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Adam Steele is back for another guest post. You can view all of Adam’s posts here. As always, we thank him for contributing.

There have been countless attempts at deducing the clutchiness of NFL quarterbacks, most of which involve tallying playoff wins and Super Bowl rings. Today I’m going to take a stab at the clutch conundrum using a different approach: Pythagorean win projection. If a quarterback’s actual win/loss record diverges significantly from his Pythagorean estimated record, perhaps we can learn something from it. I began this study having no idea how it would turn out, so there were definitely some surprises once I saw the end results. This study evaluates the 219 quarterbacks who started at least 32 games since 1950, including playoffs but excluding the 1960-64 AFL (lack of competitive depth).

Here’s how to read the table, from left to right: points per game scored by the QB’s team in games he started, points per game allowed in his starts, total starts, total wins (counting ties as a half win), Pythagorean projected wins based on the points scored and allowed in his starts (using a 2.37 exponent), and the difference between his actual win total and Pythagorean win projection.

1Peyton Manning26.7421.37292200183.916.1
2Tom Brady27.8918.92254194181.612.4
3Dan Marino23.0420.75258155144.910.1
4John Elway23.2719.43252162.5152.510.0
5Jake Plummer19.7421.941427162.18.9
6Dan Pastorini18.2721.071225950.88.2
7Jay Schroeder20.1618.871046456.17.9
8Andrew Luck24.5224.02613831.36.7
9Stan Humphries21.6220.40875346.56.5
10Jeff Hostetler21.0619.31885548.56.5
11Ken Stabler22.5118.42158103.597.46.1
12Ed Brown21.9721.199957.551.65.9
13Matt Hasselbeck21.9922.271719084.25.8
14Mike Phipps17.8219.04733933.65.4
15Rodney Peete19.4820.85894640.95.1
16Jay Cutler22.6924.171366862.95.1
17Steve McNair21.7219.691639690.95.1
18Jeff George17.5723.601274742.24.8
19Fran Tarkenton21.4020.94250133128.24.8
20Brian Sipe19.8921.151135752.44.6
21Ben Roethlisberger23.8218.57186124119.74.3
22Tony Eason20.7921.61563126.74.3
23Marc Bulger21.0825.59984237.94.1
24Vince Young21.5920.49513127.13.9
25Neil Lomax20.6923.121024844.33.7
26Frank Ryan24.8420.189059.555.93.6
27Eli Manning23.8422.90194105101.63.4
28Y.A. Tittle24.3922.2113980.577.23.3
29Matt Ryan23.9222.061317571.73.3
30Joe Theismann21.9618.371328379.83.2
31Tony Romo25.1622.061338076.83.2
32Jake Delhomme21.7319.781046157.83.2
33Phil Simms20.3017.7316910197.93.1
34Jim Plunkett20.4120.411548077.03.0
35Marc Wilson20.3921.25613229.03.0
36Daryle Lamonica26.4718.00947067.12.9
37Derek Anderson18.5122.73452017.12.9
38Bill Nelson22.8122.277943.540.62.9
39Joe Montana24.6317.35187133130.22.8
40Dave Brown16.7220.30602623.22.8
41Colin Kaepernick22.1120.89533128.32.7
42Erik Kramer19.6922.61703229.32.7
43Michael Vick22.2521.6811863.560.82.7
44Steve Walsh17.0018.54412118.42.6
45Bobby Layne23.7320.241398582.42.6
46Jim Zorn20.0024.121064441.42.6
47Joe Namath22.4223.101326663.72.3
48Trent Dilfer17.8217.521196360.72.3
49Sonny Jurgensen21.5422.6114972.570.22.3
50Quincy Carter15.7117.00351815.92.1
51David Woodley21.6717.935837.535.42.1
52Earl Morrall20.9717.0410768.566.42.1
