[Preface]
The crown jewel to anyone interested in alternative statistics is Bill James' Pythagorean Theorem. It's like the holy grail for those utterly disinterested with the belief in intangibles materially effecting the outcome of a contest.
Most of the work done in pythagoras has been limited to baseball and, to a smaller extent, hoops. If you're interested at all in studying the Pythagorean Method for these sports, I would strongly suggest checking out Ken Pomeroy on the web or pick up Bill James' Historical Baseball Abstract.
With attribution out of the way, it's time to focus on pythagoras and football, specifically the college variety. As noted earlier, there has been very little research done on football pythagoras and what has been completed is mostly associated with the NFL. However, what has been completed does serve as a suitable model to apply to the college football game.
Instead of going into a drawn out discussion of how the Pythagorean Method works or why it is important, I will simply present data and some analysis. If you are interested in learning more about the method, check out this Football Project essay or peruse this article by Football Outsiders.
A lot of people use the Pythagorean Method to determine "lucky" and "unlucky" teams. I have never been a fan of that phraseology. I prefer to use this method to determine which teams "underachieved" and those that "overachieved." It's essentially semantics, but using the latter language seems to impart onto a team control over its own destiny.
[Data]
The below data represents information derived from the 2004 season. The pythagora applied to this data is derived from the NFL model. Therefore, the accuracy of the resultant values will not be as close to perfect as it could be. However, the values will be reasonable enough that a meaningful analysis can take place.
I have limited the accumulated data to those teams who played in the six power conferences in 2004. This was done for two reasons: a) I don't care about Troy State (at least until someone can convince me otherwise); and b) I don't feel like punching the numbers right now for those other conferences. I'll eventually get around to it, but until I do, the only available data will be from the Big Six.
So, you won't see Louisville and you won't see Boise State. Well, at least for the moment.
Legend:
PF = Points For
PA = Points Against
AW/L = Actual Won/Loss Record
AW/L% = Actual Won/Loss Percentage
PW/L = Predicted Won/Loss Record
PW/L% = Predicted Won/Loss Percentage
DIF = Difference between Actual and Predicted Won/Loss Record (in parantheticals) and in Percentage
[Analysis]
The big overachievers in 2004 were:
1. Colorado
2. North Carolina
3. Michigan
4. Wisconsin
5. Arizona State
The big underachievers in 2004 were:
1. Penn State
2. Alabama
3. Purdue
4. Stanford/Arkansas
5. North Carolina State
Why did these teams perform the way they did? Well, that's a topic for another time.
Syracuse Perspective
Probably the most important thing to glean from this data set is that things should've been worst last year than they actually were.
Congratulations, Coach P!
Even with pitiful offensive production, Syracuse was able to play enough defense in key situations to keep itself in enough games (Purdue & Virginia aside) to potentially win.
Not bad, considering everyone assumed that the 2004 Syracuse squad underachieved last season.
The crown jewel to anyone interested in alternative statistics is Bill James' Pythagorean Theorem. It's like the holy grail for those utterly disinterested with the belief in intangibles materially effecting the outcome of a contest.
Most of the work done in pythagoras has been limited to baseball and, to a smaller extent, hoops. If you're interested at all in studying the Pythagorean Method for these sports, I would strongly suggest checking out Ken Pomeroy on the web or pick up Bill James' Historical Baseball Abstract.
With attribution out of the way, it's time to focus on pythagoras and football, specifically the college variety. As noted earlier, there has been very little research done on football pythagoras and what has been completed is mostly associated with the NFL. However, what has been completed does serve as a suitable model to apply to the college football game.
Instead of going into a drawn out discussion of how the Pythagorean Method works or why it is important, I will simply present data and some analysis. If you are interested in learning more about the method, check out this Football Project essay or peruse this article by Football Outsiders.
A lot of people use the Pythagorean Method to determine "lucky" and "unlucky" teams. I have never been a fan of that phraseology. I prefer to use this method to determine which teams "underachieved" and those that "overachieved." It's essentially semantics, but using the latter language seems to impart onto a team control over its own destiny.
[Data]
The below data represents information derived from the 2004 season. The pythagora applied to this data is derived from the NFL model. Therefore, the accuracy of the resultant values will not be as close to perfect as it could be. However, the values will be reasonable enough that a meaningful analysis can take place.
