Super Bowl Leverage And the Best Postseason Passers Since 1966

Even for Football Perspective, this is a very math-heavy post. I’ve explained all the dirty work and fine details behind this system, but if you want to skip to the results section, I’ll understand. Heck, it might even make more sense to start there and then work your way back to the top.

Background

In 2012, Neil Paine wrote a fascinating article on championship leverage in the NBA, building on Tom Tango’s work on the same topic in Major League Baseball. Championship Leverage was borne out of the desire to quantify the relative importance of any particular playoff game. Truth be told, this philosophy has more practical application in sports where each playoff round consists of a series of games. But Neil applied this system to the NFL playoffs and crunched all the data for every playoff game since 1965. Then he was kind enough to send it my way, and I thought this data would make for a good post.

The best way to explain Championship Leverage is through an example. For purposes of this exercise, we assume that every game is a 50/50 proposition. At the start of the playoffs, the four teams playing on Wild Card weekend all have a 1-in-16 chance of winning the Super Bowl (assuming a 50% chance of winning each of four games). This means after the regular season ended, the Colts had a 6.25% chance of winning the Super Bowl. After beating Kansas City, Indianapolis’ win probability doubled to 12.5%. Win or lose, the Colts’ Super Bowl probability was going to move by 6.25%, a number known as the Expected Delta.

New England, by virtue of a first round bye, began the playoffs with a 12.5% chance of winning the Lombardi. With a win over Indianapolis, the Patriots’ probability of winning the Super Bowl jumped 12.5% to 25%; had New England lost, the odds would have moved from 12.5% to zero. Therefore, the Expected Delta in a Division round game is 12.5%.

By beating Indianapolis, New England set up a crucial showdown with Denver. A win would again double the Patriots’ Super Bowl odds, this time from 25% to 50%, while a loss would drop it to zero. In the conference championship round, the Expected Delta is always 25%.

Denver also started the playoffs with a 12.5% chance of winning the Super Bowl, since the Broncos don’t get any extra credit for rostering Peyton Manning. Those odds jumped to 25% after beating San Diego and up to 50% after beating the Patriots. The Super Bowl, of course, has an Expected Delta of 50%. After the game, Denver’s odds of being Super Bowl champs will have moved 50% to either 100% or 0%.

There are 11 games (or 22 if you look at each game as one game for each team) in every NFL postseason, at least since 1990. The final game has an Expected Delta of 50%; the previous two each have an Expected Delta of 25%; the four before that each have an Expected Delta of 12.5%; and the first four each have an Expected Delta of 6.25%. This means, on average, each playoff game in the NFL has an average Expected Delta of 15.91%.

[math]( 4 * .0625 + 4 * .0125 + 2 * .25 + 1 * .50 )/11 = .1591[/math]

This means that the Super Bowl — with an Expected Delta of .50 — is 3.14 times as “important” as the average playoff game. That importance is what we call the Leverage Index, and at least since 1990, each Super Bowl has had a Leverage Index of 3.14. Peyton Manning’s performance against Seattle comes with a Leverage four times as great as Manning’s game against San Diego, because the stakes are four times as high. I’m reticent to ever type the word clutch, but using this method, we can at least quantify the stakes for each game.

Calculating a Quarterback’s Leverage-Adjusted Postseason Value

We can use this metric to grade each individual postseason by a quarterback after accounting for Leverage. For each game in the Super Bowl era, Neil calculated the Adjusted Net Yards per Attempt average allowed by each defense during the regular season, and then gave each quarterback credit (or blame) for his ANY/A average relative to that particular defense. By using this method, we have both an era and SOS adjustment all in one. Then, each quarterback’s production is adjusted for leverage. Let’s work through an example.

Warner was dominant in the 2008 postseason.

In the first round of the 2008 playoffs, Kurt Warner faced the Atlanta Falcons, who allowed an average of 5.96 ANY/A during the regular season. Warner produced a 19/32-271-2-1 (0-0) sack line, meaning he completed 19 of 32 passes for 271 yards, threw two touchdowns and one interception, and was not sacked. That gave Warner an ANY/A average of 8.31, 2.35 ANY/A better than we would expect (based on the Atlanta defense). Of course, this was not a particularly significant game: the leverage was only 0.39.