53Neil O'Donnell19.8719.121075855.92.1
54David Whitehurst14.8917.953716.514.52.0
55John Brodie21.6322.551648078.02.0
56Aaron Brooks20.5324.23923937.11.9
57Andy Dalton23.7920.058150.548.61.9
58Gary Hogeboom19.3821.59371816.11.9
59Jim Kelly23.2019.18177110108.21.8
60Carson Palmer22.8322.661638482.31.7
61Steve Bono20.8117.21432826.31.7
62Jim McMahon20.7515.591037068.31.7
63Tim Couch16.5921.69592220.41.6
64Danny White25.2319.731026765.51.5
65Jeff Blake20.0024.821003937.51.5
66Tommy Kramer20.5521.321145654.51.5
67Jack Concannon16.8219.184520.519.01.5
68Babe Parilli18.8224.20552119.51.5
69Jack Trudeau15.4420.00501917.61.4
70Kordell Stewart20.1718.05865048.61.4
71Norm Van Brocklin26.7422.291056563.71.3
72Craig Erickson17.6022.34351412.71.3
73Doug Williams17.7718.738842.541.31.2
74Pete Beathard18.0519.083718.517.31.2
75Mike Tomczak20.7218.67784543.81.2
76Josh Freeman19.9524.08612523.81.2
77Byron Leftwich17.3118.90512422.91.1
78Bert Jones21.5622.91994745.91.1
79Randy Johnson15.5528.454910.59.51.0
80Brett Favre24.0719.75322199198.01.0
81Chad Henne18.6225.45531817.10.9
82Charley Johnson22.2322.191246362.10.9
83Mark Sanchez22.0921.54784140.20.8
84Bob Avellini17.0018.98512322.20.8
85Jim Hart21.0421.4918289.588.70.8
86Scott Hunter16.8116.654322.521.70.8
87Sam Bradford19.1322.946325.524.80.7
88Joe Ferguson18.7820.331758079.30.7
89Dennis Shaw15.4626.033798.30.7
90Matt Cassel20.4123.00803534.40.6
91Daunte Culpepper21.4825.151044342.40.6
92Nick Foles23.6423.14361918.50.5
93Dave Krieg21.3419.73184101100.50.5
94Billy Kilmer20.1719.4812163.563.00.5
95Eddie LeBaron18.1724.318127.527.10.4
96Lamar McHan17.8223.73732524.60.4
97Vince Ferragamo21.5821.46593029.70.3
98Charlie Conerly21.7817.329258.558.20.3
99Marty Domres16.4420.72321211.70.3
100Trent Edwards18.4221.21331413.80.2
101Bubby Brister19.3519.66773837.80.2
102Chris Chandler19.7221.681556968.80.2
103J.P. Losman15.7922.7033109.80.2
104Kent Graham16.9218.61381716.90.1
105Ryan Tannehill20.3622.09642928.90.1
106Steve Spurrier16.9221.843813.513.40.1
107Craig Morton19.1417.2515486.586.40.1
108Mike Pagel17.0423.245417.517.50.0
109Cam Newton24.6821.638448.548.50.0
110Jim Harbaugh18.6819.681456868.00.0
111Derek Carr19.1326.59321010.00.0
112Matt Schaub23.6423.19944848.1-0.1
113David Carr16.2823.63792323.1-0.1
114Jay Fiedler20.7317.32633838.1-0.1
115Don Heinrich20.7316.70372323.1-0.1
116Steve Tensi19.4727.093410.510.7-0.2
117Jim Finks19.5823.04451818.2-0.2
118Bobby Hebert21.2619.681035656.2-0.2
119David Garrard21.6521.09784040.2-0.2
120Chad Pennington20.6419.53874646.4-0.4
121Randall Cunningham23.0619.5614485.585.9-0.4
122Alex Smith21.7919.5812670.571.0-0.5
123Richard Todd20.1021.6911250.551.0-0.5
124Don Majkowski19.4420.335726.527.0-0.5
125Christian Ponder23.5027.083614.515.0-0.5
126Aaron Rodgers27.8220.901328787.5-0.5
127Doug Flutie20.7418.50683838.6-0.6
128Archie Manning15.8624.3013936.537.1-0.6
129Pat Haden20.2716.056037.538.1-0.6
130Kyle Orton20.7320.06824242.6-0.6
131Wade Wilson21.6520.84743838.7-0.7
132Brad Johnson21.2618.521327676.7-0.7
133Rex Grossman21.9020.33512727.7-0.7
134Robert Griffin III23.0026.83361414.7-0.7
135Randy Wright15.0924.343277.8-0.8
136Gus Frerotte21.3721.809545.546.4-0.9
137Bob Berry17.0419.175221.522.4-0.9
