94	-0.06
2011	IND	2	14	0	-11.28	-6.99	-4.29	-11.69	0.40
2012	IND	11	5	0	-4.71	-2.39	-2.32	-1.88	-2.84
2013	IND	4	2	0	8.89	1.72	7.18	8.33	0.56

 

Using SRS, you would say that Denver has a slight advantage. Let’s look at three different predictive techniques and what they say about point spread and odds of winning the game. (1) These three, for the Denver-Indianapolis game, yield very different results.

Odds of Denver Winning and Predicted Point Spread
Pythagorean Expectation		Simple Ranking System		Median Analysis
Pct	Points	Pct	Points	Pct	Points
0.48	-0.6	0.57	2.1	0.77	9

 

The two techniques I trust more, Pythagoreans and SRS, yield different results for the winner but both say the game will be decided by less than three points. With games this close, small factors – a single turnover, a great punt return – can decide the results. I add the median prediction largely as a comparison. I don’t trust it as much as the other two methods in terms of predicting results.

All three predictions include a home field advantage effect.

Notes:

1. For a simple relationship between point spreads and winning percentages, look here. A different approach is given in the book “Mathletics“, worth reading if you’re into betting football.

 

Assessing the break even point of NFL draft trades

There were eight trades in the first day involving the first round of the 2012 NFL draft. Most of them involved small shifts in the primary pick, with third day picks added as additional compensation. The one outlying trade was that of the St Louis Rams and the Dallas Cowboys, which involved a substantial shift in  the #1 pick (from 6 to 14) and the secondary compensation was substantial. This high secondary compensation has led to criticism of the trade, most notably by Dan Graziano, whose argument, boiled to its essence, is that Dallas paid a 2 pick price for Morris Claiborne.

Counting  picks is a lousy method to judge trades. After all, Dallas paid a 4 pick price for Tony Dorsett. Was that trade twice as bad a trade as the Morris Claiborne trade?  The Fletcher Cox trade saw Philadelphia give up 3 picks for Fletcher Cox. Was that trade 50% worse than the Morris Claiborne trade?

In order to deal with the issues raised above, I will introduce a new analytic metric for analyzing trade risk, the risk ratio, which is the sum of the AV values of  the picks given, divided by the sum of the AV values of the picks received. For trades with a ratio of 1.0 or less, there is no risk at all. For trades with ratios approaching 2 or so, there is substantial risk. We are now aided in this kind of analysis by Pro Football Reference’s new average AV per draft pick chart. This is a superior tool to their old logarithmic fit, because while the data may be noisy, they avoid systematically overestimating the value of first round picks.

The eight first round trades of 2012, interpreted in terms of AV risk ratios.

The first thing to note about the 8  trades is that the risk ratio of 6 of them is approximately the same. There really is no difference, practically speaking, in the relative risk of the Trent Richardson  trade, or the Morris Claiborne trade,  or the Fletcher Cox trade. Of the two remaining trades, the Justin Blackmon trade was relatively risk free. Jacksonville assumed an extra value burden of 10% for moving up to draft the wide receiver. The other outlier, Harrison Smith, can be explained largely by the noisy data set and an unexpectedly high value of AV for draft pick 98. If you compensate by using 13 instead of 23 for pick #98, you get a risk ratio of approximately 1.48, more in line with the rest of the data sets.

Armed with this information, and picking on Morris Claiborne, how good does he  have to be for this trade to be break even? Well, if his career nets 54 AV, then the trade breaks even. If he has a HOF career (AV > 100), then Dallas wins big. The same applies to Trent Richardson. For the trade to break even, Trent has to net at least 64 AV throughout his career. Figuring out how much AV Doug Martin has to average is a little more complicated, since there were multiple picks on both sides, but Doug would carry his own weight if he gets 21*1.34 ≈ 28 AV.

Four historic trades and their associated risk ratios.

By historic measures, none of the 2012 first round trades were particularly risky. Looking at some trades that have played out in  the past, and one  that is still playing out, the diagram above shows the picks traded for Julio Jones, for Michael Vick, for Tony Dorsett, and also for Earl Campbell.