The following week, Warner went 21/32-220-2-1 (1-5) against the Panthers. Carolina allowed 5.43 ANY/A during the regular season, and Warner averaged 6.36 ANY/A in this game, giving him 0.93 ANY/A over expectation. The leverage was 0.79.

In the conference championship game, Warner faced an Eagles defense that allowed only 4.57 ANY/A during the regular season, but he went 21/28-279-4-0 (2-12); that works out to an 11.57 ANY/A average, giving him an incredible 7.00 ANY/A better than average in a game with a leverage of 1.57.

Then, in the Super Bowl, Warner was again outstanding. The Steelers defense allowed only 3.17 ANY/A to opposing quarterbacks during the regular season but Warner (31-43-377-3 (2-3), an 8.64 ANY/A average) was 5.47 ANY/A better than that against Pittsburgh. The Super Bowl, of course, has a leverage of 3.14.

All told, Warner had 140 attempts (including sacks). On average, each pass attempt came in a game with a Leverage of 1.62 (Warner’s four games, by definition, had Leverages of 0.39, 0.79, 1.57, and 3.14; that would give him a simple average of 1.47, but since he threw 12 more passes in the Super Bowl than in any other game, his weighted average leverage is a bit higher.) If you multiply his attempts by his ANY/A over expectation by the leverage for each of the four games, and then divided that total by 1.62 (the average leverage for each attempt), you get 714, the amount of (leverage-adjusted) adjusted net yards over expectation Warner produced. That’s the most by any quarterback in a single post-season.

Here’s another way to think about it. Based on the defenses Warner faced, he would have been expected to produce a weighted average ANY/A (weighted for both SOS and Leverage) of 3.87; in reality, he produced a weighted ANY/A (again, weighted for Leverage) of 8.97. Therefore, Warner exceeded expectations by 5.10 ANY/A. Since he had 140 dropbacks, that gives him 714 adjusted net yards of value over average. The table below shows the top 100 postseasons by a quarterback (looking at only passing numbers) using this method:

