≡ Menu

Over at TheGridFe, I just finished the single season portion of my series on the (statistically) greatest regular season quarterback performances in NFL history. I’ve discussed the stats, as they are, which always seem to paint modern quarterbacks in a much better light. I’ve prorated for season length, which can sometimes produce a few curious results. I’ve also applied both hard and soft inflation adjustments to account for the evolution of the position and increase in its usage rate.1 After talking with Adam Steele and agreeing that maybe even the most moderate approach still left seasons like Sid Luckman’s 1943 or Dan Fouts’s 1982 getting far more credit than they probably should. So I went ahead and made an even weaker era adjustment, which I will discuss briefly in this post, to try to mitigate the effects of the original modifications.

My main purpose for writing today isn’t to give you another list of great quarterback seasons, although I will do that as well. My goal is to solicit the opinions of the Football Perspective readers, whom I respect for their thoughtful and reasoned nature. I have two primary questions:

  1. Is it necessary, or even right, to make adjustments for changes in both schedule and QB usage rates?
  2. If we believe it is right to reward older players with schedule and inflation corrections, should we also penalize them for playing in weaker leagues?2

I will provide two tables below with several examples of what it looks like to make the changes I mentioned in the first question. I have no such table for the second question. In fact, this study from Jason Lisk is the only attempt I have seen at comprehensive comparison of the relative strengths of the NFL and AFL.3 I’ll talk a little about both after we look at some numbers.

The Basics

Since the NFL began running a standardized schedule (1936), there have been 94 professional seasons between the established league and its two greatest rivals. In those years, we have seen schedules range from a mere nine games to the current sixteen-game format. We have also seen a range of quarterback plays per game from 19.5 to 40.9. As you’ll see, this can create pretty extreme numbers when we attempt to put these seasons on a level playing field.

The table below probably isn’t for everyone, but I think many among you will find it instructive. It displays the 94 seasons mentioned above, along with the numbers we get after using different methods to prorate and adjust for inflation. Read it thus: The 2015 NFL featured a 16-game schedule and saw quarterbacks engage in 40.8 plays per game.4 The multiplier to prorate the schedule is 1.00 (16/16). To find the lower multiplier, just take the average of the higher multiplier and 1.00. In this case, the lower multiplier is still 1.00. To find the hard inflation adjustment, take the season’s plays per game and divide it into the historical plays per game (34.7). For 2015, that number is 0.85. To arrive at the soft inflation adjustment, find the average of the hard adjustment and 1.00. For 2015, that’s 0.93. To find the weakest adjustment, divide the sum of the hard adjustment and two by three [(0.85 + 2)/3]. The quotient is 0.95 for 2015. Once you have those figured out, you can used any combination of schedule and inflation adjustment to modify a quarterback’s yearly value. The last six columns show us what we end up doing to a season once we apply these combinations.


Depending on which combination of adjustments you implement, your results can vary drastically. The last few seasons receive the most significant possible penalties, with their values only given 85% credit in some cases. On the other hand, quarterbacks in 1936 receive as much as 238% credit for their output. I know this isn’t important to some of you, and it might not even be that helpful in the abstract, but I think it’s a useful tool to see how much credit we are adding – or taking away from – players based on the era they happened to play football. If you’re more interested in a practical example of what this means, you may prefer the next table.

The Results

To set up the table below, I calculated every quarterbacks Total Adjusted Yards per Play since 1932.5 I then found their efficiency relative to the rest of the league. This is similar to how Chase calculates RANY/A, but for a few small differences: first, I back out the player’s stats from the rest; second, I aggregate years n – 1, n, and n + 1 prior to finding the average. The result is what I have called value per play. All we have to do now is multiply Val/P by total plays to find total value over average.6

Once we have the actual, unadulterated value, we can apply our combinations of era modifiers to see what happens. I have done just that. Read thus: Peyton Manning, playing in the 2004 NFL, had 535 plays at a rate of 9.16 TAY/P. His marginal value of 4.32 leads to a total value over average of 2312, tops in history. However, that value changes to 2171 with a ProHard modification, 2241 with a ProSoft modification, and 2265 with a ProWeak modification. Because he played in a 16-game season, his LowHard, LowSoft, and LowWeak modifications are the same as his Pro ones.