The Julio Jones trade has yet to play out, but Atlanta, more or less, assumed as much risk (93 AV) as they did for Michael Vick (94 AV), except for a #4 pick and a wide receiver. And although Michael is over 90 AV now, counting AV earned in Atlanta and Philadelphia, he didn’t earn the 90+ AV necessary to balance out the trade while in Atlanta.

Tony Dorsett, with his HOF career, paid off the 96 AV burden created by trading a 1st and three 2nd round choices for the #2 pick. Once again, the risk was high, the burden was considerable, but it gave value to Dallas in the end.

Perhaps the most interesting comparison is the assessment of the Earl Campbell trade. Just by the numbers, it was a bust. Jimmie Giles, the tight end that was part of the trade,  had a long and respectable career with Tampa Bay. That, along with the draft picks, set a bar so high that only the Ray Lewis’s of the world could possibly reach. And while Campbell was a top performer, his period of peak performance was short, perhaps 4   years. That said, I still wonder if Houston would still make the trade, if somehow someone could go back in to the past, with the understanding of what would happen into the relative future. Campbell’s peak was pretty phenomenal, and not entirely encompassed by a mere AV score.

 

NFL Free Agency: as the beat goes on

The biggest fish in free agency was Peyton Manning, and now that fish has been landed, by the Denver Broncos. Peyton arriving now leads to speculation about Tebow leaving, and some Dallas media sorts have suggested that he might land with the Cowboys. My general feeling is possibly, if he ends up being cut, but since Dallas already has a serviceable backup in Kyle Orton (one of their first free agent pickups), I’m not sure I see the need.

Peyton Manning is now a Denver Bronco. Image from Wikimedia.

However, Tebow has what former Falcons QB David Archer calls “no off switch”. He doesn’t quit, even under conditions where most people give up.  This “never say never” attitude will land him a job somewhere. His will to win, will to work, and totally improbable ability to win games will land him somewhere. I’m sure of it.

It seems to me the team that could handle Tebow best would be the Carolina Panthers. With Cam Newton already using spread and zone concepts, it would be much less effort for that team to accommodate Tim. The question, of course, is whether they would want to.

Important in the NFC East scheme of  things was the Redskins trade for the #2 draft choice. They are almost certainly going to draft RG3 with that pick. For some years now, the Skins have lived with an unsettled QB situation, and now that is over. The question on their plate is how to accumulate talent with the draft deficit  they face.

The Eagles signed WR DeSean Jackson to a long term contract, and if I recall, have traded for DeMeco Ryans as well. Is this the end to their linebacker woes?  Now, the free agency linebacker market, as noted by such sources as Pro Football Focus, has been stolid. The general consensus is that the best linebackers had very high salary expectations. Clubs are just waiting for the talent that is there to be affordable.

Dallas, of course, faces the same issue on their offense as they did before free agency. If their biggest problem is Phil Costa at center, what have they done to fix that? They have picked up two free agent  guards, Nate Livings and Mackenzy Bernadeau, neither of which is regarded as a great player, but then again, they didn’t pay much either. The most important pickup was CB Brandon Carr, who replaces Terrance Newman. Also useful was QB Kyle Orton, and the LB Dan Connor (insert Terminator joke here).

 

NFL Playoffs 2012: #4 seeds at the #1 seeds

Both the Giants and Denver have won today, eliminating all wild cards and leading to two #4 seeds playing at the #1 seeds. In the case of the Giants, using my formula, we have the question of whether they truly have playoff experience. If they do not, then Green Bay is favored, on average, by 56%, though the relative error of strength of schedule results allow for Green Bay being favored by as much as 73% to the Giants being favored by 63%. If the Giants are treated as if they have playoff experience, then there is a wide range of results, from Green Bay being favored by 55% to the Giants being favored by 78%, with the average result being the Giants favored by 63%. Note that home field plus Pythagoreans would favor Green Bay by 83%.

In the Case of Denver versus New England, New England has playoff experience and home field in their favor, and Denver played a tougher schedule. New England is favored by my scheme by 69%. Home field plus Pythagoreans would favor New England by 88%.