The Best Single-Postseason Passing Performances From 1965 to 2012

RkQuarterbackTmYrGAttLevExp ANY/AAct ANY/AANY/A OvExValue
1Kurt WarnerARI200841401.623.878.975.1714
2Jim PlunkettOAK198041041.24.0610.596.54680
3Joe MontanaSFO19893851.684.4212.187.76658
4Jake DelhommeCAR200341101.573.739.345.61616
5Daryle LamonicaOAK19682890.852.819.146.33564
6Joe MontanaSFO19883961.754.039.785.75552
7Joe FlaccoBAL201241321.575.379.374528
8Troy AikmanDAL19923961.864.6410.135.49527
10Doug WilliamsWAS19873871.644.089.355.27458
11Aaron RodgersGNB201041401.594.67.813.21449
12Steve YoungSFO19943912.054.929.624.7426
13Joe MontanaSFO198431161.564.297.93.6418
14Peyton ManningIND200931321.834.427.473.04402
16Jim KellyBUF19903831.884.138.864.74393
17Jim McMahonCHI19853721.623.799.295.5393
18Phil SimmsNYG19863611.754.711.066.36388
19Kurt WarnerSTL199931241.935.118.213.1384
20Ken StablerOAK19763751.212.577.434.86364
21Bart StarrGNB19662591.083.229.356.13361
22Mark RypienWAS19913791.944.859.284.42350
23Jeff GeorgeMIN19992820.654.18.134.02330
24Jeff HostetlerRAI19932430.595.0112.637.62328
25John ElwayDEN19983901.874.718.343.63327
26Troy AikmanDAL19953841.814.918.663.75315
27Bernie KosarCLE19872741.093.878.094.22312
29Drew BreesNOR200931041.935.258.162.91303
30Drew BreesNOR201121120.625.027.692.67299
31Matt RyanATL20122781.224.798.613.82298
32Joe NamathNYJ19682811.492.335.973.64295
33Bart StarrGNB19673841.192.716.123.41286
34Colin KaepernickSFO20123851.855.578.923.34284
35Dan MarinoMIA198431201.814.096.432.34281
36Warren MoonHOU19912800.574.387.823.44275
37Roger StaubachDAL19753911.351.924.872.95269
38Kurt WarnerARI20092610.574.568.854.29262
39Ken StablerOAK19772780.852.736.073.34261
40Randall CunninghamMIN19972790.63.676.953.28259
41Brett FavreGNB19963782.054.677.993.31258
42Mark SanchezNYJ20103920.954.837.582.75253
44Brett FavreGNB199531080.974.97.212.31250
46Len DawsonKAN19693671.261.985.73.73250
47Dan FoutsSDG19802861.073.486.342.85245
48Ken AndersonCIN19813861.814.156.792.63226
49Joe TheismannWAS19824951.832.544.922.38226
50Brett FavreGNB199731031.984.26.382.18225
51John BrodieSFO19702750.911.894.832.94221
52Eli ManningNYG200741281.644.86.531.72220
53Erik KramerDET19912761.174.27.042.84216
54Dan MarinoMIA19942690.615.478.533.06211
55Daryle LamonicaOAK19672621.61.715.093.39210
56Kelly HolcombCLE20021450.394.799.424.63208
57Joe MontanaSFO19813951.474.436.622.19208
58Ken StablerOAK19742700.92.45.362.96207
59Aaron RodgersGNB20091470.395.089.344.26200
60Drew BreesNOR20062871.264.026.292.27198
61Joe MontanaSFO19902621.154.067.193.13193
64Troy AikmanDAL19933891.724.626.722.1188
65Roger StaubachDAL19773691.543.15.82.71188
66Peyton ManningIND200641591.514.095.261.17186
67Fran TarkentonMIN19733841.382.084.292.21185
69Ken StablerOAK19752680.961.934.612.68182
70Russell WilsonSEA20122690.615.818.432.62181
71Danny WhiteDAL198231020.854.065.781.72176
72Doug FlutieBUF19981390.393.578.054.48175
73Ken StablerOAK19732420.91.035.184.16175
74Peyton ManningIND20071480.794.127.753.63174
75Jim KellyBUF19891550.694.017.163.15173
76Neil O'DonnellPIT19942771.345.117.362.25173
77Joe MontanaSFO19832811.14.776.882.11171
78Mark MalonePIT19842661.074.386.922.54167
79Peyton ManningIND20042770.615.017.162.15166
80Lynn DickeyGNB19822630.774.427.052.63166
81Scott BrunnerNYG19812540.63.496.553.05165
82Bill NelsenCLE19692630.911.824.442.62165
83Joe FergusonBUF19741260.581.597.856.26163
84Ken AndersonCIN19751320.581.216.285.07162
85Jeff HostetlerNYG19903842.024.546.451.9160
86Matt HasselbeckSEA20102840.624.986.861.87157
87Rich GannonOAK20012620.64.647.162.52156
88Mark SanchezNYJ20093691.045.117.362.25155
89Kurt WarnerSTL2001311324.625.991.37155
90Ron JaworskiPHI19792670.563.545.822.29153
92Eli ManningNYG201141741.585.776.640.87151
93Rodney PeetePHI19952320.465.039.774.74151
94Johnny UnitasBAL19703611.163.796.242.45149
95Dan MarinoMIA19902810.634.676.451.78144
96Steve YoungSFO19922701.214.176.212.05143
97Don MeredithDAL19661330.751.926.244.32143
98Donovan McNabbPHI20022831.272.924.631.72142
99Roger StaubachDAL19783801.842.844.61.76142
100John ElwayDEN198631141.684.525.751.23140

Seeing Warner’s 2008 as the top postseason performance isn’t too surprising. What about Jim Plunkett’s 1980 season? Over four games, he had a 96.2 passer rating and averaged 9.1 yards per attempt while throwing for 7 touchdowns. Remember, this was 1980, not 2013: that year, Brian Sipe won the passer rating crown with a 91.4 rating. More importantly, Plunkett gets extra credit for being at his best in the biggest games. In the AFC Championship Game, he was 14/18 for 261 yards and 2 touchdowns. In the Super Bowl, he threw for 261 yards and 3 touchdowns on 21 passes. If the goal is to reward quarterbacks for being at their best in the most critical games, then Plunkett’s position at number two is legitimate.