1Peyton ManningINDNFL20045359.164.322312217122412265217122412265
2Dan MarinoMIANFL19846058.273.812305216222342257216222342257
3Tom BradyNWENFL20076368.343.352131198620582083198620582083
4Aaron RodgersGNBNFL20115988.773.341999176518821921176518821921
5Drew BreesNORNFL20117028.12.671877165717671804165717671804
6Peyton ManningDENNFL20137098.072.521787152916581701152916581701
7Steve YoungSFONFL19945507.983.181750158316661694158316661694
8Peyton ManningINDNFL20065947.732.891716159416551675159416551675
9Daunte CulpepperMINNFL20046827.312.471687158416351653158416351653
10Randall CunninghamMINNFL19984778.183.451648148915681595148915681595
11Kurt WarnerSTLNFL19995517.762.981642147615591586147615591586
12Tom BradyNWENFL20116867.762.331596140915031534140915031534
13Steve YoungSFONFL19925077.673.131586152815571567152815571567
14Bert JonesBALNFL19764107.443.841575203619181878190817981761
15Sid LuckmanCHINFL19432249.796.791521333828862735271223452222
16Jeff GarciaSFONFL20006577.022.31513135314331460135314331460
17Ken AndersonCINNFL19815507.22.71487144814671474144814671474
18Dan FoutsSDGNFL19816506.762.261472143414531459143414531459
19Joe MontanaSFONFL19844937.422.971462137214171432137214171432
20Steve YoungSFONFL19986357.032.31461132013911414132013911414
21Joe TheismannWASNFL19835307.142.671414134213781390134213781390
22Otto GrahamCLEAAFC19472889.94.911414210818621780197717461669
23Aaron RodgersGNBNFL20145918.042.381408119413011337119413011337
24Donovan McNabbPHINFL20045427.422.591402131613591373131613591373
25John BrodieSFONFL19703957.463.541400181117051670169815991566
26Steve YoungSFONFL19935627.062.451377129713371350129713371350
27Dan MarinoMIANFL19866526.552.081355125613061322125613061322
28Philip RiversSDGNFL20095377.752.521355124613011319124613011319
29Drew BreesNORNFL20095567.662.441355124613001319124613001319
30George BlandaHOUAFL19613698.123.641343156015471543146314511447
31Brett FavreGNBNFL19956426.872.081335119712661289119712661289
32Tom BradyNWENFL20105487.742.431333119812651288119812651288
33Drew BreesNORNFL20086707.081.981328122712781295122712781295
34Mark RypienWASNFL19914437.612.991324129813111315129813111315
35Joe MontanaSFONFL19894687.572.821322126412931302126412931302
36Peyton ManningINDNFL20006286.812.11316117612461270117612461270
37Peyton ManningDENNFL20126277.532.061290111312021231111312021231
38Otto GrahamCLENFL19533017.824.271286191918171782167915891560
39Y.A. TittleNYGNFL19634097.443.131282154415041491144714101398
40Ken AndersonCINNFL19754586.52.781271161915361508151814401414
41Tom BradyNWENFL20126877.321.841266109211791208109211791208
42Brett FavreMINNFL20095747.422.191257115612061223115612061223
43Sonny JurgensenWASNFL19675426.372.321256152214781464142613861372
44Boomer EsiasonCINNFL19884617.382.71245116812071220116812071220
45Carson PalmerARINFL20155877.872.121242105611491180105611491180
46Peyton ManningINDNFL20055037.352.451234115811961208115811961208
47Brian SipeCLENFL19805976.512.061229122612271228122612271228
48Otto GrahamCLEAAFC19493129.243.911221200718171754175615901535
49Daunte CulpepperMINNFL20005976.752.041215108611511172108611511172
50Philip RiversSDGNFL20085347.352.261207111511611176111511611176
51Kurt WarnerSTLNFL20016126.761.971203107811401161107811401161
52Trent GreenKANNFL20025277.032.281199109211451163109211451163
53Len DawsonKANAFL19663088.573.891199138413771375129812911289
54Drew BreesNORNFL20066146.791.951197111211541169111211541169
55Joe MontanaSFONFL19836096.431.951190112911591170112911591170
56Rich GannonOAKNFL20027046.441.691190108311371154108311371154
57Aaron RodgersGNBNFL20096497.061.831187109111391155109111391155
58Steve YoungSFONFL19913587.933.311183116011721176116011721176
59Neil LomaxSTLNFL19846446.281.831175110211391151110211391151
60Peyton ManningINDNFL20036126.811.911171108011251140108011251140
61Peyton ManningINDNFL20096007.171.941167107311201136107311201136
62Scott MitchellDETNFL19956506.581.791162104111021122104111021122
63Roger StaubachDALNFL19795346.32.161155121311841174121311841174
64Philip RiversSDGNFL20106087.21.891149103310911111103310911111
65Jim EverettRAMNFL19895726.7521145109511201128109511201128
66Tony RomoDALNFL20096197.071.841142105010961111105010961111
67Vinny TestaverdeNYJNFL19984647.182.451135102610801099102610801099
68Philip RiversSDGNFL20136027.431.8811309671048107696710481076
69Daryle LamonicaOAKAFL19684626.22.421120132013001293123812191212
70Nick FolesPHINFL20134028.332.7811199571038106595710381065
71John BrodieSFONFL19654206.842.641110131612921284123412111204
72Aaron RodgersGNBNFL20105707.251.9411069941050106999410501069
73Sammy BaughWASNFL19473796.132.91097179816311575157314271378
74Warren MoonHOUNFL19906756.41.621096105710761083105710761083
75Drew BreesNORNFL20137227.061.5110899321011103793210111037
76Joe NamathNYJAFL19684006.492.711086128012601254120011821176
77Ken AndersonCINNFL19744076.32.661082140713221293131912391212
78Matt SchaubHOUNFL20096566.871.6510799921036105099210361050
79Johnny UnitasBALNFL19643797.212.831074129612621251121511831172
80Johnny UnitasBALNFL19593966.972.71069172115731524150613771334
81Cecil IsbellGNBNFL19423046.493.511067199417731699168214961434
82Tom BradyNWENFL20096106.971.7410639771020103497710201034
83Ken StablerOAKNFL19763176.953.351062137312941267128712131188
84Trent GreenKANNFL20035696.761.8710629791021103597910211035
85Johnny LujackCHINFL19493206.723.311059164715301491144113391304
86Chad PenningtonNYJNFL20024507.12.3410559611008102496110081024
87Tom FloresOAKAFL19663118.063.391054121712101208114111351133
88Peyton ManningINDNFL19995826.581.8104694199410119419941011
89Joe NamathNYJAFL19675235.6821046122112081204114411331129
90Fran TarkentonMINNFL19754685.962.241046133212641241124911851164
91Sammy BaughWASNFL19452017.535.191044208618781809169515261470
92John HadlSDGAFL19674735.882.21041121512021198113911271123
93Erik KramerCHINFL19955726.611.82104193398710059339871005
94Daryle LamonicaOAKAFL19694506.22.311041125012201210117211441134
95Peyton ManningINDNFL20075566.851.8610359651000101296510001012
96Ron JaworskiPHINFL19805056.52.051034103210331033103210331033
97Tommy ThompsonPHINFL19482587.64.011034167015241476146113341291
98Milt PlumCLENFL19602678.183.871032165815181471145113281287
99Dan FoutsSDGNFL19823517.442.941031176417991810137814051414
100Kurt WarnerSTLNFL20003857.382.661025916971989916971989
101Y.A. TittleNYGNFL19623927.372.61021138412751239129711951162
102Brett FavreGNBNFL20045686.631.791019957988998957988998
103Fran TarkentonMINNFL19764645.792.191017131412381213123211611137
104Len DawsonDTXAFL19623487.52.921016120711841177113111101103
105Carson PalmerCINNFL20055626.71.811016953985995953985995
106Ken StablerOAKNFL19743406.622.981013131712371211123511601135
107Roger StaubachDALNFL19784875.812.081011112410681049112410681049
108Jim HartSTLNFL19764136.042.451011130712311206122511541131
109Donovan McNabbPHINFL20063697.572.731007936972983936972983
110Steve YoungSFONFL19974416.982.281007917962977917962977
111Ben RoethlisbergerPITNFL20146747.151.491005852929954852929954
112Jim KellyBUFNFL19915256.531.911001981991994981991994
113Drew BreesNORNFL20127116.881.41999862931954862931954
114Aaron RodgersGNBNFL201265771.52999862931953862931953
115Roger StaubachDALNFL19712757.493.63999133012361205124711591129
116Bernie KosarCLENFL19874266.882.3298798410191030953987998
117Trent GreenKANNFL20046136.441.61985924955965924955965
118Elvis GrbacKANNFL20006066.341.62983879931948879931948
119Steve DeBergKANNFL19904876.782.01979944962967944962967
120Norm Van BrocklinRAMNFL19532946.863.31973145313751350127112041181
121Rich GannonOAKNFL20005906.361.65972869921938869921938
122John ElwayDENNFL19874966.521.9697196810021013938971981
123Steve BeuerleinCARNFL19996486.271.5969871920937871920937
124Tom BradyNWENFL20055836.551.66967907937947907937947
125Sonny JurgensenPHINFL19614366.762.2961131412061170123211311097
126Bart StarrGNBNFL19662987.343.2955113711141106106610441037
127Steve McNairTENNFL20034576.982.09953879916929879916929
128Fran TarkentonNYGNFL19674506.172.12953115511221111108310521042
129Fran TarkentonMINNFL19743896.082.44949123511601135115710871064
130Tony RomoDALNFL20075756.641.65949884916927884916927
131Brian GrieseDENNFL20003827.192.47944844894911844894911
132Johnny UnitasBALNFL196748361.95943114211101099107110401030
133Joe MontanaSFONFL19874556.632.07941938971982909941951
134Dan FoutsSDGNFL19806445.911.46940937939939937939939
135Boomer EsiasonCINNFL19865396.211.74937869903914869903914
136Matt HasselbeckSEANFL20055096.731.83933875904913875904913
137Peyton ManningINDNFL20085896.681.58932861896908861896908
138Peyton ManningDENNFL20146387.121.46932790861884790861884
139Daryle LamonicaOAKAFL19674845.61.92929108310721069101610051002
140Drew BreesSDGNFL20044716.81.96925869897906869897906
141Matthew StaffordDETNFL20117216.71.27919811865883811865883
142Bert JonesBALNFL19754295.862.14918116911091089109610401021
