Philadelphia Eagles

The methodology of this work is described here.

This year, the formulas favor the Baltimore Ravens and the Seattle Seahawks. Baltimore has the advantage in any possible encounter in the AFC. Seattle has the advantage over any team not named the New Orleans Saints. As the Saints lose their HFA against Green Bay, they are not favored against Green Bay. The odds of a Seattle-New Orleans matchup are small.

2019 NFL Playoff Teams, C&F Worksheet.
Rank Name Home Field Adv Playoff Experience SOS Total Score
1 San Francisco 49ers 0.660 0 0.125 0.785
2 Green Bay Packers 0.660 0.747 -0.225 1.182
3 New Orleans Saints 0.660 0.747 0.015 1.422
4 Philadelphia Eagles 0.660 0.747 -0.511 0.896
5 Seattle Seahawks 0.0 0.747 0.690 1.376
6 Minnesota Vikings 0.0 0.747 -0.334 0.413
1 Baltimore Ravens 0.660 0.747 0.015 1.422
2 Kansas City Chiefs 0.660 0.747 0.061 1.468
3 New England Patriots 0.660 0.747 -0.535 0.872
4 Houston Texans 0.660 0.747 0.292 1.699
5 Buffalo Bills 0.0 0.747 -0.380 0.367
6 Tennessee Titans 0.0 0.747 -0.310 0.437


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.

Because the worksheet above can be hard to decipher, for the first week of the 2019 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
New Orleans Saints Minnesota Vikings 1.009 0.733 7.5
Philadelphia Eagles Seattle Seahawks -0.541 0.368 -4.0
New England Patriots Tennessee Titans 0.435 0.607 3.2
Houston Texans Buffalo Bills 1.332 0.791 9.9

It’s a new playoff season, and another time to try our new playoff formulas. Methodology of this work is described in depth here.

The playoff formulas like New Orleans and Kansas City. They like Baltimore, but Baltimore, which will lose home field after the first round, is unlikely to be favored after that point. The formulas place a substantial penalty on the lack of playoff experience, and so does not favor Chicago, the Chargers, or the Colts. Update: Baltimore has not been in the playoff since 2014, and so the results have been amended.

2017 NFL Playoff Teams, C&F Worksheet.
Rank Name Home Field Adv Playoff Experience SOS Total Score
1 New Orleans Saints 0.660 0.747 0.192 1.599
2 LA Rams 0.660 0.747 -0.134 1.273
3 Chicago Bears 0.660 0.0 -0.711 -0.051
4 Dallas Cowboys 0.660 0.747 0.046 1.453
5 Seattle Seahawks 0.0 0.747 -0.170 0.577
6 Philadelphia Eagles 0.0 0.747 0.167 0.914
1 Kansas City Chiefs 0.660 0.747 -0.033 1.374
2 New England Patriots 0.660 0.747 -0.535 0.872
3 Houston Texans 0.660 0.747 -0.465 0.942
4 Baltimore Ravens 0.660 0 0.195 0.855
5 LA Chargers 0.0 0.0 -0.070 -0.070
6 Indianapolis Colts 0.0 0.0 -0.693 -0.693

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.

Because the worksheet above can be hard to decipher, for the first week of the 2018 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
Chicago Bears Philadelphia Eagles -0.965 0.276 -7.1
Dallas Cowboys Seattle Seahawks 0.876 0.706 6.5
Houston Texans Indianapolis Colts 1.635 0.836 12.1
Baltimore Ravens LA Chargers 0.925 0.716 6.8


But to summarize, the formulas used here were found by logistic regressions and each element in the formula has a playoff significance of 95%. I promise if the more common offense metrics could say that, they would. I’ll also note that in vogue stats like FPI don’t really give answers markedly different from other common offensive metrics, such as Pythagorean expectation.

That said, offensive metrics like Pythagorean Expectation favor Seattle over Dallas by about half a point, or 52% win probability for Seattle. Offensive stats still favor Baltimore, but not as much. Simple Ranking stats favor Chicago by around 8 points, circa 75% WP. Houston-Indianapolis have approximately even offensive stats, so the difference between the teams is about 3 points. HFA is worth a bit more in the playoffs, circa 63%.

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

Summary: Replacing Wentz with Foles removes about 6.5 points of offense from the Philadelphia Eagles, turning a high flying offense into something very average.

Last night the Atlanta Falcons defeated the LA Rams. Now we’re faced with the prospect of the Falcons playing the Eagles. I have an idiosyncratic playoff model, one I treat as a hobby. It is based on static factors, the three being home field advantage, strength of schedule, and previous playoff experience. And since it values the Eagles as 0.444 and the Falcons as 1.322, the difference is -0.878 (win probability in logits). The inverse logit of -0.878 is 0.294, which is the probability of the Eagles winning, and an estimated point spread would be a 6.5 point advantage for the Falcons.