Joe Montana’s magical 1989 is number three, and the only reason he’s behind Plunkett is because he had fewer attempts. Montana’s leverage-adjusted 7.76 ANY/A over expectation is the best performance in a postseason since 1965. Jake Delhomme’s presence at #4 might be surprising, but that’s a function of his production in a high-leverage situation against a great opponent. Forget the name, and consider that a quarterback ten years ago faced the #1 pass defense in the league (by ANY/A) and threw for 323 yards and 3 touchdowns with no interceptions on 33 pass attempts in the Super Bowl. Had Carolina won that game (and, perhaps, had Delhomme not subsequently imploded five years later), we might remember his 2003 playoffs the way we think of Joe Flacco’s 2012 postseason.

Working Through Another Example

Speaking of Flacco, I was a bit surprised he wasn’t in the top 3, but that’s essentially a function of the built-in era adjustment. Let’s go through this method using Flacco’s 2012 season, but using another method to get to the same result.

ELITE.

Flacco’s first game was against the Colts, who allowed 6.54 ANY/A during the regular season. If we multiply that number by the leverage (0.39) and his number of dropbacks (24), we get 61.66. In Denver, Flacco faced a team that allowed 4.87 ANY/A during the regular season. Multiply that number by the leverage (0.79) and dropbacks (35), and you get 133.85. In the AFC Championship Game, Flacco had 38 dropbacks against a team that allowed 6.31 ANY/A during the regular season; multiply those two numbers by the leverage (1.57) and you get 376.83. Finally, he faced the 49ers in the Super Bowl, and San Francisco allowed 4.88 ANY/A during the regular season. Flacco had 35 dropbacks in a game with massive leverage (3.14); the product of those three numbers is 536.91.

If you add up those four numbers – 61.66, 133.85, 376.83, and 536.91 — you get 1,109.26. Next, we divide that number by Flacco’s total number of dropbacks (132) to get 8.40. The last step is to divide that number by the average leverage of each pass Flacco attempted. Do the math, and that number is 1.57. Once you divide 8.40 by 1.57, you get the Expected (leverage-adjusted) ANY/A for Flacco during the post-season, which is 5.37. That’s a really high number, at least historically speaking, which simply reflects the fact that putting up good passing numbers was a lot easier in 2012 than it was in 1972. Flacco is essentially getting dinged for an era adjustment, but that’s appropriate.

How did Flacco actually do? He had an ANY/A of 12.88 against Indianapolis, 10.97 against Denver, 7.76 in New England, and 9.54 in the Super Bowl. Adjust for his number of attempts and leverage, and Flacco produced a leverage-adjusted ANY/A of 9.37. That’s also a hair lower than his non-leverage adjusted ANY/A of 10.02, which makes sense: his best game was against Indianapolis, the lowest-stakes game in which he played. Flacco was still great, but the leverage and the era combine to put him at “only” 4.00 ANY/A better than expectation.

You might be surprised that Tom Brady doesn’t fare all that well in this metric. In fact, he only has three top-100 seasons, and none in the top 40. Well, Brady’s never had one dominant postseason. His best year was in 2004, but even then, his numbers there look merely “very good” as opposed to historically great. Is his playoff reputation overrated? Perhaps. In Part II, I’ll show you the career playoff ratings.

I won’t pretend that the math involved isn’t overly complicated. But hey, Neil and I already did all the work for you. So what do you think of the list?

• James

This makes perfect sense to me! I’m glad you weighted everything according to the number of attempts as it’s much more representative that way! After all, Warner’s 45 dropbacks in the Super Bowl count a lot more than those 32 drop backs in the Wild Card round.