143Chris ChandlerATLNFL19984086.972.24912824868883824868883
144Roman GabrielRAMNFL19674386.132.0891211051074106310361006997
145Joe MontanaSFONFL19855716.041.6911847879890847879890
146Mark BrunellJAXNFL19975166.461.77911830870884830870884
147Troy AikmanDALNFL19954676.741.95909815862878815862878
148Tom BradyNWENFL20156967.061.31908773841863773841863
149Dan MarinoMIANFL19926026.051.51908875892897875892897
150Otto GrahamCLEAAFC19483567.882.54905131311731127123111001056
151Chad PenningtonMIANFL20085306.81.71904836870882836870882
152Brett FavreGNBNFL19975966.211.52904823864877823864877
153Matt RyanATLNFL20126776.81.33899775837857775837857
154Russell WilsonSEANFL20156317.181.42897764830853764830853
155Lynn DickeyGNBNFL19835456.121.64894848871879848871879
156Don MeredithDALNFL19664196.272.13892106210411033996976969
157Otto GrahamCLEAAFC19462049.044.37891141612171151132711411079
158Frank RyanCLENFL19664466.131.99886105510341027989969963
159Charlie ConerlyNYGNFL19483396.22.61883142713021261124911401103
160Joe MontanaSFONFL19815396.121.62874851863866851863866
161John BrodieSFONFL19613117.372.8187411951097106411201028998
162Dan MarinoMIANFL19874656.441.87871869899909841871881
163Tony RomoDALNFL20115806.931.5869767818835767818835
164Earl MorrallBALNFL19683526.672.478681069103010171002966954
165Eli ManningNYGNFL20116526.751.32864763813830763813830
166Joe MontanaSFONFL19905896.241.46862832847852832847852
167Bill NelsenCLENFL19683176.922.72862106110231010995959947
168Bert JonesBALNFL19774475.471.928601124105310301054987965
169Jim KellyBUFNFL19903886.982.21858827842847827842847
170Charlie ConerlyNYGNFL19592098.374.1857137912611222120711041069
171Y.A. TittleBCLAAFC19483417.842.5185512411109106511631039998
172Michael VickPHINFL20105066.991.69854768811826768811826
173Frankie AlbertSFOAAFC19483337.892.5685212371106106211601037995
174Randall CunninghamPHINFL19906326.121.35851821836841821836841
175Frank FilchockWASNFL19391927.464.43851154913941342130711761132
176Troy AikmanDALNFL19934506.51.89851801826834801826834
177Jim ZornSEANFL19795745.611.47845888867860888867860
178Dan FoutsSDGNFL19833666.782.31845802824831802824831
179Brett FavreGNBNFL20075796.451.46844786815824786815824
180Roger StaubachDALNFL19764415.511.918431090102710061022963943
181Tommy KramerMINNFL19864266.441.97841780810821780810821
182Marc BulgerSTLNFL20045456.381.54840789815823789815823
183Robert GriffinWASNFL20125437.021.55840725783802725783802
184Roman GabrielRAMNFL19694485.991.8783610571006989991943927
185Len DawsonKANAFL19682626.953.18833982967962920906902
186Tony RomoDALNFL20144907.351.69830704767788704767788
187Doug WilliamsTAMNFL19815376.041.54828806817821806817821
188Boomer EsiasonCINNFL19895386.281.53824788806812788806812
189Kurt WarnerARINFL20086426.381.28824761793803761793803
190Boomer EsiasonCINNFL19854966.11.66823764793803764793803
191Dan MarinoMIANFL19946556.051.25821743782795743782795
192Roman GabrielPHINFL19735035.371.63820109910189911031955929
193Jake PlummerDENNFL20045986.211.37819769794802769794802
194Roger StaubachDALNFL19774425.41.85818107010039801003940919
195Dan MarinoMIANFL19916035.981.36818802810813802810813
196Cecil IsbellGNBNFL19412785.832.94816149313401289126011311088
197Norm Van BrocklinRAMNFL19542666.723.0781612221155113210691010991
198John ElwayDENNFL19936345.91.29815767791799767791799
199Joe NamathNYJNFL19723416.112.36806109910109801030947919
200Jake PlummerDENNFL20055246.431.53802752777786752777786
201Vinny TestaverdeBALNFL19966176.021.3800717758772717758772
202Jim EverettRAMNFL19885796.061.38800750775783750775783
203David GarrardJAXNFL200739572.01793739766775739766775
204Greg LandryDETNFL19713666.022.177931056981956990920896
205Johnny UnitasBALNFL19634995.91.59792954930922894872864
206Ben RoethlisbergerPITNFL20095966.561.33792728760771728760771
207Bob WaterfieldRAMNFL19511857.564.237831192111810941043978957
208Ken O'BrienNYJNFL19855755.81.36780725753762725753762
209Mark RypienWASNFL19895186.261.51780746763769746763769
210John HadlSDGAFL19664136.561.89780900896894844840838
211Jay CutlerDENNFL20086846.231.14778719748758719748758
212Marc BulgerSTLNFL20066556.031.19777722750759722750759
213Dan FoutsSDGNFL19854596.141.69776721749758721749758
214Doug FlutieBUFNFL19984146.61.87773698735748698735748
215Trent GreenKANNFL20055746.241.35772725748756725748756
216Brett FavreGNBNFL19966325.941.22768688728742688728742
217Jeff GarciaSFONFL20016026.071.27767687727741687727741
218Johnny UnitasBALNFL19653286.532.34767909893887852837832
219Troy AikmanDALNFL19925335.981.44766738752756738752756
220Steve McNairTENNFL20015436.21.41765685725738685725738
221Fran TarkentonMINNFL19654136.041.85763905889883849833828
222Babe ParilliBOSAFL19622817.282.7759902885879845829824
223Johnny UnitasBALNFL19582966.842.557551248112810871092987951
224Ben RoethlisbergerPITNFL20104546.961.66752676714727676714727
225Brad JohnsonWASNFL19995746.091.31752676714726676714726
226John ElwayDENNFL19956056.031.24752674713726674713726
227Tobin RoteSDGAFL19633107.092.42750876867863821812809
228Sid LuckmanCHINFL19452535.292.96749149613471297121610951054
229Norm Van BrocklinRAMNFL19502486.373.01747113110641041990931911
230Jim HartSTLNFL19744145.441.8745969911891909854835
231Drew BreesNORNFL20156826.851.09745634689708634689708
232Spec SandersNYYAAFC19474026.841.8574411109809371041919878
233Sammy BaughWASNFL19492686.182.767411152107010421008936912
234Greg LandryDETNFL19723745.721.987411009928901946870844
235Vince FerragamoRAMNFL19804426.121.68740739740740739740740
236Fran TarkentonNYGNFL19694825.661.53739934889874875833819
237Bobby Layne2TMNFL19583346.52.217371218110010611066963929
238Billy WadeCHINFL19612957.062.57371008925897945867841
239Joe NamathNYJAFL19693855.791.91735883862854828808801
240Fran TarkentonNYGNFL19704685.491.57735950895877891839822
241Sid LuckmanCHINFL19411378.245.3573313401203115711301015976
242Jeff GeorgeOAKNFL19975965.921.23732667699710667699710
243Norm Van BrocklinRAMNFL19512016.953.63729110910411018971911891
244Roger StaubachDALNFL19733755.681.94727975903879914847824
245John HadlRAMNFL19732896.252.52727974903879913846824
246Don MeredithDALNFL19683616.212.01726894862851838808798
247Dan MarinoMIANFL19833346.652.17725688707713688707713
248Steve YoungSFONFL19955226.181.39723648686698648686698
249Fran TarkentonNYGNFL19684215.921.71722889857846833803793
250Archie ManningNORNFL19785465.051.32720800760747800760747
251Fran TarkentonMINNFL19724315.41.66714973895868912839814
252Roger StaubachDALNFL19754395.341.62711905859844849805791
253Sid LuckmanCHINFL19473335.362.137091162105410171017922890
254Dan FoutsSDGNFL19784235.391.66704782743730782743730
255Sammy BaughWASNFL19422455.842.856991306116211131102980939
256Craig MortonDALNFL19702436.792.87698902850832846797780
257Y.A. TittleSFONFL19532736.12.556961039984965909861844
258Terry BradshawPITNFL19784215.381.65695773734721773734721
259Ken AndersonCINNFL19823606.431.93695118812121220928947953
260Daryle LamonicaOAKNFL19703795.751.83693896844826840791775
261Norm Van BrocklinPHINFL19593516.231.9769011111016984972889861
262Rudy BukichCHINFL19653656.071.87684812797792761747742
263Bobby ThomasonPHINFL19533135.742.186841021966948893846830
264Tobin RoteGNBNFL19563925.621.73679116510359921019906868
265Norm SneadNYGNFL19723435.721.98678923849824866796773
266Sonny JurgensenWASNFL19703685.731.81667862812795808761746
267Craig MortonDALNFL19693486.031.91665841801787788750738
268Y.A. TittleSFONFL19543235.712.05663994939921870822806
269Joe FergusonBUFNFL19753645.521.8656835793778783743730
270Otto GrahamCLENFL19524064.941.61655986930911863814797
271Tommy ThompsonPHINFL19492296.272.866551018946921891827806
272Mike LivingstonKANNFL19764005.211.61644832784768780735720
273Y.A. TittleNYGNFL19613106.632.07643879806782824756734
274Johnny UnitasBALNFL19573436.031.876411091973934955851817
275Ken AndersonCINNFL19733795.431.69641859795774805746726
276Sammy BaughWASNFL19483195.591.996361028938908899821795
277Fran TarkentonMINNFL19733465.561.83632847785764794736716
278Norm Van BrocklinPHINFL19602956.452.146311013927898887811786
279Sammy BaughWASNFL19401975.952.925761028933901867787761
280Bob WaterfieldRAMNFL19451895.383.0557611511036998935842811
281Bobby LayneDETNFL19542765.732.08573858811796751710696
282Joe MontanaSFONFL19823965.881.38547935954960731745750
283Ed BrownCHINFL19562086.52.61544933829794816725695
284Sammy BaughWASNFL19432585.12.154111871027973965834791
285Johnny UnitasBALNFL19604145.611.3540867794769759695673
286Bobby LayneDETNFL19513934.691.37539820770753718673659
287Jim HardyRAMNFL19482166.062.46531858783758750685663
288Dutch ClarkDETNFL19361945.392.7252812569808881099858777
289Milt PlumCLENFL19592876.081.81520837766742733670649
290Tommy O'ConnellCLENFL19571248.133.97492837746716732653627
291Sid LuckmanCHINFL19462544.71.89480876787758739664639
292Frank FilchockWASNFL19441805.332.25405936792744760643604
293Tony CanadeoGNBNFL19432234.771.77394865748709703608576