138Adrian Burk20.1022.834116.517.4-0.9
139Steve Fuller17.4118.14442020.9-0.9
140Blaine Gabbert15.4924.313588.9-0.9
141Jon Kitna20.8924.461255051.0-1.0
142Gary Cuozzo18.8517.76412122.0-1.0
143Tobin Rote22.0826.089838.539.5-1.0
144Roger Staubach23.8215.311319697.0-1.0
145Jack Kemp20.9819.27512728.1-1.1
146Joe Kapp19.1517.605227.528.6-1.1
147Ryan Fitzpatrick20.6423.4210543.544.7-1.2
148Kyle Boller19.0220.64472021.2-1.2
149Otto Graham26.8514.747861.562.8-1.3
150Lynn Dickey19.7022.1011347.548.9-1.4
151Johnny Unitas24.3618.53194126127.4-1.4
152Joey Harrington17.2421.95762627.4-1.4
153Kerry Collins19.6321.121878485.4-1.4
154Joe Flacco23.6018.821378586.4-1.4
155Ken O'Brien20.1921.4611250.552.0-1.5
156Rick Mirer17.7421.99682425.5-1.5
157Drew Brees26.6023.23227130131.5-1.5
158Zeke Bratkowski18.5322.604716.518.1-1.6
159Brian Griese22.0419.86834546.6-1.6
160Eric Hipple20.0519.64582829.7-1.7
161Kurt Warner26.6722.361297677.8-1.8
162James Harris19.0715.20442627.8-1.8
163Tommy Maddox21.2921.953816.518.3-1.8
164George Blanda21.8125.264215.517.4-1.9
165Chris Miller19.4123.34943536.9-1.9
166Billy Wade22.4722.05864244.0-2.0
167Mark Rypien23.3818.48855254.0-2.0
168Billy Joe Tolliver18.1922.94471517.2-2.2
169Jeff Garcia22.5522.161226062.2-2.2
170Bernie Kosar20.8420.4311556.558.9-2.4
171Tony Banks19.1819.83783537.5-2.5
172Charlie Batch20.6920.71552527.5-2.5
173Shaun Hill22.0620.50341618.5-2.5
174Russell Wilson25.7316.19745355.5-2.5
175Bobby Douglass17.1921.965316.519.0-2.5
176Milt Plum21.7018.521045961.7-2.7
177Jason Campbell19.6621.77793234.7-2.7
178Bill Munson18.6819.056629.532.2-2.7
179Len Dawson22.6317.4212578.581.3-2.8
180Dan Fouts23.7723.0317889.592.3-2.8
181Elvis Grbac22.4118.88734143.8-2.8
182Vince Evans18.1020.18391417.0-3.0
183Tarvaris Jackson22.2919.69351720.1-3.1
184Matthew Stafford23.4224.44954245.1-3.1
185Greg Landry18.9119.189945.548.7-3.2
186Bob Griese21.1516.7716299.5102.7-3.2
187John Friesz18.7621.18381316.3-3.3
188Gary Danielson20.4819.756128.531.8-3.3
189Josh McCown19.2323.88571821.3-3.3
190Mark Malone20.1120.13552427.5-3.5
191Scott Mitchell22.4122.89733235.6-3.6
192Steve Grogan22.3819.861387578.7-3.7
193Vinny Testaverde19.5021.6221992.596.2-3.7
194Roman Gabriel21.3018.3815989.593.2-3.7
195John Hadl21.9520.0115079.583.2-3.7
196Steve Bartkowski20.3820.821316063.9-3.9
197Warren Moon21.9021.45213105109.2-4.2
198Donovan McNabb22.9218.28177107.5111.7-4.2
199Boomer Esiason21.8722.251788387.2-4.2
200Steve Young25.7618.84157102106.3-4.3
201Steve Beuerlein20.2520.101044852.5-4.5
202Bobby Thomason20.3618.054219.524.0-4.5
203Mark Brunell21.6120.081618387.5-4.5
204Terry Bradshaw22.8515.68177121125.6-4.6
205Mike Livingston19.4520.017531.536.2-4.7
206Jim Everett20.1922.011586671.0-5.0
207Bill Kenney21.7521.49773439.0-5.0
208Norm Snead19.5923.9515855.560.6-5.1
209Philip Rivers25.0921.1516996101.4-5.4
210Drew Bledsoe20.7419.54199101106.5-5.5
211Don Meredith26.6121.04895156.6-5.6
212Trent Green25.0723.581155661.7-5.7
213Steve DeBerg19.6022.5314454.560.2-5.7
214Troy Aikman21.9418.01180105110.7-5.7
215Ken Anderson21.3119.291789399.5-6.5
216Ron Jaworski19.0617.3215177.584.0-6.5
217Rich Gannon24.1219.471398086.8-6.8
218Bart Starr22.9916.68167106113.8-7.8

