New England Patriots

I’ll continue posting my odds, though this has not been the best season for them. Jacksonville continued to be best modeled by their median point spread, as opposed to their playoff formula. Philadelphia outperformed any reasonable prediction of their play once Wentz went down.

My system gives an edge to New England. Philadelphia played a tougher schedule but lacks playoff experience by my system. There is no home field in the Superbowl.

Super Bowl Playoff Odds
Home Team Visiting Team Score Diff Win Prob Est. Point Spread
New England Patriots Philadelphia Eagles 0.586 0.642 4.3

Outside of the New England game, all the games were good and exciting, from the final goal line stand by the Eagles, to the win with ten seconds left by the Vikings. The Jacksonville Jaguars are just not well managed by this system. It was easy to see that through the year that they were a boom or bust team. They could win big or lose big, and in the game with the Steelers, they were enough in “win big” mode that the Steelers could not keep up.

Philadelphia won because of their stout defense, a Nick Foles that gave them a AYA of 8.2 for the game, much akin to Carson Wentz’s average.

To remind people, the 2017 worksheet is here, and the methodology is here. The odds for the next round are below.

Conference (NFC/AFC) Playoff Odds
Home Team Visiting Team Score Diff Win Prob Est. Point Spread
Philadelphia Eagles Minnesota Vikings -0.604 0.353 -4.5
New England Patriots Jacksonville Jaguars 1.872 0.867 13.9

The first round is over and in terms of predicting winners, not my best (by my count, 1-2-1, as we had Jax and Bills in a de facto tie). I was pleased that the model got Rams and Atlanta correct, and the Sunday games all came down to the wire. One or two plays and my formal results would have been impressive. Still, back to the predictions for this week.

To add some spice, we will predict results for New Orleans normally, and also as if Drew Brees is elite. Values in parentheses are the elite numbers. With elite status or no, Minnesota is still favored in this data set.

The only home team not favored is Philadelphia. We discussed this in part in this article.

Second Round Playoff Odds
Home Team Visiting Team Score Diff Win Prob Est. Point Spread
Philadelphia Eagles Atlanta Falcons -0.878 0.294 -6.5
Minnesota Vikings New Orleans Saints 1.231 (0.484) 0.774 (0.619) 9.1 (3.6)
New England Patriots Tennessee Titans 1.674 0.842 12.4
Pittsburgh Steelers Jacksonville Jaguars 1.915 0.872 14

I suspect  to a first approximation almost no one other than Baltimore fans, such as Brian Burke, and this blog really believed that Baltimore had much of a chance(+). Well, I should mention Aaron Freeman of Falc Fans, who was rooting for Baltimore but still felt Denver would win. Looking, his article is no longer on the Falcfans site. Pity..

WP graph of Baltimore versus Denver. I tweeted that this graph was going to resemble a seismic chart of an earthquake. Not my work, just a screen shot off the excellent site Advanced NFL Stats.

WP graph of Baltimore versus Denver. I tweeted that this graph was going to resemble a seismic chart of an earthquake. Not my work, just a screen shot off the excellent site Advanced NFL Stats.

After a double overtime victory by 3 points, it’s awfully tempting to say, “I predicted this”, and if you look at the teams I’ve  favored, to this point* the streak of picks is 6-0. Let me point out though, that you can make a limiting assumption and from that assumption figure out how accurate I should have been. The limiting assumption is to assume the playoff model is 100% accurate** and see how well it predicted play. If the model is 100% accurate, the real results and the predicted results should merge.

I can tell you without adding up anything that only one of my favored picks had more than a 70% chance, and at least two were around 52-53%. So 6 times 70 percent is 4.2, and my model, in a perfect world, should have picked no more than 4 winners and 2 losers. A perfect model in a probabilistic world, where teams rarely have 65% chances to win, much less 100%, should be wrong sometimes. Instead, so far it’s on a 6-0 run. That means that luck is driving my success so far.

Is it possible, as I have argued, that strength of schedule is an under appreciated playoff stat, a playoff “Moneyball” stat, that teams that go through tough times are better than their offense and defensive stats suggest? It’s possible at this point. It’s also without question that I’ve been lucky in both the 2012 playoffs and the 2013 playoffs so far.

Potential Championship Scenarios:


Conference Championship Possibilities
Home Team Visiting Team Home Win Pct Est. Point Spread
NE BAL 0.523 0.7
HOU BAL 0.383 -3.5
ATL SF 0.306 -6.1
SF SEA 0.745 7.9


My model likes Seattle, which has the second best strength of schedule metric of all the playoff teams, but it absolutely loves San Francisco. It also likes Baltimore,  but not enough to say it has a free run throughout the playoffs. Like many modelers, I’m predicting that Atlanta and Seattle will be a close game.


+ I should also mention  that Bryan  Broaddus tweeted about a colleague of his who predicted a BAL victory.

* Sunday, January 13, 2013, about 10:00am.

** Such a limiting assumption is similar to assuming the NFL draft is rational; that the customers (NFL teams) have all the information they should, that they understand everything about the product they consume  (draft picks), and that their estimates of draft value thus form a normal distribution around the real value of draft picks, and that irrational exuberance, or trends, or GMs falling in love with players play no role in picking players. This, it turns out, makes model simulations much easier.

