≡ Menu

Are The Giants As Bad As They Appear?

Over the last three and a half seasons, the Giants have the worst record in football. In fact, it’s not particularly close: since the start of the 2017 season, the Giants are 13-42. The Jets have the second worst mark, at 16-39, the Bengals are 16-38-1, and every other team has a winning percentage at least 10% higher than the Giants.

But does it feel like the Giants have been by far the worst team in the NFL? Probably not: they’ve been bad, but not even necessarily all that noticeably bad. And I think the biggest reason for that is New York has been relatively competitive over this stretch. The Giants don’t even rank in the bottom three in points differential since the start of the 2017 season: the Jets, Raiders, and Dolphins all have fared worse. Along with Tampa Bay (more on them in a moment), the Giants have been a large outlier in terms of underperforming, at least when we measure their points scored and points allowed numbers relative to their winning percentage.

We can calculate each team’s Pythagenpat winning percentage fairly easily. If you want the fine print, check this footnote [1]To use the 2020 Giants as an example. First, you calculate the total points scored and points allowed in all Giants games (296) and divide it by the number of games played (7, leaving 42.3 total … Continue reading, but the Pythagenpat winning percentage tells you what you would “expect” a team’s record to be based on how many points they score and how many points they allowed. The 2020 Giants have a Pythagenpat winning percentage of 0.287, which would translate to a 2-5 record instead of the team’s actual 1-6 record. In fact, over the last three and a half years, New York has had a better Pythagenpat winning percentage each year:

TmFromGW-L%PFPAPDPythagDiff
NYG2017160.188246388-1420.241-0.053
NYG2018160.313369412-430.427-0.115
NYG2019160.250341451-1100.322-0.072
NYG202070.143122174-520.287-0.144

In 2018, New York went 4-8 in games decided by 7 or fewer points, and since the start of ’17, New York is just 8-21 in these one-score games. Tampa Bay is 10-20 in these close games and 12-13 in all other games.

The Giants form an easy comparison to the other team in New York. While the Jets have a better record than the Giants, they have a 7-28 mark in non-close games, similar to the Giants 5-21 record (but over more games). Meanwhile, in close games, the Giants are 8-21 while the Jets are 9-11. Had those numbers been closer to average for the Giants, it’s likely that the Jets would have the worst record over the last three and a half seasons.

The table below shows each team’s Pythagenpat winning percentage since the start of 2017. To read the Giants line, they have played 55 games and have a 0.236 winning percentage. The Giants have scored 1078 points and allowed 1425, for a points differential of -347. The team has a Pythagenpat winning percentage of 0.326, which means they have underachieved by about 9%.

RkTmGW-L%PFPAPDPythagDiff
1NYG550.23610781425-3470.326-0.089
2TAM550.40014111437-260.488-0.088
3LAC540.519126911001690.591-0.073
4DET540.39812311324-930.452-0.054
5JAX550.40011161201-850.453-0.053
6BAL540.70414949765180.752-0.049
7SFO550.49113331264690.535-0.044
8CIN550.30011001418-3180.340-0.040
9ATL550.45513321344-120.494-0.040
10DEN540.37010161200-1840.396-0.025
11IND540.46312141236-220.488-0.025
12CLE550.33611281416-2880.355-0.019
13NWE540.70414299894400.722-0.019
14DAL550.52713031220830.543-0.016
15MIN540.602130410882160.615-0.013
16NYJ550.2919921385-3930.298-0.007
17HOU550.47312841354-700.4650.008
18CHI550.54511031041620.5360.009
19WAS550.34510221347-3250.3300.016
20LAR550.691157512013740.6740.017
21PHI550.609137211931790.5910.018
22CAR550.47312411347-1060.4460.026
23KAN550.727164912114380.6970.030
24ARI550.39110841374-2900.3510.040
25TEN540.59312341143910.5490.043
26LVR540.37010751456-3810.3110.060
27PIT540.676130610892170.6160.060
28SEA540.648140212491530.5760.072
29MIA540.38910661433-3670.3150.073
30NOR540.759159011943960.6840.076
31GNB540.58312691256130.5070.077
32BUF550.54510591170-1110.4370.108

Finally, here’s every team-season since 2017. This includes the partial year of 2020, which is more prone to outliers of course. The 2020 Falcons have been the biggest underachiever by this metric, while the 2020 Browns have been the biggest overachievers.

