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Expected Playoff Games Played

Projected playoff fantasy points based on expected number of games played.

In playoff fantasy football, predicting the correct number of games played for each team is paramount. This article, now in its fourth year, uses statistics to do just that. If you're unfamiliar with how my system works, click on any (or all) of the following links to the previous installments:

The Cliffs NotesTM version is that I use win probabilities published by Fivethirtyeight.comFootball OutsidersVegas, and Pro Football Reference to calculate how many games a given team can be expected to play according to math and statistics. I used to use ESPN Stats & Info's, but they're no longer giving details with respect to each team's probability of a conference championship appearance or conference championship; which is kind of important for the math. Thererfore, I've replaced them with Pro Football Focus, who is newly obliged in that regard.


Below is a table showing my games played expectations for each team in this year's playoffs:

TEAM (SEED)P(1)P(2)P(3)P(4)Exp GAdj Exp G
NE (AFC1) 17.6% 25.0% 57.4% 0.0% 2.40 2.97
NO (NFC4) 35.0% 35.4% 16.4% 13.2% 2.08 2.21
PIT (AFC2) 26.5% 43.9% 29.6% 0.0% 2.03 2.33
LAR (NFC3) 40.9% 34.2% 11.4% 13.5% 1.98 2.11
MIN (NFC2) 37.7% 29.4% 33.0% 0.0% 1.95 2.28
KC (AFC4) 29.6% 53.2% 11.4% 5.7% 1.93 1.99
JAX (AFC3) 29.9% 52.9% 12.5% 4.7% 1.92 1.97
PHI (NFC1) 43.9% 26.6% 29.6% 0.0% 1.86 2.15
ATL (NFC6) 59.1% 25.5% 9.2% 6.2% 1.62 1.69
CAR (NFC5) 65.0% 23.3% 7.4% 4.2% 1.51 1.55
TEN (AFC5) 70.4% 24.6% 4.0% 1.1% 1.36 1.37
BUF (AFC6) 70.1% 25.2% 3.5% 1.1% 1.36 1.37

Quickly for newcomers, P(1) means "the probability of playing exactly one game," P(2), means "the probability of playing exactly two games," and so on. EXP G is the number of expected games, and ADJ EXP G is the number of expected games if you're playing in a contest where the Super Bowl counts double.

The clear discrepancy between seeding and expected games comes in the NFC, where the Saints and Rams both have higher projections than the higher-seeded Vikings and (especially) Eagles. One could argue that this is just a byproduct of Philadelphia and Minnesota not having the possibility of playing more games by definition due to their first-round byes. However, if that were indeed the case, we'd see the same phenomenon with respect to the AFC's Top 2 seeds; but we don't. Instead, the key factor here is that Los Angeles (24.9%) and New Orleans (29.6%) have considerably higher probabilities of reaching the NFC Championship game than Jacksonville (17.2%) and Kansas City (17.1%) have of reaching the AFC Championship game. Stated differently, the various statistical models project New England and Pittsburgh to be large favorites in the divisional round, whereas Philadelphia and Minnesota not so much.

It's worth noting, however, that the above phenomena almost completely disappears in playoff contests that award double points for the Super Bowl. As the "Adj Exp G" column shows, once you add in Philadelphia and Minnesota's higher chances of playing exactly three games (i.e., making the Super Bowl), all four teams end up within 0.17 total games of each other.

If I could sum up this entire discussion, it would be to say that the outcome of your playoff league is likely to be decided in the NFC Divisional round.

Well actually, there's one other factor that your league likely hinges on: the performance of the New England Patriots. Their 2.40 expected games and 2.97 adjusted expected games are the second-most since I debuted this article four seasons ago. Ditto their 0.32 expected games advantage over any other team. And what team are the 2017 Patriots second to in these rankings? The 2016 New England Patriots, who had expectations of 2.45 games and 3.05 adjusted games, as well as a 0.38 expected game advantage over the second-highest team.

The importance of New England, New Orleans, and Los Angeles is why, in my contribution to the Footballguys staff playoff predictions, which are a part of the input for our Playoff Excel App, I went with a Saints-Rams NFC Championship game and the Patriots defeating the Saints in Super Bowl LII.


As always, I've used the expected game totals above to calculate expected FFPC points for both standard (EXP PTS) and "Super Bowl counts double" (ADJ EXP PTS) contests. For the majority of players, I've simply multiplied their scoring averages over Weeks 13-16 by the expected games total for their team. The exceptions are players for which their Week 13-16 scoring averages were either unsustainable or had been affected by injuries or playing time anomalies. In their cases, I did as much research as possible to use the most representative scoring averages I could to thereby produce my best approximations of their expected points. (And truth be told, this year required much more "approximation" than years past.)

As an example of unsustainability, I used Todd Gurley's full-season average of 25.8 points instead of his 36.2 points per game in Weeks 13-16. As an example of a current injury, I decided that DeMarco Murray isn't coming back from a torn MCL by the Divisional round, so I've allocated his full 9.7-point average to Derrick Henry, for a total of 18.2 points per game. This may seem too generous, but Henry scored 18.7 points with the full workload in a meaningful game against a playoff team just last week. Another injury example involved having to adjust for the uncertainty surrounding LeSean McCoy this week. Finally, there have been a ton of injury-related playing time anomalies since Week 13. Two quick examples involved 1) figuring out New England's "typical" backfield usage/production when all three heads of the monster are healthy; and 2) figuring out snap-, alignment- and target-usage in Jacksonville in the event that they have their Top 4 wide receivers healthy for the first time in months.