I’m also tickled to see that among these top 100 the two lowest ANY/A over expected postseasons are two Manning Super Bowls, but perhaps not the two you’d expect!

• Tim Truemper

Just some cursory observations. Only 17 of the top 100 are from the “dead ball” 1970’s. Not sure if this is disproportinate or not.

Of those 17, 12 are from Bradshaw (4), Staubach (3), and Stabler (5!). For the ’70’s, Tarkenton only once and no Bob Griese.

Was surprised not to see Chris Chandler for the 1998 season and Atlanta’s super bowl run. My impression was he had quite th hot streak to carry Atlanta that year. Guess I should check those box scores for the playoffs of that year.

Overall, an interesting metric that weights relative performance to game importance to generate the list.

• Just some cursory observations. Only 17 of the top 100 are from the “dead ball” 1970′s. Not sure if this is disproportinate or not.

I think there are 2 reasons.

1) From 1970-1979, there were only 74 playoff games played (an average of 7.4/season). But the playoffs expanded in the 70’s and 1990. So the decades of the 90’s had 110 playoff games (11 per season). The 80’s had 96 playoff games (9.6/season). So – there were just fewer QB’s playing postseason games in the 70’s.
2) The increase in games also increased the leverage of the later round games. So Bradshaw was at a handicap winning the Super Bowl in 1974, when there were zero wildcard games. (Again – this is pending a check on my math/understanding in another comment.)

• Chase, in the formula you posted above (4x.0625 + 2x.0125, etc…), why am I getting .1182 instead of .1591?

• Wes

It seems you may have used .0125 instead of .125?

• Richie

Yes, that was my error. Thanks.

• When the playoffs expanded in 1990, that increased the Super Bowl leverage index from 3.83 to 4.23. (Based on my math, which may be wrong.) Why should Joe Montana get less “credit” for winning the Super Bowl in 1989 than Jeff Hostetler got in 1990? (Regardless of my math, adding 2 games to the wild card round in 1990 should decrease the average delta, thereby increasing the leverage for any game with a delta above .0625.)

• That’a sort of the big question with a system like this… The reason we diminish the Super Bowl in the wild card era is because we want to maintain that relationship where the average leverage of a playoff game ALWAYS equals exactly 1.00. This is useful for a number of reasons, not least because it means the sum of leverages will always equal the number of playoff games played across the league. However, I can also appreciate the argument that the leverage of a Super Bowl should be constant across seasons, regardless of whether there was a wild-card game or not. Ideally, my way would work in concert with a regular-season leverage that quantifies the swings of every game in the entire season, playoffs or otherwise. Then it would be entirely self-contained, and more appropriate to set the average game to 1.00.

• Wes

The evolution of Wild Card games certainly puts a strange twist on leverage. From the above example, both Montana and Hostetler had first round byes, giving them seemingly the same odds of winning the Super Bowl, which they both did in 3 games. Yet, because of the format at the time, Hostetler gets some extra leverage. If there were 2 fewer Wild Card games in 1990, Hostetler’s leverage would have dropped from 2.02 to 1.90, and if there were 2 more Wild Card games in 1989, Montana leverage would have jumped from 1.68 to 1.78.

Given that they both came into the playoffs with the same path to a championship, does it make sense to alter their rating based on a round they didn’t play in?

• William Gregory

This “formula” is crap. Plain and simple.

Jim Plunkett’s 1980 playoff performance @ #2 all-time, while Aaron Rodgers’ 2010 playoff performance is @ #10 all-time? Really?

Yes, because completing 41% of your passes with 2 TD passes and 3 INT across the first two rounds of the playoffs screams “all-time great performances!” Plunkett had next to nothing to do with the Raider wins in the first two rounds. Oakland’s defense intercepted Kenny Stabler and Brian Sipe a combined 5 times, and held Earl Campbell to 91 yards on 27 carries (3.37 ypc). Not bad, considering Campbell ran for an NFL leading 1,934 yards in 1980, and averaged 5.2 ypc. Not only did Plunkett barely contribute in the first two rounds, he gave Cleveland a 7-0 lead by throwing a pick 6. The defense bailed his ass out. Now, I give him somewhat of a pass, because the game at Cleveland was 2 degrees at game time (and 20 below zero wind chill), but Rodgers had to face similar conditions at Chicago, and he played a much tougher defense than Plunkett did.