The most glaring issue that arises is what happens when we sort by the ProHard column. Not only does Luckman’s 1943 season jump to the top, it does so by an astronomical margin. Some might argue that he was a dominant force that year and deserving of the top spot. I think 1943’s 2.19 total multiplier gives him way too much credit. I’d say the same for Fouts in 1982, as well as for every quarterback to play in a 12-game-or-less season.7 It isn’t until I apply the weakest of all era adjustments that Manning and Dan Marino jump back to the top two spots. Luckman still outranks Tom Brady’s blitzkrieg 2007 campaign. It’s clear to me that seasons with low attempts, whether because of a shorter schedule or lower usage rate of passers, seem to receive undue credit. Perhaps that’s a nice balance to the fact that those seasons rarely receive proper credit from fans in real life. I don’t know.

Maybe the issue isn’t that I am adjusting for era so harshly. Maybe the real issue is that I am doing so without discounting for the relative weakness of the league that Luckman (or Sammy Baugh, or Cecil Isbell, or Otto Graham, or George Blanda) dominated. That’s where the second question I asked at the beginning comes in. Is it a good idea to start applying some sort of discount to these eras? If we do, should it be based on rigorous analysis, or should it be based on what feels right? I don’t have the answers to these questions. If I did, I wouldn’t crave your input. What do you, esteemed readers of Football Perspective, think about the idea of era adjustments and discounts?