I have limited the accumulated data to those teams who played in the six power conferences in 2004. This was done for two reasons: a) I don't care about Troy State (at least until someone can convince me otherwise); and b) I don't feel like punching the numbers right now for those other conferences. I'll eventually get around to it, but until I do, the only available data will be from the Big Six.
So, you won't see Louisville and you won't see Boise State. Well, at least for the moment.
Legend:
PF = Points For
PA = Points Against
AW/L = Actual Won/Loss Record
AW/L% = Actual Won/Loss Percentage
PW/L = Predicted Won/Loss Record
PW/L% = Predicted Won/Loss Percentage
DIF = Difference between Actual and Predicted Won/Loss Record (in parantheticals) and in Percentage
| Pythagorean Method - 2004/5 Season | ||||||||
| Conf. | Team | PF | PA | AW/L | AW/L% | PW/L | PW/L% | DIF |
| ACC | VTech | 387 | 151 | 10-2 | .833 | 11-1 | .903 | (-1)/-0.07 |
| FSU | 272 | 151 | 8-3 | .727 | 9-2 | .801 | (-1)/-0.074 | |
| Miami | 353 | 194 | 8-3 | .727 | 9-2 | .805 | (-1)/-0.078 | |
| UVA | 329 | 175 | 8-3 | .727 | 9-2 | .817 | (-1)/-0.09 | |
| UNC | 295 | 345 | 6-5 | .545 | 4-7 | .408 | (+2)/0.137 | |
| GT | 213 | 213 | 6-5 | .545 | 6-5/5-6 | .500 | (0)/0.045 | |
| Clemson | 236 | 229 | 6-5 | .545 | 6-5 | .518 | (0)/0.027 | |
| NCSU | 264 | 218 | 5-6 | .455 | 7-4 | .612 | (-2)/-0.157 | |
| MD | 195 | 220 | 5-6 | .455 | 5-6 | .429 | (0)/0.026 | |
| Wake | 230 | 253 | 4-7 | .364 | 5-6 | .444 | (-1)/-0.08 | |
| Duke | 183 | 322 | 2-9 | .182 | 2-9 | .208 | (0)/-0.026 | |
| BE | BC | 259 | 179 | 8-3 | .727 | 8-3 | .706 | (0)/0.021 |
| Pitt | 318 | 253 | 8-3 | .727 | 7-4 | .632 | (+1)/0.095 | |
| WVU | 343 | 216 | 8-3 | .727 | 8-3 | .7495 | (0)/-0.023 | |
| SU | 273 | 293 | 6-5 | .545 | 5-6 | .458 | (+1)/0.087 | |
| UConn | 324 | 250 | 7-4 | .636 | 7-4 | .649 | (0)/-0.013 | |
| Rutgers | 269 | 343 | 4-7 | .364 | 4-7 | .3599 | (0)/0.004 | |
| Temple | 238 | 399 | 2-9 | .182 | 2-9 | .227 | (0)/-0.045 | |
| B10 | Mich | 333 | 241 | 9-2 | .818 | 8-3 | .683 | (+1)/0.135 |
| Iowa | 262 | 186 | 9-2 | .818 | 8-3 | .741 | (+1)/0.077 | |
| Wisc | 228 | 161 | 9-2 | .818 | 8-3 | .695 | (+1)/0.123 | |
| NWest | 295 | 342 | 6-6 | .500 | 5-7 | .413 | (+1)/0.087 | |
| PU | 358 | 179 | 7-4 | .636 | 9-2 | .838 | (-2)/-0.202 | |
| OSU | 257 | 212 | 7-4 | .636 | 7-4 | .612 | (0)/0.024 | |
| MSU | 353 | 326 | 5-7 | .417 | 7-5 | .547 | (-2)/-0.13 | |
| Minn | 341 | 257 | 6-5 | .545 | 7-4 | .662 | (-1)/-0.117 | |
| PSU | 195 | 168 | 4-7 | .364 | 6-5 | .587 | (-2)/-0.223 | |
| Illinois | 240 | 323 | 3-8 | .273 | 4-7 | .331 | (-1)/-0.058 | |
| Indiana | 262 | 343 | 3-8 | .273 | 4-7 | .346 | (-1)/-0.073 | |
| B12 | Colorado | 271 | 304 | 7-5 | .583 | 5-7 | .432 | (+2)/0.151 |
| ISU | 229 | 246 | 6-5 | .545 | 5-6 | .458 | (+1)/0.087 | |