RkTmFromGW-L%PFPAPDPythagDiff
1ATL202070.143184207-230.420-0.277
2MIA202060.500160113470.712-0.212
3CLE2017160.000234410-1760.195-0.195
4MIN202060.167155192-370.356-0.189
5DAL2019160.5004343211130.689-0.189
6HOU202070.143166217-510.325-0.182
7LAC2019160.313337345-80.485-0.172
8CIN202070.214163194-310.385-0.171
9LAC202060.333149154-50.478-0.145
10NYG202070.143122174-520.287-0.144
11DET2019160.219341423-820.362-0.143
12CIN2019160.125279420-1410.258-0.133
13JAX202070.143154220-660.275-0.132
14JAX2017160.6254172681490.757-0.132
15NYG2018160.313369412-430.427-0.115
16SFO202070.571181136450.678-0.107
17TAM2017160.313335382-470.416-0.103
18BAL2017160.563395303920.665-0.102
19LAC2017160.563355272830.661-0.099
20NYJ202070.00085203-1180.099-0.099
21SFO2018160.250342435-930.346-0.096
22HOU2017160.250338436-980.338-0.088
23DEN2018160.375329349-200.462-0.087
24TAM2018160.313396464-680.394-0.081
25WAS202070.286133165-320.365-0.080
26NWE2019160.7504202251950.829-0.079
27TAM2019160.43845844990.514-0.076
28NYJ2018160.250333441-1080.322-0.072
29NYG2019160.250341451-1100.322-0.072
30CHI2017160.313264320-560.384-0.071
31TEN2019160.563402331710.624-0.062
32BAL2018160.6253892871020.685-0.060
33DET2018160.375324360-360.433-0.058
34MIN2019160.6254073031040.682-0.057
35TAM202070.714222142800.769-0.055
36NYG2017160.188246388-1420.241-0.053
37GNB2018160.406376400-240.459-0.053
38CAR2018160.438376382-60.490-0.052
39ATL2018160.438414423-90.485-0.048
40CAR202070.429162168-60.476-0.048
41LAR2017160.6884783291490.731-0.043
42IND2019160.438361373-120.479-0.041
43JAX2018160.313245316-710.349-0.037
44NYJ2017160.313298382-840.346-0.034
45ATL2019160.438381399-180.469-0.032
46WAS2019160.188266435-1690.219-0.032
47SFO2017160.375331383-520.406-0.031
48NWE202060.333115143-280.364-0.030
49IND202060.667157115420.692-0.026
50ARI2019160.344361442-810.368-0.024
51IND2018160.625433344890.648-0.023
52CLE2019160.375335393-580.397-0.022
53PHI202070.357163196-330.379-0.021
54PIT2018160.594428360680.613-0.019
55DEN2017160.313289382-930.329-0.017
56NOR2017160.6884483261220.699-0.011
57SEA2018160.625428347810.635-0.010
58KAN2017160.625415339760.630-0.005
59MIN2018160.531360341190.535-0.004
60DAL202070.286176243-670.289-0.003
61IND2017160.250263404-1410.251-0.001
62SEA2017160.563366332340.5630.000
63NWE2018160.6884363251110.6850.003
64LAR202070.714176124520.7110.003
65DET2017160.563410376340.5570.005
66DEN202060.333116153-370.3280.006
67ARI202070.714203146570.7070.008
68DEN2019160.438282316-340.4300.008
69PHI2019160.563385354310.5550.008
70OAK2017160.375301373-720.3660.009
71BUF2019160.625314259550.6160.009
72LAR2019160.563394364300.5520.011
73CHI2018160.7504212831380.7360.014
74CIN2018160.375368455-870.3610.014
75CAR2019160.313340470-1300.2960.017
76KAN2019160.7504513081430.7320.018
77WAS2017160.438342388-460.4180.019
78ARI2018160.188225425-2000.1660.021
79DAL2017160.563354332220.5410.021
80CLE2018160.469359392-330.4420.026
81BAL202060.833179104750.8070.027
82OAK2018160.250290467-1770.2220.028
83PHI2018160.563367348190.5340.028
84PIT2019160.500289303-140.4710.029
85BAL2019160.8755312822490.8450.030
86HOU2018160.688402316860.6510.036
87DET202060.500156165-90.4620.038
88CHI2019160.500280298-180.4620.038
89JAX2019160.375300397-970.3270.048
90TEN2018160.56331030370.5140.048
91SFO2019160.8134793101690.7610.052
92CIN2017160.438290349-590.3850.052
93ATL2017160.625353315380.5720.053
94PHI2017160.8134572951620.7600.053
95GNB2017160.438320384-640.3840.053
96NWE2017160.8134582961620.7590.053
97KAN2018160.7505654211440.6960.054
98BUF2018160.375269374-1050.3030.072
99MIN2017160.8133822521300.7400.072
100MIA2017160.375281393-1120.2980.077
101LAC2018160.750428329990.6670.083
102WAS2018160.438281359-780.3500.087
103NOR2018160.8135043531510.7250.088
104MIA2019160.313306494-1880.2180.095
105DAL2018160.625339324150.5290.096
106NYJ2019160.438276359-830.3400.097
107LVR202060.500171197-260.4020.098
108KAN202070.857218143750.7570.100
109TEN2017160.563334356-220.4590.103
110LAR2018160.8135273841430.7050.107
111OAK2019160.438313419-1060.3180.119
112CAR2017160.688363327360.5670.121
113NOR2019160.8134583411170.6870.125
114ARI2017160.500295361-660.3750.125
115MIA2018160.438319433-1140.3090.128
116HOU2019160.625378385-70.4880.137
117PIT2017160.813406308980.6720.141
118NOR202060.66718017460.5240.143
119BUF2017160.563302359-570.3920.171
120SEA2019160.68840539870.5120.176
121GNB202060.833197159380.6450.188
122TEN202060.833188153350.6380.195
123GNB2019160.813376313630.6160.197
124SEA202060.833203172310.6150.218
125CHI202070.714138140-20.4910.223
126BUF202070.714174178-40.4850.229
127PIT202061.000183118650.7640.236
128CLE202070.714200221-210.4310.284

Please leave your thoughts in the comments.

References

References
1 To use the 2020 Giants as an example. First, you calculate the total points scored and points allowed in all Giants games (296) and divide it by the number of games played (7, leaving 42.3 total points scored per game). We then take that number and raise it to the 0.251 power, and get a result of 2.56. This is the exponent we use when calculating the Giants expected winning percentage using the traditional Pythagorean formula. The advantage here using this two-step process over a static exponent (historically, 2.37) is that it recognizes that higher-scoring games provide different environments than lower-scoring games. To calculate New York’s expected winning percentage, we would use this formula:

(Points Scored ^ Exponent) / [(Points Scored ^ Exponent) + (Points Allowed ^ Exponent)]

In the case of the 2020 Giants, that’s:

(122 ^ 2.56) / (122 ^ 2.56 + 174 ^ 2.56)

That gives a result of 0.287, which is New York’s expected winning percentage based on its points scored and points allowed.

{ 0 comments }