Let me know in the comments. Thanks for reading.

  1. I also presented TAY/P+ scores, but that’s not particularly relevant to this discussion. Check it out anyway, though. []
  2. This doesn’t mean the AAFC and the AFL; it includes those, but it also includes the pre-UFA, pre-big-money, pre-AFL-merger, pre-integration, pre-AFL-merger, pre-T-Formation, and WW2 eras of the NFL. []
  3. I used that article as the foundation for my own research and came up with some multipliers for AFL stats, but they have received mixed fanfare from the few to whom I have showed them. The more historically minded tend to think I am being too punitive to the AFL, while those who think the league is in a constant state of improvement and evolution have agreed that the harsh discounts are not only fair, but imperative. I imagine commenters will have similar disagreements, both with me and with each other. []
  4. Note that when I say a year, I actually mean the three year span with that year in the middle. In order to increase my data set, I aggregated each three year span to find my averages. The exceptions, of course, are the years beginning and ending leagues. You can find the background information here, and the quarterback stats that went into it here. []
  5. Those of you familiar with the stat from reading about it here or at my site should be warned that this is a stripped-down version of the original. Proper TAY/P includes first downs and removes spikes and kneels. Because that information isn’t available for the majority of players in history, I decided to use a simper model. The formula: Total Adjusted Yards = Passing Yards – Sack Yards + Rushing Yards + Passing TDs*20 + Rushing TDs*20 – Interceptions*45 – Fumbles*25; Plays = Pass Attempts + Sacks + Rush Attempts; TAY/P = Total Adjusted Yards/Plays, obviously. []
  6. We could try to look at replacement value as well, but I think a higher baseline is better when trying to determine the very best individual seasons. We’ll save replacement value for the career article. []
  7. Luckman’s season ranks 15th all-time without any adjustments, while Fouts’s ranks 99th. The harshest adjustments see Luckman rank as high as first and Fouts rank as high as seventh. You may agree with that or disagree with that. That’s exactly why I am laying this on the altar of your opinion. []
  • eag97a

    There always is a tension between measuring efficiency and measuring productivity (volume). I don’t agree with pro-rating older qbs to modern day usages. Its artificially adding in plays that they don’t actually deserve since they never did those. About the only trump card of the older qbs would be rule changes since it was harder to pass then and level of qb protection. Everything else, level of competition, number of plays and games, defensive complexity are all tilted towards modern qbs. There is no easy way to level comparisons across different eras of football. Much easier to lump them into buckets like SB era, post-WW 2 era and pre-war and then apply your metrics.

    • I think your approach is probably the most reasonable one, but I’m not sure if content-starved readers would let you get away with it. Brad split up pre-modern guys from the rest, which I thought was a smart move, but it’s harder to do that with an analysis of career stats than it is for the more hagiography driven structure of his epic series.

      • Adam

        I’ll a toss out a radical idea that I’ve been toying with: Using a “tilt” adjustment. Run your objective statistical analysis of every QB in history using whatever methodology you like, but include a subjective tilt multiplier using your human judgment. I think us analytical types sometimes get so wrapped up in being objective and statistically proper that we ignore human analysis altogether. In some cases our subjective judgment is simply more accurate than an equation or algorithm, because we know things that the numbers will never tell us.

        We know that Roger Staubach missed games because of his military service, while Kurt Warner missed games because his poor play put him on the bench. Common sense tells us these two careers should be evaluated differently, but the numbers alone don’t provide us with this critical information. We know that some QB’s played with an all-star supporting cast, while others played with relative scrubs. Again, vitally important to our analysis, but something the numbers alone could never capture.

        Think of a highly sophisticated assembly line in a factory. Robots may be able to do 90% of the work, but there’s still that other 10% of the process that must be handled by a real live human. We not apply the same principle to football analysis?

        • I’m often hesitant to leave fudging stats up to my judgment and the thousand natural shocks the subconscious is err to. You could have ten different, intelligent, thoughtful guys apply their tweaks and all come up with different weights. Heck, we could have some huge differences in some areas, especially when it comes to how we view the past. I imagine you and Brad, for instance, would use far different adjustments for AAFC seasons. Ange Coniglio and I would probably place far different weights on AFL seasons. That doesn’t mean either side is necessarily right or wrong; I think it means that we value different things and hold different beliefs on some fundamental facets of the game.

          Same goes for supporting cast arguments (you can make a HOF case for McNabb with the receiving corps argument…you could also say he’d miss the playoffs without Johnson’s defenses). Or coach arguments (like, sure, Marino had an all time great in Shula, but he was hardly in his coaching prime for most of Marino’s career). We could both passionately believe different sides of the same argument. One of could be right and the other wrong, or we could both be wrong. We can’t exactly apply the scientific method and test every quarterback in history with control groups (although that is what heaven might look like for some).

          • sacramento gold miners

            One of aspects I enjoy about these discussions is the fact football hasn’t yet reached the level of some baseball writers who rely 100% on data, and 0% on watching the sport. It’s black or white philosophy of analyzing the subject matter, and everyone knows there is no perfect formula for rankings or evaluating teams, coaches, and players. Adjusting for eras will always be difficult, but I’ve always believed legendary players are great not just because of raw physical ability, but the aspects of the game which can’t be measured.