| Mizzou | 256 | 215 | 5-6 | .455 | 7-4 | .602 | (-2)/-0.147 | |
| Neb | 275 | 298 | 5-6 | .455 | 5-6 | .453 | (0)/0.002 | |
| KU | 262 | 235 | 4-7 | .364 | 6-5 | .564 | (-2)/-0.2 | |
| KSU | 326 | 337 | 4-7 | .364 | 5-6 | .480 | (-1)/-0.116 | |
| OU | 433 | 164 | 12-0 | 1.000 | 11-1 | .909 | (+1)/0.091 | |
| Texas | 385 | 178 | 10-1 | .909 | 9-2 | .862 | (+1)/0.047 | |
| TT | 389 | 283 | 7-4 | .636 | 7-4 | .680 | (0)/-0.044 | |
| TAMU | 334 | 254 | 7-4 | .636 | 7-4 | .657 | (0)/-0.021 | |
| Okie St. | 380 | 268 | 7-4 | .636 | 8-3 | .696 | (-1)/-0.06 | |
| Baylor | 224 | 406 | 3-8 | .273 | 2-9 | .196 | (+1)/0.077 | |
| Pac-10 | USC | 441 | 150 | 12-0 | 1.000 | 11-1 | .928 | (+1)/0.072 |
Cal | 410 | 147 | 10-1 | .909 | 10-1 | .919 | (0)/-0.01 | |
| ASU | 331 | 271 | 8-3 | .727 | 7-4 | .616 | (+1)/0.111 | |
| Org. St. | 282 | 273 | 6-5 | .545 | 6-5 | .519 | (0)/0.026 | |
| UCLA | 340 | 285 | 6-5 | .545 | 7-4 | .603 | (-1)/-0.058 | |
| Oregon | 282 | 282 | 5-6 | .455 | 6-5/5-6 | .500 | (0)/-0.045 | |
| WSU | 275 | 307 | 5-6 | .455 | 5-6 | .435 | (0)/0.02 | |
| Stanford | 242 | 233 | 4-7 | .364 | 6-5 | .522 | (-2)/-0.158 | |
| 'Zona | 164 | 275 | 3-8 | .273 | 2-9 | .227 | (+1)/0.046 | |
| U'Dub | 154 | 334 | 1-10 | .091 | 2-9 | .138 | (-1)/-0.047 | |
| SEC | Tenn | 340 | 288 | 9-3 | .750 | 9-3 | .721 | (0)/0.029 |
| UGA | 311 | 177 | 9-2 | .818 | 9-2 | .792 | (0)/0.026 | |
| UF | 372 | 226 | 7-4 | .636 | 8-3 | .765 | (-1)/-0.129 | |
| S. Car | 243 | 229 | 6-5 | .545 | 6-5 | .535 | (0)/0.01 | |
| UK | 173 | 341 | 2-9 | .182 | 2-9 | .167 | (0)/0.015 | |
| Vandy | 212 | 286 | 2-9 | .182 | 4-7 | .3297 | (-2)/-0.1477 | |
| Auburn | 401 | 134 | 12-0 | 1.000 | 11-1 | .931 | (+1)/0.069 | |
| LSU | 319 | 175 | 9-2 | .818 | 9-2 | .806 | (0)/0.012 | |
| 'Bama | 279 | 169 | 6-5 | .545 | 8-3 | .766 | (-2)/-0.221 | |
| Ark. | 328 | 270 | 5-6 | .455 | 7-4 | .613 | (-2)/-0.158 | |
| Ole Miss | 215 | 278 | 4-7 | .364 | 4-7 | .352 | (0)/0.012 | |
| Miss St. | 173 | 280 | 3-8 | .273 | 3-8 | .242 | (0)/0.031 | |
[Analysis]
The big overachievers in 2004 were:
1. Colorado
2. North Carolina
3. Michigan
4. Wisconsin
5. Arizona State
The big underachievers in 2004 were:
1. Penn State
2. Alabama
3. Purdue
4. Stanford/Arkansas
5. North Carolina State
Why did these teams perform the way they did? Well, that's a topic for another time.
Syracuse Perspective
Probably the most important thing to glean from this data set is that things should've been worst last year than they actually were.
Congratulations, Coach P!
Even with pitiful offensive production, Syracuse was able to play enough defense in key situations to keep itself in enough games (Purdue & Virginia aside) to potentially win.
Not bad, considering everyone assumed that the 2004 Syracuse squad underachieved last season.
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