Yesterday's attempt at team similarity scores got me wondering about what the future holds for other surprise teams. I chose two of the more interesting surprise teams IMO, Rutgers and Washington. With a quick glance at Rutgers preseason schedule, most prognosticators probably had them at worst, 3-1. Still, an undefeated Scarlet Knight's squad in late September is something to take note of. Certainly few expected the Washington Huskies to have already matched their win total for the past two seasons in one month. The mathematical details for calculating the similarity scores are at the end of this post so as not to discourage you from reading further. Also, as explained yesterday, I'm only using a one-season look back. Hopefully next week I'll expand the look backs to two or three seasons to get a more representative sample. Still, I think this method has its merits.
The most similar teams to Rutgers (2006) from last season--similarity score in parentheses and final record following
1. Minnesota (856) 7-5
2. UCLA (823) 10-2
3. Florida (775.25) 9-3
4. Penn State (666.75) 11-1
5. Wisconsin (666.5) 10-3
I think these comparables are pretty good for the Knights, except for Penn State. Like Rutgers, each team, with the exception of Penn State, went to a bowl game the season before. Also like Rutgers, all of these teams, with the exception of Penn State, were good, but hardly elite BCS conference teams. With Rutgers remaining schedule, a 9 or 10 win season is certainly a possibility.
The most similar teams to Washington (2006) from last season-- similarity score in parentheses and final record following
1. South Florida (649.5) 6-6
2. Kansas (456.5) 7-5
3. Texas A&M (198.25) 5-6
The Huskies don't have nearly as strong comps primarily because their record (2-9) was so bad last season. Both South Florida and Kansas seem like good comparables. They both finished 4-7 the year prior, before breaking out and participating in a low to mid level bowl game. I'd expect the same from Washington.
Here's the methodology.
1. Start with 1000 points
2. Through 'x' number of games take the difference in winning percentage multiply by 1000 and subtract from 1000
example: Team A is 4-0 and Team B 3-1, then the difference in winning percentage would be 1-.75=.25, multiplying this by 1000=250, subtract this number from 1000
3. For every game difference in home/road inequality subtract 50 points
example: Team A has played 2 road games and 2 home games, Team B has played 3 road games and 1 home game, subtract 50 points (neutral sites count as half games)
4. Subtract the difference in point differential through 'x' number of games
5. Subtract the difference in average opponents' Sagarin Rating (I think its a pretty good measure of schedule strength)
6. Subtract the difference multiplied by 1000 in previous year's record (we need to know how good the team's were in the previous season)
7. Subtract the difference multiplied by 1000 in previous year's Pythagorean Winning Percentage (a better indicator of team strength than actual record)
8. The remaining points are the teams' similarity score (the higher the better)