          • Adam

            As I replied to Brad, I never had any serious intentions of building a subjective element into my ratings. It was just a nutty idea I’ve had and wanted to see if other people thought it had an merit. Now that I’ve heard two NO answers from guys I respect, I will happily toss this in the scrap heap.

        • I agree with Bryan. I prefer subjective analysis applied to objective stats, rather than building the subjective element into the formula. And until we get stone tablets from The Ghost of Curly Lambeau, who do you trust to be The One Person Who Is Qualified To Determine The Subjective Element?

          The “tilt” adjustment creates the illusion of accurately quantifying things we aren’t currently able to quantify, and no matter what disclaimers you use, many people will misinterpret your intentions and/or results. Too radical for me, I guess.

          • Adam

            Frankly, I agree with both you and Bryan on this; I just wanted to float a crazy idea out there and see what you guys thought. The subjective element is one of the reasons ESPN’s QBR is so widely distrusted, and for good reason. Their game charting is nothing more than somebody’s opinion, which will obviously differ from the next person’s opinion, and so on.

            “Who do you trust to be The One Person Who Is Qualified To Determine The Subjective Element?”

            Jaworski and Gruden will have to fight for the position.

            • Jaworski and Gruden are the obvious choices.

  • Adam Steele gave me the idea to use a three year average of a player’s TAY/P and use that as the number to multiply by when I prorate. I decided to run some quick numbers, using a weighted 3 year average (doubling year N performance) and came up with a few results I’d like to share.

    Sid Luckman 1943
    Original TAY/P: 9.79
    3YrAvg TAY/P: 7.74
    Original VAL: 1521
    Prorated VAL: 2434
    New Prorated VAL: 2158

    Otto Graham 1953
    Original TAY/P: 7.82
    3YrAvg TAY/P: 6.30
    Original VAL: 1286
    Prorated VAL: 1714
    New Prorated VAL: 1516

    Dan Fouts 1982
    Original TAY/P: 7.44
    3YrAvg TAY/P: 7.04
    Original VAL: 1031
    Prorated VAL: 1834
    New Prorated VAL: 1725

    These results look just as good as any of the others, depending on what you’re looking for. This method could be used in concert with any of the other methods I mentioned in the article. Of course, doing so would give us about fifteen different answers for the season value, and we probably wouldn’t agree on any of them. Still, I think this is important to talk about (football important, not real life important).

    • Adam

      Thanks for testing this out, Bryan. I like the results this method yields, although it seems like a lot of extra work so I wouldn’t blame you for scrapping the idea. The general point is that we don’t want fluky statistical seasons to be made even more fluky by prorating an outlier sample that may not accurately represent the QB’s true level of play.

      • You’re right about the extra work. At least with the way I have my database set up now, it’s pretty difficult to something like that without just manually adjusting every player. That’s why I only did it for three player seasons above. I’ll probably take to Twitter or Reddit to find someone who can help out.

        The part about true level of play is interesting. I always read Danny Tuccitto’s posts at Intentional Rounding whenever he publishes new ones, and his mandatory minimum articles are my favorite. They’ve made me rethink volume thresholds for rate stats in many cases. They’re worth checking out if you haven’t before.

  • One thing I like to do with these lists is look on a franchise basis. For example, type GNB into the list:

    In TAY/P, which is per-play efficiency unadjusted for era, Rodgers ’11 is number one, followed by Rodgers ’14, then Starr ’66.

    In VAL/P, which is per-play efficiency adjusted for era, Isbell ’42 is #1, followed by Rodgers ’11 and Starr ’66. I would have guessed Starr ’66 would be higher, but that’s a story for a different day.

    In VAL, the top 5 are all Rodgers with 1 Favre season (’95) in there.

    In PH, it’s Isbell 42, Rodgers 11, Isbell 41, Favre 95, Rodgers 14.

    In PS, it’s Rodgers 11, Isbell 42, Isbell 41, Rodgers 14, Favre 95.

    In PW, it’s Rodgers 11, Isbell 42, Rodgers 14, Isbell 41, Favre 95.

    In LH, it’s Rodgers 11, Isbell 42, Isbell 41, Favre 95, Rodgers 14.

    In LS, it’s Rodgers 11, Isbell 42, Rodgers 14, Favre 95, Rodgers 09.

    In LW, it’s Rodgers 11, Isbell 42, Rodgers 14, Favre 95, Rodgers 09.

    I’m not quite sure what that tells us, but maybe something.

  • Let’s use the Jets as an example. Here are the top 5 rankings:

    TAY/P: Testaverde 98, Pennington 02, Namath 68, Namath 72, O’Brien 85

    VAL/P: Namath 68, Testaverde 98, Namath 72, Pennington 02, Namath 67

    VAL: Testaverde 98, Namath 68, Pennington 02, Namath 67, Namath 02

    PH: Namath 68, Namath 67, Namath 72, Testaverde 98, Pennington 02

    PS: Namath 68, Namath 67, Testaverde 98, Namath 72, Pennington 02

    PW: Namath 68, Namath 67, Testaverde 98, Pennnington 02, Namath 72

    LH: Namath 68, Namath 67, Namath 72, Testaverde 98, Pennnington 02

    LS: Namath 68, Namath 67, Testaverde 98, Pennnington 02, Namath 72

    LW: Namath 68, Namath 67, Testaverde 98, Pennnington 02, Namath 72

    Not a whole lot changing here, although Namath 67 does move up in all of these to 2nd once you move away from VAL. It jumps both Testaverde and Pennington.

    I’ll let someone else pick SF 🙂

    • Bobby Layne had the greatest season in 2TM’s history.

  • Another fun thing to do: type in AFL.

  • This is an extremely ambitious project, Bryan. I really appreciate your approach, recognizing the limitations of different statistical approaches and avoiding a rushed jump to conclusions.

    Is it necessary, or even right, to make adjustments for changes in both schedule and QB usage rates?

    Yes, I think. I get the impression — and perhaps I’m wrong — that your goal is to produce the best and most comprehensive stat-based list of the greatest quarterbacks in the history of pro football. Something I know you’re aware of, but which I believe is essential to an all-time list, is that it be a true all-time list — that it isn’t dominated by recent players. In terms of pure skill, today’s QBs are better than their predecessors, but a ranking that shows Matt Hasselbeck ahead of Bobby Layne isn’t an all-time list.