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.

Which of these players was drafted at a premium?

Sebastian Vollmer, drafted in the seond round in 2009.
Wikimedia image.

Derrick Burgess
Second round choice by Philadelphia in 2001.
Wikimedia image by BrokenSphere.

In my  mind, the answer is “both of them”.

One of the meatier passages in War Room comes in chapter 14, where Bill Belichick discusses the thought processes behind his selection of Sebastian Vollmer in 2009:

“Sebastian Vollmer is a good example”, he says of the Patriots’ starting right tackle, one of the team’s four second-rounders in ’09. “There’s no way he was really a second-round pick. Based on film or really based on the player he was at the end of the ’08 season. You know, East-West game and all  that. We knew there would be an undertow of Vollmer. And it was just a question of, ‘When’s this guy going to  go?’

“He should have been a fourth or fifth-round pick, by the film, by his performance. But  you saw him as an ascending player and he had rare size, and  there were a lot of things that you had to fix and all that. But it was clear the league liked him. Now,  the question is always, “How much do  they like him and where are they willing to buy?’ I’m sure for some teams it was the fourth round. For some teams it was the third round. But we just said, ‘Look we really want this guy. This is too high to pick him, but if we wait  we might not get him, so we’re going to  step up and take him.’

“And sometimes when you do that  you’re right and sometimes when you do  that  you’re wrong and everybody looks at you like, ‘Damn, you could have had him in the fourth.’

The Patriots aren’t the only team that practices the overdraft or the premium draft. If the Eagles really like someone, they tend to take them a round ahead of where he is commonly valued. Odd that teams that maintain plenty of draft picks practice this.  Offhand, I can recall the Eagles doing this for Derrick Burgess (generally viewed as a fourth rounder). The Steelers have done this as well;  they drafted Casey Hampton a full round above his common valuation.

In the 2012 draft class, players who appear to be attracting premium attention (we’re a day before the draft, mind you) are Ryan Tannehill (late first by talent, thought to be going to Miami at #8), Stephon Gilmore (drafted #3 in a mock draft by Greg Cosell), Fletcher Cox (mid first talent, seen as high as #5 in respectable mocks), Kevin Zeitner (mid second round talent, often in mocks with Pittsburgh in the first round), Chandler Jones (appearing in the first in some mocks), and Mark Barron (some people claim he’s the #7 now, often ranked as a mid first rounder).

If you feel you need the player, sometimes you have to just go out and get him.

I picked up this book after Greg Cosell gave it a big thumbs up on Rob Rang and Doug Farrar‘s radio show for KJR in Seattle, curious what it might actually say about the NFL draft.

Turns out this book is an update and rewrite of his earlier book, Patriot Reign, and for 11 of the chapters of this book, really has almost nothing to do about the draft, other than teasers spiked throughout the work. One interesting comment about the draft ranking system implemented by Belichick goes:

One of the things that made the system different was that it absolutely required a scout to know his college area or region of coverage in addition to each member of the Patriots’ fifth-three man roster. All reports, without exception, were comparative, and were based on what a given prospect could do vs. any current Patriot playing his position.

As a book, it initially has no sense of overarching storyline, content to wander about the narrative landscape the way a 60 year old grandfather would, telling one story in deep depth and then switching abruptly to another. It follows a variety of points of view. They all do not make much sense until you get to the end, where Michael actually starts talking more in depth about the draft in chapter 12. It finally becomes clear that he has three points of view, all intertwined, that of Belichick, that of Thomas Dimitroff, GM of the Atlanta Falcons, and that of Scott Pioli, GM of the Kansas City Chiefs. But to get there, to the three chapters of new material, he has you read about 11 chapters that I suspect were mostly all told in Patriot Reign.

Disturbing is the often myopic point of view of the book. Most notable in this regard is the coverage of Spygate, which can be summarized as (A) It was all Eric Mangini’s fault (B) Everybody does it and (C) People are picking on us needlessly and hurtfully. It’s in these segments where the book descends even from rambling history and becomes a fanboy lament. When you have to complain, in Poor Poor Pitiful Me fashion, about Gregg Easterbrook talking you down – in football terms, a comic, mind you – then you really do need to step out of the narrative a while and reexamine the facts. Tom, of the blog Residual Prolixity, puts it this way:

There are also a couple things Holley doesn’t seem to get, either from a Boston-centric viewpoint or they’re not obvious and nobody actually bothered to explain them to him, with the foremost example in my mind that Spygate (covered only briefly) exacerbated an existing anti-Boston sentiment arising from a belief that the Patriots were willing to push to the edge of the rules and beyond, if they could get away with it, which they could (see increase in illegal contact penalties, 2004, post Colts-Patriots).

All that said, once you get to Chapter 12, there are three chapters of useful insider stuff on how three teams conduct their draft. The background info on Dimitroff and Pioli are good enough to be useful to fans of the Falcons and Chiefs. Just, the new stuff isn’t substantial enough to be a book on its own – more like a long extended article in the New Yorker or the Washington Post. But, book sales being what they are, the new stuff was tacked onto the old stuff and sold as an entirely new product.

Up to you, whether you should read it. It can be interesting given the limitations of the material. Scaled in the measure of a draft pick, this is day two material.

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