If you want to make the case for Peyton Manning and Tom Brady (in either order) being the two greatest quarterbacks to ever play the game, this is a good place to start. According to Pythagoras, they are the two biggest overachievers in NFL history. In a league where records in close games regress heavily toward the mean from one season to the next, Manning and Brady have consistently defied the odds and won games they had no business winning, year in and year out. The presence of Dan Marino at #3 runs counter to the popular narrative of the Dolphins great coming up small in big moments; despite often being saddled with mediocre teammates, Miami won significantly more games than it should have with Marino under center. Conversely, John Elway’s reputation as a winner has long exceeded his statistical output, but in this case the numbers agree with conventional wisdom. Elway’s Broncos won 10 more games than expected, and I’d say it’s fair to give most of the credit to Elway himself.

Dan Pastorini is a fascinating case, at least to me. By any statistical measure, Pastorini is one of the worst long term starters in NFL history. Yet he also ended up as one of the most prolific Pythagorean overachievers in history! How did this happen? I don’t have an answer, but I do have a theory. Despite Pastorini’s poor play, the Oilers’ staff noticed that the team was winning an inordinate percentage of close games when he started. Given that us humans are loathe to accept the vagaries of random chance, someone in Houston probably concluded that Pastorini must be clutch and/or have winnersauce flowing through his veins. And since winnersauce is such a rare quality, the Oilers kept starting him even though he played like Christian Ponder.

Take a gander at the biggest underachievers, it surely must be a bunch of scrubs. Instead we find… Hall-of-Famers, MVP’s, and Pro-Bowlers? I was beyond shocked to see Bart Starr dead last, and nearly as surprised to see Aikman, Bradshaw, and Young down there with him. Besides having a bust in Canton, these guys have something else in common – they all played on dominant teams. The tendency of dominant teams is to win big and lose close, the perfect recipe for tricking Pythagoras into thinking the team isn’t winning as many games as it should. I feel safe in concluding that’s the reason for these all-time greats to appear so low on this list. Really bad quarterbacks like Randy Wright, Blaine Gabbert (thus continuing our streak of mentioning Justin Blackmon or someone on the ugly 2012 Jaguars), and Dennis Shaw don’t get much of a chance to underperform: those three are the only ones on here with less than 10 Pythagorean wins.

Now I’ll turn the floor over to the FP readership. Does this study reveal anything significant, or is it mostly statistical noise? If you believe the former, which QB’s stand out to you and why?

  • I looked at this a few years ago, with similar results: http://www.footballperspective.com/quarterback-wins-over-pythagoras/

    I didn’t quite pick up on the reason that Starr, Aikman, and Young (all members of the 94-win club!!) fared poorly, but I think you’re right. In some ways, being on dominant teams can hurt you here. It’s even more impressive then, I think, that Brady does so well here. OTOH, all 3 of those QBs all had some lean years, which Brady never had.

    As for Pastorini, he had a LOT of comebacks. In ’78, he had 6 fourth quarter comebacks and 7 GWDs; in ’74, he had 3/4. I also wonder how playing on some legitimately terrible teams maybe distorted things. Do you have his season-by-season splits available?

    • Adam

      For some reason I had no recollection of you already doing this study. Oh well, updates are good! I don’t have season by season splits for each QB, but I will note that Houston was +1.5 in ’74, +2.5 in ’78, and +2.2 in ’79; these seasons coincide with most of Pastorini’s 4QC/GWD, so your theory appears to be correct.

      • Your numbers and Chase’s will differ slightly, as well, because he used 2 as an exponent while you used 2.37.

        • Adam

          Good point. Has the analytics community reached a consensus on what the exponent should be for football?

          • 2 is the simpler approach, but 2.37 is the number given in Wikipedia and Doug’s post at the PFR blog. Of course, Football Outsiders used to use 2.37 as well, but they decided to move to a more accurate number. In this post, Chase uses 2.53 as the exponent. Jim Glass, in a post at AFA determined 2.67 was the superior exponent.