    Passing plays a larger role today than ever before, and to the extent that a quarterback’s influence on other parts of the game was larger in the past, that’s very difficult to quantify. I think it’s appropriate to acknowledge the QB’s greater role in modern offense, but tempered in such a way that the top of the list isn’t dominated by the Illegal Contact era.

    If you don’t adjust for schedule length, you’re not going to get a meaningful all-time list. Dan Fouts in 1982 is a thorny problem, but I think it’s a mistake to include Pre-Modern seasons. I know you discussed this with eag97a, but with Sid Luckman in 1943 and Peyton Manning in 2004, you’re not comparing apples to apples. I’d cut it off at 1946, maybe even 1950. I’d suggest ’50, and grandfather in the late-40s seasons of players like Graham, Layne, Conerly, etc., who are essentially Modern players. 99% of people will understand why you didn’t include “quarterbacks” who also played defense and kicked field goals. Hell, 95% of them won’t notice.

    If we believe it is right to reward older players with schedule and inflation corrections, should we also penalize them for playing in weaker leagues?

    Probably, though it depends on what you mean and how you adjust. You don’t want George Blanda’s 1961 to rate as the greatest season of all time. I forget if it was you or someone else who mentioned last year that they don’t give full credit to any season before 1970. I think that’s a serious mistake. The NFL was a stronger league in 1969 than in 1970, and stronger yet in 1968, and even stronger before expansion. The quality of an average pro football player, relative to the population, was probably higher in 1959 than any time for several decades afterwards, some lingering racial bias notwithstanding. We went from 12 major league teams to 26 in less than a decade, and the average AFL team was never as good as an average NFL team.

    On a related note, the NFL in the 1960s does not do particularly well by any of the methods above, and that probably suggests some more tinkering.

    Simply as a point of interest, these are the top 20 TSP rankings, through 2015:

    1. Peyton Manning
    2. Dan Marino
    3. Fran Tarkenton
    4. Johnny Unitas
    5. Tom Brady
    6. Drew Brees
    7. Joe Montana
    8. Brett Favre
    9. Otto Graham
    10. Dan Fouts
    11. Steve Young
    12. John Elway
    13. Sonny Jurgensen
    14. Ken Anderson
    15. Norm Van Brocklin
    16. Y.A. Tittle
    17. Warren Moon
    18. John Brodie
    19. Roger Staubach
    20. Aaron Rodgers

    As you know, that ranking varies from my subjective opinion. While it is obviously imperfect, I think it does a pretty good job of balancing eras, leaning slightly towards recent players, but without being dominated by them. Actually, I’m toying with a tweak suggested by readers last year — increasing the exponent adjustment to ^2. That produces the following list: Manning, Marino, Unitas, Graham, Tarkenton, Brady, Montana, Brees, Favre, Young, Fouts, Anderson, Jurgensen, Tittle, Van Brocklin, Elway, Brodie, Staubach, Moon, Rodgers. Players from the 12-game schedule probably rate a little higher than they should, but only a little.

    Please keep us updated as you refine your methodology!

    • This is exactly the kind of feedback I was hoping for when I brought this to the FP audience. You are right that the goal is to make a comprehensive statistical ranking of every quarterback. Rather than trying to do it all at once, I am working it out step by step, asking for intelligent opinions along the way. I am using regular season stats as the starting point, but I plan on adding postseason numbers soon. My biggest issue right now is that it is currently somewhat arduous to get all the playoff stats. I have been talking with PFR about having a postseason option in the player season finder, like they do in the game finder, but it isn’t high on their priority list. NFL.com has complete postseason stats back to 1933, but it doesn’t separate them by game, nor does it include yards lost on sacks (which I think is an important variable). Even after we finally get all the stats in place, there’s the issue of whether to give extra credit to postseason performance. I can see arguments both ways.

      I want to incorporate SOS with an SRS-style adjustment. That will require much more information than I currently have, but I am working to record the data I can find. I also want to incorporate weather, but I haven’t seen a comprehensive study on weather effects that I find totally convincing. It would be great to find a way to account for supporting cast (the golden goose of stats, as a commenter here once called it), but there’s a lot of chicken and egg there, and a circle has no beginning or end.

      I have thought a lot about setting the cutoff at 1950 and just ignoring everything before it, even from Graham. Just include his NFL stats and give an explanation of how great he was prior to the merger. Sort of the thing Chase does with his “greatest X since the merger” stuff, which kicks Tarkenton in the pants every time.

      I don’t believe I said the thing about pre-1970, but I sure may have. I think the biggest distinction from any era to another is the giant lineman era. Most other players aren’t all that different, but offensive linemen and defensive tackles are ridiculous today. I can imagine a man of Graham’s stature playing QB today. Jim Brown was bigger than Adrian Peterson. Dick Butkus was as large as your standard MLB/ILB nowadays. Mel Blount would fit right in with the Legion of Boom, with his condor length and blazing speed. But I can’t imagine a Jim Otto or John Hannah having success today. Even a guy as recent as Munoz would have to add weight to be a star. I say all this to illustrate that when I say the average QB is better today, it has very little to do with his actual physical skill and very much to do with his mental skill. I’m sure an average 1960s passer could learn just as much as a 2015 passer, but the 2015 guys have had the benefit of growing up in increasingly complex systems, getting sound position coaching at a young age, playing 7 on 7 drills, attending passing camps, being exposed to terminology that either didn’t exist or was in its infancy back then, among other advantages.

      Regarding the 1960s, I noticed that there aren’t many historically high seasons, but that the decade has the second most seasons in the top 100 of any decade (with the PS column, which I cover in more depth ).

      I’m glad you posted your updated TSP rankings. I have looked at the rankings from the article you linked a lot over the past few weeks, and I have laughed at how similar our career lists look (depending on which of the many multipliers I employ). Like you, I end up with Ken Anderson and John Brodie ranked among a cavalcade of Gold Jackets.

      • Adam

        I really think the best policy for dealing with the older seasons is to make a sharp cutoff at 1950. Of course it’s unfortunate to leave WWII era players out in the cold, but the style of play, level of competition, and schedule length are just too foreign to compare directly with the modern game. If those seasons are included in any sort of historical analysis, the pre-modern players will always be underrated or overrated, but never just right. And frankly, as Brad pointed out, the vast majority of readers won’t care or even notice.