 

Playoffs 2011: Pittsburgh at Denver

Playoff experience is a potent effect, enough to overcome Denver’s advantages in home field and tougher schedule.

Steelers: Super Bowl last year, Away, SOS = -0.84, Pythagorean = 71.8%

Broncos: Last in playoffs 2005, Home, SOS = -0.23, Pythagorean = 35.3%

Typically in playoff games, you don’t see huge differences in offensive stats, because the teams that make it in the modern NFL tend to be good offensive teams.But Denver is nearly as bad this year as Seattle was last year (Seattle actually was worse, with a Pythagorean of 32.7%).  Treating this as a regular season game, instead of a playoff game would give PIT a 76% edge. Instead, using the playoff formula, PIT would be favored by 54%.

 

Tim Tebow, Eli Manning, and notions of clutchness

The fans were all nestled, all snug in their beds, while visions of clutch quarterbacks all danced in their heads.

Tim Tebow has managed to capture the imaginations of many announcers, fans, and analysts, including the eye of one Benjamin Morris. Ben posits, among other things,  that Tebow is being held back by his own conservatism,  that an inability to take passing risks in the first three quarters of the game is tossed aside in the fourth and some more true representation of his passing skill emerges.

This isn’t the first time that Ben has speculated on the nature of young quarterbacks and interceptions (This link is the most important, but also see here and here). One contradictory notion  that has come out of his analyses is that a lot of interceptions early in the career of a quarterback tends to be a good thing. It suggests a quarterback with exceptional skills testing those skills out — the idea that a talented cook has to get burned by his own grease to learn his chops spills over into the quarterbacking world.

A related question, important to NFC East fans, is Eli Manning clutch? This question was raised this year by Eli Manning’s exceptionally high ESPN QBR ratings relative to other metrics. People really got upset, claimed that the ESPN QBR was “busted”. But perhaps the ‘clutch’ factor actually saw something in Eli.

It’s almost a theme with the Giants that they fall behind and Eli either scores a couple late to win the game, or scores late to tie the game and then (win/lose) in overtime, or he puts on this furious rally that almost wins the game. They beat teams they shouldn’t, based on their Pythagoreans, and then lose to football patzers.

What to make of it? My gut unchecked feeling is yes, Eli is clutch, but  his team is another question altogether. It’s difficult to know with fans, emotions get the best of them. Donovan McNabb becomes Donovan McFlabb, good analysts try to prove that Jon Kitna is a better quarterback than Tony Romo, etc.

Thinking without benefit of numbers a bit further, Eli just doesn’t get ruffled. His play doesn’t suffer any effects of pressure. And that means, no matter how inadequate the team around him becomes, he’s still dangerous.

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Kindle notes: just bought a Kindle Fire, and like it a great deal. It’s a better email platform than many web based email services, so it is  useful to forward  mails from those services to this device. I wish I could plug my  camera into the Kindle and upload photos, but  that will probably have to wait until Android 4 becomes a common base OS for these kinds of portable devices.

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Twitter notes: For those familiar with Smart Football, he tweets well, and is a useful feed if you’re at all interested. Trent Dilfer does quite a bit of good analysis via tweets. Surprisingly good is Doug Farrar, whose player analyses I tend to respect. I haven’t read much of Doug’s blog, Shutdown Corner, but given the character of his tweets, it might be worth a gander.

 

Rex and Rob Ryan: Loaded for Bear

Both Rex and Rob Ryan are known to use the Bear front, otherwise known as the double eagle, and in its 1985 incarnation, the 46, and  in preseason week 1 year 2011, both brothers flashed some double eagle with 8 man line.

The image above is the most famous Bear of the night, as Jon Gruden mentioned it, but  the very next play featured a Bear with a flexed nose tackle.

Rob’s double eagle had 5 down linemen instead of 6, but the 6 players along the line, and two players at linebacker depth and over the tackle leads me to designate this the first Bear the Cowboys have run under Rob Ryan.