            Personally, I prefer Pythagenpat. However, the number we use to find the final exponent for that is also debated. Basically, we don’t agree on anything. I imagine the best way to find the premium exponent would be to minimize standard deviation rather than maximize correlation with actual win%. If we want to maximize correlation, we could just set the exponent to a million and watch as R climbs to nearly one.

            • Adam

              Is there any easy way to set up a pythagenpat formula in excel?

              • Yea. My computer is at work, so I’ll email you a file in the morning.

  • Yeah, I think I lean noise. The top 4 looks great and then you don’t find another all-timer until #19, followed by #28 and #39.

    You know what stat this reminds me of a little bit in that regard, actually, although it’s not quite the same? Plain old passing yards. http://www.pro-football-reference.com/leaders/pass_yds_career.htm

    • Adam

      I tend to agree that it’s mostly noise….but not entirely. There are parallels in every sport – pitcher BABIP, goalie save %, and basketball RAPM all follow the same property as QB Pyth numbers. These measures all contain a pinch of skill but are so overwhelmed by noise that it takes a decade or more for any of that skill to show through.

  • Who’s to say Dan Pastorini’s quarterback play is the reason his teams outperformed their point spreads? Perhaps he was the most clutch punter in NFL history.

    • Andy Trimble

      In 1975 they went 10-4. Billy Whiteshoes returned 4 kicks/punts for TDs, and their defense was very good. They were a +18 in turnover ratio in a 14 game season. The closest thing to an all-pro receiver on the team was Burroughs, and he was a fast guy with below average skills. They were 0-4 vs Pitt and Cincy, their two chief rivals in their division. Had they one just ONE of those games, they would have made the playoffs. They lost those game by 2, 7, 23, and 4, respectively. Dan and Ken both were selected to the pro bowl.

      I always liked Pastorini, but he didn’t spend the better part of his career throwing to Swann and Stallworth, nor handing it to Franco. Call me crazy, but I think he was every bit as good as Bradshaw, who was HORRIBLE for the first 5 yearsof his career. Dan got the crap kicked out of him for most of his career. He struggled for the first few years, but so did the Oilers (back to back 1-13 seasons).

      (Yes, I lived in Houston all those years. Peace.)

  • Josh Sanford

    This is fascinating. Can you break out the playoff games so we can see those separately?

    • Adam

      I don’t have the playoff data available offhand, but I’d be happy to calculate the playoff Pyth numbers for specific QB’s. Have anyone in mind?

      • Josh Sanford

        I was thinking of Starr, Anderson, Aikman, Bradshaw–those guys who look like they are being punished down at the bottom of the list because, according to the narrative, their job is not to go out and win the game, but to manage, reduce mistakes, and let the rest of the team do their thing. (And then of course you have to Brady and Manning!)

        • Adam

          9-1, 8.5 pyth, +0.5

          2-4, 2.4 pyth, -0.4

          11-4, 11.0 pyth, +0.0

          14-5, 13.4 pyth, +0.6

          22-9, 20.0 pyth, +2.0

          14-13, 14.0 pyth, +0.0

          Looks like Brady is the only major overachiever in the playoffs among this group, not sure if that means anything. Interesting that Manning and Aikman both matched their projections exactly.

          • Josh Sanford

            I guess even when you make the playoffs a bunch of time, it is still a small sample size. Thanks for doing that inquiry.

  • Josh Sanford

    I wonder if we looked at a list of era-adjusted PPG, would that sort out the “problem” of team dominance? (Not for me–I like this list just the way it is.)

    • Adam

      I think era-adjusted PPG would be quite interesting, and will probably be the topic of a follow-up study. Which QB led the highest scoring offense in history, relative to the league environment? My guess is Otto Graham, but I don’t really know. The adjusted defensive numbers might be even more illuminating in explaining why some QB’s have a W/L record that doesn’t match their level of play. Like, check out Russell Wilson’s defensive PPG….he’s a good QB, but no wonder he wins so much!

      I don’t think era adjusting would solve the issue of dominant teams, but putting a MOV cap (say, 21 points) on each game would probably do the trick. Unfortunately that would be a ton of work to go back and correct all the blowout games by hand, so I’ll pass (unless someone here has the programming skills to do this quickly).