        • So far two guys whose opinions I respect have agreed on a 1950 cutoff, which I have entertained as well. That might end up being the final path I take, given how different the position is that we’re comparing. The last point is the one that bothers me the most. As a guy with an undergrad degree in history, I am passionate about making sure people remember the older players and appreciate their part in the evolution of the game we love. Perhaps it would just be easier to go from 1950 and then do some separate, focused articles on great 1950 seasons and careers.

          I also have the goal of finding fumble info for the AAFC. I’ve enlisted the help of John Turney, who is about as good as it gets at unearthing football records, but still no luck. As I’ve told you privately, I really hate estimating.

          • Adam

            “Perhaps it would just be easier to go from 1950 and then do some separate, focused articles on great 1950 seasons and careers.”

            That’s exactly how I would handle it. I agree that it’s very important to educate fans about the forefathers of the game, but it’s more sensible to tell their stories with words rather than numbers. I don’t think there’s anything wrong with that. As an aside, I find it borderline disturbing how little knowledge most fans have of football history, especially the younger ones. Peruse a typical thread on Reddit and you’d think the NFL was founded in 2005. Makes me sad.

            • It’s not just football, man. Peruse a thread on almost any topic on almost any site, and you’re sure to find a fairly uninformed majority. As it pertains to football, I don’t think it’s because people are dumb. I think most people are just casual fans, and I think even most super fans just don’t care all that much about stuff that they didn’t see with their own eyes (unless you’re a young 49ers fan, then you gotta shove Montana down the throats of the 12s whenever you can).

              • You’re right, of course, but I think it’s a more obvious issue in football than anything else. Sports get the worst of it, and baseball in particular has a better sense of its history. I guess the NBA is pretty rough, too.

                I’ll also use this opportunity to plug my current series.

          • That sounds like a good idea, but I don’t like the hard cutoff at 1950. Probably we’ve all run into this, but I hate including only part of a player’s career. I remember once doing a 1990-present project, and Joe Montana ranked 50th or something.

            Otto Graham is the most significant example of a player affected by the 1950 cutoff, and if he stood alone, I’d say fine — emphasize him as an exception who’s underserved by your methodology. But players whose names will show up on 1950-pres leaderboards, like Y.A. Tittle and Charlie Conerly, will also rank lower than they deserve. Maybe this is just me, but I’d prefer to do at least a partial workup on 1946-49 (or even 1945 if you want to include Bob Waterfield), so you can present fair (or fair-ish) ratings for those players. Even if we have less confidence in our analysis of those 4-5 seasons, in the case of partial careers, I believe an estimate is better than a gap. My $.02.

            Also, if you and Mr. Turney find the AAFC fumble data and feel inclined to share it, I will be your best friends.

            • One of my favorite stat-based things regarding Montana is that he ranked eighth in career New TAY/P above average, even though the stat only goes back to 1992 and excludes his prime. He ranked 34th in total value above average, I believe.

              I agree about your point on Graham, Tittle, and Conerly. It’s always hard to have a cutoff in any given year because it can exclude some really important information. I always find the most drastic examples, for me, are Graham and Tarkenton, depending on which merger you use as your cutoff.

              I’m all about sharing information and being as transparent as possible. If I find the information, it’s going public as soon as I get in organized.

    • Ryan

      Intuitively the 2nd list looks fairer to all eras, does anyone give Staubach a bump for Navy duty, and what would he look like if he doesn’t currently?

    • Adam

      Hypothetical question using made up numbers:

      Otto Graham was 50% better than the average QB of his era
      Johnny Unitas was 30% better
      Roger Staubach was 25% better
      Dan Marino was 20% better
      Tom Brady was 15% better

      Which of these feats is the most impressive?

      • Based on those numbers, IMO, Graham is the obvious #1. Then (much closer) Unitas, Staubach, Marino, Brady. Modern players deserve an edge, but I don’t think it’s as large as the differences those numbers would suggest.

        FWIW, QB-TSP by decade:


        1. Graham, 33.9
        2. Van Brocklin, 15.8


        1. Van Brocklin, 22.5
        2. Layne, 16.5


        1. Unitas, 27.8
        2. Tittle, 16.0


        1. Unitas, 23.6
        2. Jurgensen, 23.5


        1. Tarkenton, 23.5
        2. Gabriel, 17.4


        1. Staubach, 22.4
        2. Tarkenton, 21.5


        1. Fouts, 25.5
        2. K.Anderson, 19.7


        1. Montana, 28.3
        2. Marino, 25.3


        1. Marino, 29.4
        2. Montana, 19.5


        1. Young, 27.7
        2. Marino, 20.4


        1. Favre, 22.7
        2. Manning, 22.2


        1. Manning, 33.7
        2. Brady, 18.1


        1. Manning, 29.7
        2. Brees, 28.5

        • Adam

          Roughly speaking, if the current NFL is a 1.00, how strong do think each era / league is in comparison? This is an issue I continue to struggle with.

          • Man, the day I know the answer to that…

            For whatever this is worth — I’ve been thinking a lot about WRs recently. My top 100 of the Modern Era includes:

            * 13 who mostly played 12-game seasons (1946-64)
            * 21 who mostly played 14-game seasons (1960-79)
            * 15 from the Air Coryell era (1975-89)
            * 17 from the West Coast Offense era (1985-99)
            * 20 from the expansion era (1995-2009)
            * 14 from the Illegal Contact/Defenseless receiver era (2005-15)

            The ratios are about the same for Top 75, Top 50, Top 125. It’s essentially half from the years 1946-89 (44 years), and the other half from 1985-2015 (31 years). For WRs, at least, that seems about right to me. In fact, if I developed a list with a significantly different distribution, I would probably re-evaluate my approach. That’s something I appreciate about Bryan’s project: his dedication to finding the right balance, to be as fair as possible to players of all eras.

  • I forgot to mention what seasons are actually in the second table. I included all seasons that ranked in the top 250 in any category, in order to avoid a ridiculously long list. If you like super inclusive lists, I have some pretty robust tables on my own site. If you don’t like big lists, this one’s for you.

  • eag97a

    I suggest using 4 numbers for your exercise, 2 for efficiency (how dominant) and 2 for production. For dominance one number will be for 1 season and then the other number is the sum for the whole career efficiency. Same with production, one for a season and the otgpher number being the sum for the whole career. If you want to add in adjustments for era, number of games etc. you can do so. Then you can add the career efficiency number and the career productivity number to arrive at a single metric. As I said you can add in modifiers to give some boost to older qbs but having the efficiency number as part of the metric should be enough of a boost without messing with the career productivity numbers IMO. Good luck with the metric.