Plunket was 8-23 for 168 yards, 2 TD passes and an INT in the first round. That’s a 34.78% completion rate. Basically, he completed one of every three passes he threw. Round 2? 14-30 for 149 yards, 0 TD passes and 2 INT. By today’s QB rating metric, through 2 playoff rounds, his passer rating was 50.9. Now he did better in the third round, going 14-18 for 261 yards, 2 TD passes and 0 INT. But that was against the Charger defense that was 18th in points allowed (18th out of 28 teams then). Finally, in the Super Bowl, he faced the #1 scoring defense, and was 13-21 for 261 yards, 3 TD and 0 INT. So, he certainly improved the last two games. But two crap performances, and two really good performances do not average out to the second best postseason performance in NFL history!

Rodgers was 18-27 for 180 yards and 3 TD passes against the Eagles in the first postseason game of the 2010 season. His second game, he was nearly perfect, going 31-36 for 366 yards and 3 TD against the Falcons. The Eagles may have been 21st in the NFL in points allowed, but Rodgers did this against a Falcon defense that was 5th in points allowed, and he did it to them at Atlanta, where the Falcons were considered virtually unbeatable. Now, Rodgers’ only bad game of the playoffs came against Chicago. He was 17-30 for 244 yards. He threw 0 TD passes and 2 INT. Can you blame him though? The game was at Soldier Field. It was 20 degrees with a 14 mph. The wind chill was 7. As with the first TWO games the Raiders won, the defense was responsible for winning this game for the Packers. And the Super Bowl? Rodgers, like Plunkett, faced the #1 scoring defense in the NFL in Pittsburgh. Rodgers was 24 for 39 for 304 yards and 3 TD. Like Plunkett, he won the Super Bowl MVP. Unlike Plunkett’s receivers, Rodgers’ receivers dropped no fewer than seven passes. Rodgers lost Packer all-time leading receiver Donald Driver in the first half, and was forced to go with Greg Jennings (who was granted, a Pro Bowl receiver), and an untested Jordy Nelson. I distinctly recall Nelson dropping three passes himself. But he and Rodgers made up for it.

Plunkett had a home game in round one. Rodgers was on the road for all three playoff games leading up to the Super Bowl.

What teams did each QB face? Record (and NFL defensive points allowed ranking):
Plunkett: 11-5 Houston (2nd), 11-5 Cleveland (12th), 11-5 San Diego (18th), and 12-4 Philadelphia (1st). Combined records: 45-19. Average pts allowed rank: 8.25/28
Rodgers: 10-6 Philadelphia (21st), 13-3 Atlanta (5th), 11-5 Chicago (4th), and 12-4 Pittsburgh (1st). Combined records: 46-18. Average pts allowed rank: 7.75/32.

Who had the harder road to the Super Bowl victory? Aaron Rodgers, who played three road games, and faced the 1st, 4th, 5th and 21st ranked defenses (out of 32), or Plunkett who had a home game, and faced the 1st, 2nd, 12th and 18th ranked defenses (out of 28)? Plunkett faced the top two scoring defenses in the NFL. Rodgers faced three of the top 5. Rodgers faced more tough defenses on his way to hoisting the Lombardi.

Pure numbers? Plunkett was 49 of 92 (53.26%) for 839 yards (9.12 ypa), 7 TD passes vs 3 INT. QB rating 96.2
Pure numbers? Rodgers was 90 for 132 (68.18%) for 1,094 yards (8.39 ypa), 9 TD passes vs 2 INT. QB rating of 109.8.

Plunkett beats Rodgers in one area, yards per attempt. Rodgers completed 15% more of his passes, threw for 2 more touchdowns and one fewer interception. Plunkett ran in a touchdown against the Chargers in the AFC Championship Game. Aaron Rodgers ran in a touchdown in the divisional game against Atlanta, AND a touchdown against the Bears in Chicago. So while Plunkett accounted for 8 touchdowns, Rodgers counted for 11.