      • Josh Sanford

        Interesting. As I conceived of it, you wouldn’t calculate or adjust for what the defenses were doing–you just normalize the actual scoring of the offense and that gives you some baseline for understanding the relative productivity of the QB. (And since you mentioned Otto Graham, I have to make my plug for him: he RUSHED for 26 TDs over his last 39 career games.)

      • Instead of correcting all the blowout games by hand, just use a formula like =if(B2>21,21,B2). That would save a lot of time.

        • Adam

          Thanks for the tip! I really need to work on my database skills…

          • One of the great things about having a Twitter account is that I have no shortage of people who are A) better at things than I am and B) willing to help or teach. I don’t play fantasy football, but man of the people I follow on Twitter are fantasy writers. I don’t follow them because I want their fantasy opinions; I follow them because they are intelligent, thoughtful, and often have unique insights about how to approach understanding the game.

            • Adam

              Who are your favorite follows? Might be time to dust off my Twitter account…

              • I only follow 59 people, so the hit rate for great follows is pretty high. Mostly some FO guys, Barnwell, Chase, Adam Harstad, Brian Malone, George Kritikos, Ken Krippen…humans like that.

  • sacramento gold miners

    Generally speaking, I would put Brady’s and Manning’s supporting cast above Marino’s.I’m a big believer of how important the QB position is to dominance, I don’t the Patriots as successful with Bledsoe or the Colts as good with a Jim Harbaugh under center. I keep thinking back to those old Cowboy teams with Craig Morton, and despite a strong supporting cast, it took Roger Staubach for that franchise to win multiple Super Bowls.

    Dan Pastorini was a number one draft choice, and those Oiler teams of the mid to late 70s did have a strong defense. Of course, Earl Campbell joined Houston in 1978. It makes sense the Oilers would have the type of team to win close games.

    • Adam

      Are you implying that Marino’s pythagorean greatness is more impressive than Manning and Brady’s due to a weaker supporting cast?

      • sacramento gold miners

        Naw, I don’t believe in the pythagorean approach, but this is still interesting material.

  • Dr__P

    wins and losses are TEAM stats not individual ones

    • Adam

      Couldn’t agree more. How much of these numbers do you think we can attribute to the QB, if any?

    • sacramento gold miners

      I’m with you if we saw a bunch of QBs with mediocre won/loss records with elite numbers historically, but it’s not going to happen. The top QBs almost always have strong winning records, which is indicative of the most important position on the football field. In baseball, we don’t see HOF pitchers with mediocre records for the same reason.

      • Dr__P

        Even in baseball, the sports writers et al are not so impressed with pitchers won/loss records as much as they used to.

        • Andy Trimble

          That may be true for individual seasons, but for a career, it’s as important. Pitchers rarely win more than 20 games anymore, so you have 5-6 guys each season with 15-19 wins. It’s easier to vote a guy with 17 wins the Cy Young award over a guy who wins 19 than it was to pick the 20 game winner over the 25 game winner.

  • Tom

    This is pretty cool, as you say, a different approach. And yes, the question is, how much credit can we give to the QB for this difference? In any event, I was thinking there would be a correlation between what you’ve done and game winning drives, so I checked it out. Turns out the top 4 guys match almost exactly (as far as ranking goes) Peyton, Marino (instead of Brady), Brady and Elway. But after that, things just get wacky…the correlation turns out to be a pretty weak 0.11. Don’t think it means anything, but I did find it interesting that the top 4 were right on…

    • Adam

      Thanks for running those numbers, Tom. Is it possible that those four QB’s are so uniquely elite at situational football that they transcend randomness?

      • Andy Trimble

        When a list is weighted so heavily towards an era, it cannot be random. Most games in the modern era come down to last minute drives. Also, Pey Pey has played in far more games than anyone else.

        Staubach had 23 come from behind, 4th quarter drives, in 137 games, 16.8% of his games.
        Peyton has 56 GWD in 292 starts, 19.2%
        Marino has 51 in 258, 19.8%
        Elway 46 in 258, 17.8%
        Brady 48 in 254, 18.9%

        I may be wrong, but there were many more games (as a % of his games) that Staubach didn’t NEED to lead a GWD, because his teams were good, and some opponents were bad. There were lots more blowouts in Roger’s day.