Another question that a Falcons or Eagles fan might have is how much is Carson Wentz worth as a QB, in points scored? We can use the adjusted yards per attempt stat of Pro Football Reference to estimate this, and also to estimate how much Carson Wentz is better than Foles. We have made these kinds of analyses before for Matt Ryan and Peyton Manning.

Pro Football Reference says that Carson Wentz has a AYA of 8.3 yards per attempt. Nick Foles has a AYA of 5.4. Now lets calculate the overall AYA for every pass thrown in the NFL. Stats are from Pro Football Reference.

(114870 yards + 20*741 TDs – 45*430 Ints) / 17488 Attempts
(114870 yards + 14820 TD “yards” – 19350 Int “yards”) / 117488 Attempts
110340 net yards / 17488 yards
6.31 yards per attempt to three significant digits

So about 6.3 yards per attempt. Carson Wentz is 2 yards per attempt better than the average. Nick Foles is 0.9 yards less than the average. The magic number is 2.25 which converts yards per attempt to points scored per thirty passes. So Carson, compared to Foles, is worth 2.9 * 2.25 = 6.5 points per game more than Foles, and 4.5 points more than the average NFL quarterback.

This doesn’t completely encompass Carson Wentz’s value, as according to ESPN
‘s QBR stat
, he account for 10 expected points on the ground in 13 games, so he nets about 0.8 points a game on the ground as well.

Now, back to some traditional stats. The offensive SRS assigned to Philadelphia by PFR is 7.0 with a defensive SRS of 2.5. If Carson Wentz is worth between 6.5 and 7.3 points per game, then it reduces Philadelphia’s offense to something very average, about 0.5 to -0.3. That high flying offense is almost completely transformed by the loss of their quarterback into an average offense.

Note: logits are to probabilities as logarithms are to multiplication. Rather than multiplying probabilities and using transitive rules, you just add the logits and convert back. Logarithms allow you to add logarithms of numbers rather than multiplying them.

I didn’t expect another trade of this magnitude, and so quickly. But let’s crunch the numbers on this trade, and compare them to the 2016 Titans-Rams trade.

The Browns received from the Eagles, the #8, #77 and #100 picks in this draft. In 2017 they receive the Eagles first round pick. In 2018 they receive the Eagles 2nd round pick. The Eagles have received the #2 pick in this draft, and the Browns 4th round pick in 2017.

For the purposes of this calculation, we assume the Eagles will pick 20th in 2017 and 2018, and that the Brown in 2017 will rise from 2nd to 10th.


The AV costs of the 2016 Eagles Browns trade.
Eagles Browns Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
2 46 8 40
(138) 8 77 12
100 17
(20) 29
(52) 22
Total 54 Total 120
66 2.22


The Delta AV for both trades are the same, but since the Eagles received a lot less AV, the relative ratio of AV given to AV received is higher. The trade cost is the same, but the purchase is more highly leveraged.

I’ve been reading a ton of books. One of these is Robert W. Peterson’s “Pigskin”, which has been an interesting read so far. I’m roughly in the late 1940s in this book, which starts with the beginning of professional football and ends with the NFL championship in 1958. What has caught my eye are Mr. Peterson’s comments about the spread of the T formation in the 1940s. He describes the Bears 73-0 NFL Championship victory over the Redskins. Later, when describing the switch of the Redskins to the T in 1944, he gives this accounting of the state of the football world in 1944: (1)

By that year, more than 50 percent of college teams has converted to the T formation. So had most pro teams. Henceforth, the old single-wing formula of “three yards and a cloud of dust” as the ideal offensive play would go the way of the rugby ball in pro football

The adoption was not immediate upon the end of the 1940 season, however, and teams, coaches, and whole conferences that were successful with the single wing (or Southwestern spread) tended to stick with it. For example, in Tom Landry’s autobiography, he notes that Texas made the switch in 1947, after Dana Bible retired.(2) Y. A. Tittle’s memory of the conversion is (3)

If I remember correctly, the first Southwestern conference team to switch to the T formation from the single- and double-wing formations was Rice University, followed by Georgia and Louisiana State.

The quote above mixes the SEC and the Southwest conference, but still.. LSU switched in 1945. I’m just not sure which of the 50% of college football teams were converting. Army and Notre Dame are well known early adopters, but as a counterexample, in 1947, Fritz Crisler won a national championship with a single wing offense at Michigan.