In summary, Rodgers performed better than Plunkett. He was forced to win three games on the road, while Plunkett had a home game and two road games. Statistically he was better against better on-average defensive opponents.

There is no way Plunkett deserves to be second on this list, and Rodgers 10th.

• William Gregory

And before anybody jumps my ass for “not realizing this measures drop backs compared to net yards”, I do realize it, and it’s a stupid metric. Tell me, if a team has a lead late in the game, and is passing the ball at all, are they more likely to throw it short, or long? They’re going to throw short, high percentage plays. This will drive their average yards per attempt down, but the name of the game in the postseason is winning, and if shorter passes nets more first downs, who cares how many yards each pass is netting?

There is no metric…none, that passes the sniff test, that will convince me, or any other sports enthusiast with a brain, that Jim Plunkett outplayed Aaron Rodgers when compared side by side.

• Tim Truemper

To Richie – thanks for the overview on my previous comment. There were wildcard games in the NFL system starting in 1970 (but only one entry per conference) and in the AFL during the SB era but prior to the merger. I was also figuring that there were fewer playoff games and thus, my own qualifier that the fewer 70’s representatives on the list may be due to disproprotionate playoff game opportunties. Thanks again for your review of my statement. I might add that I don’t consider the 70’s a “dead ball” era in actuality. But from 1970 through 1976 there was a major decline in passing numbers that started to turn with the changes in passing game rules starting in 1977.

• Danish

I think it’s nice.

However I think you should be careful equating good performance in high leverage situation to being clutch. I admit clutchness is a somewhat subjective thing, but I think when people talk about the clutch they see a performance relative to the amount of “pressure” the player in question was under. This doesn’t always result in a zero-sum game.

Example: AFC Championship a week ago. It seemed to me that Brady was on somewhat of a freeroll: If he won, great, but if he lost no biggie – how could he beat a juggernaut like the Broncos with that many injuries and those recievers? Manning however was under maximum pressure – he HAD to win or else he’d be labelled the ultimate playoff choker seriously hurting his GOAT case. Plus, you know, he’d blow his likely last chance to get to the super bowl. Mannings was under more pressure, but gets credit for the same leverage as Brady.

I’m don’t think clutch exist – football is a series of near independent events. I’m just saying you should bevare of selling any stat as a measure of clutchness, since the term clutch is so flimsy and hard to define, thus the stat will be extremely easy to poke holes in.

But as I said i kinda like it.

• Red

Overall, I like it. The adjustment for era and SoS is particularly helpful, which seems to be missing in most QB playoff discussions. However, I do have one concern: the heavy weighting of the Super Bowl allows single plays to wildly swing a QB’s value, even if he had little to do with the play. Think of an unlucky tip-drill INT, which carries a penalty of 141.3 yards (45 x 3.14). Or a dumpoff to a RB who takes it 80 yards for a TD, which credits the QB 314 yards (80+20 x 3.14).

Why is Jake Delhomme ranked 4th? Because more than half of his value came on one play, an 85 yard TD pass in the closing minutes of the Super Bowl (worth 329.7 yards). He dropped back 110 times, yet 54% of his value is determined by one single play? That’s borderline absurd.

ANY/A works great over a full season or career, but with the small sample of one playoff run, outliers have a huge influence.

• That’s probably pretty accurate, though. Think about Eli Manning, for instance: basically two plays — the helmet catch by Tyree and the *perfect* 38-yard pass to Manningham — are the difference between him being regarded as a massive bust/NYC media whipping boy and a 2-time Super Bowl champion. In that case, the absurdly elevated emphasis on the Super Bowl by talking heads is actually somewhat in line with what leverage says about the Super Bowl’s importance relative to other games.

• Football troll

“Denver also started the playoffs with a 12.5% chance of winning the Super Bowl, since the Broncos don’t get any extra credit for rostering Peyton Manning.”

More like losing credit for rostering Peyton Manning, amirite?