        Don’t get me wrong, I’m not bashing Manning, nor any of these other guys. It’s a tribute to Peyton that he’s played 292 games… however, Staubach and his generation didn’t have the protection that modern QBs have in the rules. Defensive players absolutely unloaded on QBs before 1980.

        I hate to sound like the “get off my lawn” guy, but the rules have changed so much, it doesn’t make sense to compare the stats of QBs from 40 years ago to present day. It’s like comparing hitting stats of steroid era 1990’s MLB to those of the 1960’s when the mound was 6 feet high.


        • Adam

          There are more close games today than there were in the 70’s, but it’s an exaggeration to say “most” games come down to a last minute drive. Do you think Elway and Marino comprise the same era as Manning and Brady? Kinda sounds like that’s what you’re implying.

          I fully agree that QB’s took more abuse in Staubach’s era than they do now, but how does that relate to playing in close games?

          • Andy Trimble

            a) My only point about the abuse comment was how many more games QBs can play today. Favre, Manning, Brady, et al can play longer today because of the rules put in place to protect them. That’s all. They also play 16 game seasons. A QB who plays 15 seasons today plays 30 more games in a career than the 60’s and 70’s QBs, and 60 more than the QBs of the 40’s and 50’s, who played 12 game seasons. More games, more chances to play in a close game.
            b) The list is top heavy with modern QBs. Close games are more abundant today. Elway is a special case, and should probably be at the top of any “clutch” list. He rarely played for great teams, and pulled them from the fire more than any QB I’ve ever seen. 11 of the top 24 QBs on this list played in the era after ’95 – 45.8%. You either conclude that QBs are more “clutch” today, or that the rules have effected the nature of the game to such an extent that close games are more prevalent.
            c) I may be wrong about “most” games coming down to the last drive, but I’d like to see the stats. Before ’95, all but a few SBs were blowouts (Cowboys/Colts, both Steelers/Cowboys and 49ers/Bengals, and Bills/Giants), that’s 6 out of the first 30 that were not decided by halftime. Since then, there hasn’t been a blowout, except the Seahawks/Broncos 2 years ago, and the Ravens/Giants in 2000. I just watched a show on NFL network about the greatest SBs of all time… More than half of them have been post ’95. MOST SBs in this era have been close games that came down to the last drive, even the failures like the Titans/Rams or the Seahawks/Pats. That’s a fact.


  • Andy Trimble

    I’d say what this proves is that the modern QB is much more valuable than ever because of FA. There is basically parity in the NFL now, and a great QB is the difference between winning 31-27 games instead of losing them 27-24. The only anomaly in the last 20 years is Trent Dilfer, whose Ravens defense was so dominant, no one could have beaten them. Except for him, almost every SB winning QB was a HOFer, going all the way back to Lomabardi’s Packers. (Doug Williams and Brad Johnson aren’t going to be enshrined anytime soon, but they were good QBs on great teams. The only other “Dilfer-type” is Hostetler, and again, he had a great team around him.) Very few SB losers have had below average QBs, either. Good teams usually have good QBs.

    Staubach’s team won the games they were supposed to win. Every team brought their “A” game against the Cowboys in his day. It doesn’t surprise me that in the days before FA and parity that great QBs won exactly what they should have won.

    Today’s NFL reminds me of the old adage, “In a country of blind people, the one-eyed man is King.” Craig Morton took two different teams (franchises!) to the SB. So did Earl Morrall. What does that prove about them? As far as I concerned, QBs cannot be truly compared across generations, especially with the rule changes. Staubach retired with the highest QB rating of all time. That rating isn’t in the top 20 anymore. Bradshaw beat Staubach twice ib head to head SB matchups. Does anyone really think Terry was better than Roger (besides diehard Steelers’ fans)?

    If you break down Manning’s 292 games in to 16 game seasons, he has 18.25 seasons. He has won, by your theorem, .88 more games per season that he should have. So, the GOAT QB adds almost one win per season more to his team than would be expected. That’s a very unremarkable stat. I hate to burst the bubble of all your work, but I have to conclude that this means nothing, or almost nothing.

    ( Sidebar: Denver won a bunch of games last year, even though Manning sucked. Their defense won that championship. I’d like to see you take last years figures out of his totals and see where he stands. )