Dan Daly, when discussing the effects of the 73-0 Bears win over the Redskins, noted:(4)

Only one other NFL team, the Philadelphia Eagles, switched to the T the next season. And as late as 1944, both clubs that played in the championship game, the Green Bay Packers and the New York Giants, used the single wing or some variation.

Paul Brown, the head coach of Ohio State from 1941 to 1943, was the first coach to see Don Faurot’s split T in action, in his very first game as Ohio State’s head coach, but then says of his game with Clark Shaughnessy’s Pittsburgh squad in 1943 (5)

It was my first real look at the T formation with flankers and men in motion, however, and it was the kind of football I later assimilated into my own system with the Browns.

So from 1941 to 1943, the “Bears” T was largely unknown in the Big 10. Paul Brown then learned the T while serving in the armed services. In 1946 and 1947, in the first two AAFC championships, Brown’s T was pitted against the single wing offense of the New York Yankees.(6)

As Dan Daly notes, the lack of players trained in the new offense slowed the T formation’s spread.(7)

In the early ’40s, the Bears and the Eagles – the only two T-formation teams – drafted an unusual number of Shaughnessy’s Stanford players because the Cardinal were the lone major college team using the offense.

Dan Daly later writes (8)

By the end of the decade, though, five out of seven college teams played some form of the T. Suddenly it was the single-wing Steelers who were having trouble finding players to fit their system.

And it does make sense. There were some early adopters who ran into Luckman, or Shaughnessy, or former Bears quarterbacks and coaches, but a lot of coaches learned the T while serving in the armed services during the war, coaching or playing in service teams. So it wasn’t the early 1940s when the transition occurred, as far as I can tell. Instead, it was the mid to late 1940s when the T became dominant. The conversion was not “immediate”. It took 3-4 years to gain steam, and a decade for it to dominate.


There were only ten pro teams in 1944, and it’s entirely possible that most NFL teams were running a T by 1944 (By my count, Chicago, Philadelphia, Washington, and Cleveland are using the T by 1944. Green Bay and New York are not. The other four – Brooklyn, Boston, Detroit, and Card-Pitt – I’m not sure of). Green Bay switches to the T in 1947, New York in 1949.

Army’s first use of the T is in the 1941 Army-Navy game.(9) Notre Dame had Halas’s players assist with the conversion in 1942. Clark Shaughnessy coaches Maryland in 1942 and then Pittsburgh in 1943.

1944 is an unusual year to use as a baseline, because so many coaches and players were in the armed services. That may in fact have aided the transition, as so many coaches with a traditional single wing background found themselves coaching alongside experts in the T on service teams.

For those who have never read Ron Fimrite’s article in Sports Illustrated about the Stanford Indians’ 1940 season, just do it. It’s one of the great short articles on football. The link is given in the bibliography.


1. Peterson, Chapter 8.

2. Landry and Lewis, p. 74.

3. Tittle, Chapter 5.

4. Daly, Chapter 3.

5. Brown and Clary, p. 101.

6. Brown and Clary, pp. 181-182.

7. Daly, Chapter 3.

8. Daly, Chapter 3.

9. Roberts, Chapter 2.


Brown, Paul, and Clary, Jack, PB: The Paul Brown Story, Atheneum 1980.

Daly, Dan, The National Forgotten League: Entertaining Stories and Observations from Pro Football’s First Fifty Years, University of Nebraska Press, 2012. [ebook]

Fimrite, Ron, “The Melding of All Men, Suited to a T”, September 5, 1977. “Sports Illustrated”. retrieved July 28, 2013.

Holland, Gerald, “The Man Who Changed Football”, February 3, 1964. Sports Illustrated. retrieved July 28, 2013.

Johnston, James W. ,The Wow Boys: A Coach, a Team, and a Turning Point in College Football , University of Nebraska Press, 2006.

Landry, Tom, and Lewis, Gregg,Tom Landry: An Autobiography, Harper Paperbacks, 1990.

McGarr, Elizabeth, “The Top 20 Greatest Moments”, August 20, 2008. “Sports Illustrated”. retrieved July 28, 2013.

Peterson, Robert W., Pigskin: The Early Years of Pro Football, 1997. [ebook]

Roberts, Randy, A Team for America: The Army-Navy Game That Rallied a Nation at War , Houghton Mifflin Harcourt, reprint ed 2011. [ebook]

Tittle, Y. A, and Clark, Kristine S.,Nothing Comes Easy: My Life in Football ,Triumph Books, 2009. [ebook]

Zimmerman, Paul, in “Letters”, December 22, 1997. “Sports Illustrated”. retrieved July 28, 2013.

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