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Pythagorean Mayhem

[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

Pythagorean Method - 2004/5 Season
Conf.TeamPFPAAW/LAW/L%PW/L PW/L%DIF
ACCVTech38715110-2.83311-1.903(-1)/-0.07
FSU2721518-3.7279-2.801(-1)/-0.074
Miami3531948-3.7279-2.805(-1)/-0.078
UVA3291758-3.7279-2.817(-1)/-0.09
UNC2953456-5.5454-7.408(+2)/0.137
GT2132136-5.5456-5/5-6.500(0)/0.045
Clemson2362296-5.5456-5.518(0)/0.027
NCSU2642185-6.4557-4.612(-2)/-0.157
MD1952205-6.4555-6.429(0)/0.026
Wake2302534-7.3645-6.444(-1)/-0.08
Duke1833222-9.1822-9.208(0)/-0.026
BEBC2591798-3.7278-3.706(0)/0.021
Pitt3182538-3.7277-4.632(+1)/0.095
WVU3432168-3.7278-3.7495(0)/-0.023
SU2732936-5.5455-6.458(+1)/0.087
UConn3242507-4.6367-4.649(0)/-0.013
Rutgers2693434-7.3644-7.3599(0)/0.004
Temple2383992-9.1822-9.227(0)/-0.045
B10Mich3332419-2.8188-3.683(+1)/0.135
Iowa2621869-2.8188-3.741(+1)/0.077
Wisc2281619-2.8188-3.695(+1)/0.123
NWest2953426-6.5005-7.413(+1)/0.087
PU3581797-4.6369-2.838(-2)/-0.202
OSU2572127-4.6367-4.612(0)/0.024
MSU3533265-7.4177-5.547(-2)/-0.13
Minn3412576-5.5457-4.662(-1)/-0.117
PSU1951684-7.3646-5.587(-2)/-0.223
Illinois2403233-8.2734-7.331(-1)/-0.058
Indiana2623433-8.2734-7.346(-1)/-0.073
B12Colorado2713047-5.5835-7.432(+2)/0.151
ISU2292466-5.5455-6.458(+1)/0.087
Mizzou2562155-6.4557-4.602(-2)/-0.147
Neb2752985-6.4555-6.453(0)/0.002
KU2622354-7.3646-5.564(-2)/-0.2
KSU3263374-7.3645-6.480(-1)/-0.116
OU43316412-01.00011-1.909(+1)/0.091
Texas38517810-1.9099-2.862(+1)/0.047
TT3892837-4.6367-4.680(0)/-0.044
TAMU3342547-4.6367-4.657(0)/-0.021
Okie St.3802687-4.6368-3.696(-1)/-0.06
Baylor2244063-8.2732-9.196(+1)/0.077
Pac-10USC44115012-01.00011-1.928(+1)/0.072

Cal

41014710-1.90910-1.919(0)/-0.01
ASU3312718-3.7277-4.616(+1)/0.111
Org. St.2822736-5.5456-5.519(0)/0.026
UCLA3402856-5.5457-4.603(-1)/-0.058
Oregon2822825-6.4556-5/5-6.500(0)/-0.045
WSU2753075-6.4555-6.435(0)/0.02
Stanford2422334-7.3646-5.522(-2)/-0.158
'Zona1642753-8.2732-9.227(+1)/0.046
U'Dub1543341-10.0912-9.138(-1)/-0.047
SECTenn3402889-3.7509-3.721(0)/0.029
UGA3111779-2.8189-2.792(0)/0.026
UF3722267-4.6368-3.765(-1)/-0.129
S. Car2432296-5.5456-5.535(0)/0.01
UK1733412-9.1822-9.167(0)/0.015
Vandy2122862-9.1824-7.3297(-2)/-0.1477
Auburn40113412-01.00011-1.931(+1)/0.069
LSU3191759-2.8189-2.806(0)/0.012
'Bama2791696-5.5458-3.766(-2)/-0.221
Ark.3282705-6.4557-4.613(-2)/-0.158
Ole Miss2152784-7.3644-7.352(0)/0.012
Miss St.1732803-8.2733-8.242(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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