For your convenience, I've highlighted in bold, blue font those players I adjusted due to Week 13-16 unsustainability and highlighted in bold, red font those players I adjusted due to injuries/playing time anomalies since Week 13. (Important note: This color-coding is only to inform you who I adjusted and why; they could be either higher or lower. For example, Zay Jones' scoring in Weeks 13-16 was unsustainably low for a wide receiver that played around 80 percent of snaps (1.1 points per game), so I bumped him up slightly to his post-bye average of 4.5 points per game.) As always, feel free to move these players up or down in your rankings if you disagree with my adjustments:

PlayerPosTeamExp PtsAdj Exp Pts
Ben Roethlisberger QB PIT 49.2 56.4
Alex Smith QB KC 47.1 48.5
Tom Brady QB NE 37.2 46.1
Case Keenum QB MIN 37.0 43.3
Jared Goff QB LAR 39.4 42.1
Drew Brees QB NO 38.1 40.6
Blake Bortles QB JAX 37.5 38.4
Cam Newton QB CAR 34.4 35.4
Nick Foles QB PHI 26.0 30.1
Matt Ryan QB ATL 22.9 23.8
Marcus Mariota QB TEN 21.2 21.4
Tyrod Taylor QB BUF 21.0 21.2
Todd Gurley RB LAR 51.0 54.5
LeVeon Bell RB PIT 46.8 53.6
Kareem Hunt RB KC 44.6 45.9
Alvin Kamara RB NO 44.5 47.4
Mark Ingram RB NO 44.2 47.0
Rex Burkhead RB NE 41.1 51.0
Leonard Fournette RB JAX 35.1 36.0
Dion Lewis RB NE 31.2 38.6
Devonta Freeman RB ATL 25.3 26.2
Jerick McKinnon RB MIN 24.7 28.9
Derrick Henry RB TEN 24.6 24.8
Christian McCaffrey RB CAR 21.7 22.3
Latavius Murray RB MIN 20.8 24.3
Jay Ajayi RB PHI 19.9 23.0
Jonathan Stewart RB CAR 17.4 17.9
T.J. Yeldon RB JAX 17.0 17.4
LeSean McCoy RB BUF 16.9 17.1
Tevin Coleman RB ATL 14.2 14.8
James White RB NE 13.7 17.0
Charcandrick West RB KC 9.6 9.9
Marcus Murphy RB BUF 9.2 9.3
Corey Clement RB PHI 8.7 10.1
Mike Tolbert RB BUF 5.9 5.9
LeGarrette Blount RB PHI 5.3 6.2
Antonio Brown WR PIT 41.2 47.2
Michael Thomas WR NO 33.7 35.8
Brandin Cooks WR NE 31.9 39.5
Tyreek Hill WR KC 31.7 32.6
JuJu Smith-Schuster WR PIT 28.8 33.1
Robert Woods WR LAR 28.6 30.6
Cooper Kupp WR LAR 27.3 29.1
Keelan Cole WR JAX 27.1 27.6
Stefon Diggs WR MIN 24.5 28.6
Nelson Agholor WR PHI 23.4 27.1
Dede Westbrook WR JAX 23.2 23.8
Danny Amendola WR NE 22.4 27.7
Martavis Bryant WR PIT 21.8 25.0
Adam Thielen WR MIN 20.5 24.0
Julio Jones WR ATL 20.1 20.9
Chris Hogan WR NE 19.7 24.4
Sammy Watkins WR LAR 19.4 20.7
Alshon Jeffery WR PHI 19.1 22.2
Ted Ginn WR NO 18.7 19.9
Mohamed Sanu WR ATL 16.0 16.6
Rishard Matthews WR TEN 15.0 15.1
Allen Hurns WR JAX 14.5 14.8
Devin Funchess WR CAR 14.3 14.7
Torrey Smith WR PHI 13.5 15.7
Eric Decker WR TEN 13.2 13.3
Albert Wilson WR KC 13.0 13.4
Kelvin Benjamin WR BUF 13.0 13.1
Corey Davis WR TEN 10.2 10.3
Marqise Lee WR JAX 10.2 10.7
Kaelin Clay WR CAR 9.8 10.0
Brenton Bersin WR CAR 8.5 8.8
Deonte Thompson WR BUF 8.2 8.3
Brandon Coleman WR NO 7.6 8.1
Zay Jones WR BUF 6.2 6.2
Willie Snead WR NO 5.7 6.1
Justin Hardy WR ATL 5.4 5.6
Taylor Gabriel WR ATL 5.3 5.5
Rob Gronkowski TE NE 44.5 55.2
Travis Kelce TE KC 36.5 37.6
Zach Ertz TE PHI 33.7 39.1
Kyle Rudolph TE MIN 21.0 24.5
Greg Olsen TE CAR 19.3 19.8
Delanie Walker TE TEN 19.2 19.3
Vance McDonald TE PIT 17.8 20.4
Charles Clay TE BUF 11.7 11.8
Marcedes Lewis TE JAX 11.6 11.9
Trey Burton TE PHI 11.5 13.4
Jesse James TE PIT 10.6 12.1
Austin Hooper TE ATL 9.1 9.4
Dwayne Allen TE NE 8.3 10.3
James OShaughnessy TE JAX 7.6 7.8
Josh Hill TE NO 7.5 8.0
Gerald Everett TE LAR 5.8 6.2
Tyler Higbee TE LAR 4.6 4.9
Nick OLeary TE BUF 3.9 4.0