 

Bobby Beathard, the book “Hail Victory”, and classes of draft strategies

I’ve had this book a while, but really haven’t had a chance to show it off.

“Hail Victory” is an oral history of the Washington Redskins, written by Tom  Loverro, a writer for the Washington Times. It’s smaller than Pete Golenbock’s oral history of the Cowboys, by a few hundred pages, and as a consequence, coverage of certain periods can be spotty.

But to give an example of the kinds of insights this book does have, here is a quote from page 180 talking about the beginnings of the 1982 season.

Gibbs made it clear he was going to use youngsters over veterans who didn’t produce. He cut running back Terry Metcalf, whom  he had been close to from their days in Saint Louis. He made backup linebacker Rich Milot a starter, as well as rookie cornerback Vernon Dean. He cut receiver Carl Powell, a top draft choice, in favor of unheralded Alvin Garrett. He brought in veteran defensive end Tony McGee to replace Mat Mendenhal and shore up the pass rush.

I bought “Hail Victory” initially to help answer the question of George Allen’s five man line back in 1972, but it was no help there. It’s going to be a terrific help as I chase down information on my next element of interest, Bobby Beathard. And he’s interesting because Washington is the ultimate counter example of the group “A” teams I’ve been so fascinated by recently.

What’s a  group “A’ team?  It’s one of the four I’ve circled on this plot:

I’m thinking now there are clusters of teams with draft strategies. The four in group “A” are New England, Green Bay, Pittsburgh, and Philadelphia. I spoke about their apparent habits here. The groups “B” and “C” are unstudied so far. Group B  teams are Denver and Indianapolis. Group C teams are Minnesota and the New York Giants. Left of group B are a cluster of 8 teams, that might as well be named group D for now. And down by its little lonesome, right at the 6.5 player/year line, is Washington.

My guess is that Bobby Beathard, the former general manager of the Washington Redskins, is the ultimate counterexample for the type “A” team.

Some things to note. Bobby was quarterback in college, and then a scout before he entered the NFL. He scouted for Kansas City in the later 1960s, was the director of player personnel for the Miami Dolphins during their peak, and in 1978, when Jack Kent Cooke was the majority owner of the Skins, he became their general manager.

There is an excellent interview of Bobby Beathard on the site Burgundy and Gold Obsession. There is a section from that interview that really stands out, and it’s the same kind of emphasis  that Bill Billick  has attributed to the Belichick era with New England. Bobby is responding to a question in this excerpt (emphasis is mine).

There should be a relationship where the personnel people and the coach are really together. We knew exactly what type of player each Redskin position coach wanted. We knew what kind (offensive line coach) Joe Bugel wanted, we knew what kind (linebackers coach) Larry Peccatiello, (defensive coordinator) Richie Petitbon wanted. I think on our first Super Bowl team we had 26 kids who weren’t drafted, we just signed them as free agents. It didn’t matter who we brought in. Those guys coached the dog out of them. When I was with (head coach) Kevin Gilbride in San Diego, he’d make up his mind before he even got to minicamp, `I don’t want that guy, I don’t want this guy, I don’t want that guy.’ And it became impossible to satisfy him with anybody. The exact opposite was Joe and his staff. Having a staff like that really helps the organization.

What’s very intriguing is this emphasis on the “back end” of the draft, or in this case, post-draft free agents. It’s also the notion that the coaches tell the scouts what kind of players to get, and the scouts go out and  get them exactly those kinds of players. The fit helped make the Redskins of the 1980s successful. And in another form, it’s the same back end emphasis you see in the type “A” teams.

With regard to the best possible athlete versus need question, Bobby said this:

Sometimes you get into that situation when you have the philosophy which we did, you have to take the best one on the board, regardless of position. We always hoped when we picked there would be two or three good players available at different positions, so you’d at least get to take closer to your need. But if there’s just one there, and he’s outstanding, and you have a great grade on the guy and the next athlete on the board doesn’t have that kind of grade, you have to go with the highest-graded player.

And that seems to be a common theme, BPA of course, but need when there are two or three attractive alternatives.