I'm sure this reads like an elementary school book for Howard and Tim. :icon_evil:
His model's algorithm:
1. What am I trying to do? My model attempts to estimate the number of wins a team will achieve during the 2013 season. It's a low resolution model that provides me the winner; or if it can't calculate a clear winner, declares the game a toss up. It doesn't provide point totals or margins of victory so it can't be used for 'against the spread' calculations.
2. How do I estimate wins? Thatās the secret sauce, and a good cook never reveals the actual ingredients. However, in the interest of not giving the critics additional ammunition to sharpshoot my work, hereās a basic laydown of the components and steps involved:
His model's algorithm:
1. What am I trying to do? My model attempts to estimate the number of wins a team will achieve during the 2013 season. It's a low resolution model that provides me the winner; or if it can't calculate a clear winner, declares the game a toss up. It doesn't provide point totals or margins of victory so it can't be used for 'against the spread' calculations.
2. How do I estimate wins? Thatās the secret sauce, and a good cook never reveals the actual ingredients. However, in the interest of not giving the critics additional ammunition to sharpshoot my work, hereās a basic laydown of the components and steps involved:
a. Each team's scoring offense and scoring defense is normalized to a Z-score using the difference between a team's actual offensive PPG and defensive PPG and the average PPG of the entire FBS and dividing it by the standard deviation of all FBS PPGs. This gives me a more usable (apples to apples principle) comparison between teams as well as across statistical categories.
b. I calculate an āadvantage' score for each team by subtracting an opponent's Def Z-score from the team's Off Z- score (Off Advantage) and by subtracting an opponent's Off Z-score from the team's Def Z-score (Def Advantage). I then add those to advantage scores together to get combined advantage score.
c. Using data from all games from 2007-2011 I calculated the average MOV and standard deviation MOV for each combined advantage score. With this information I used excel to calculate the probability of a MOV of at least 1 (less than 1 would be a loss). For the excel nerds, that calculation is (1-(normdist(1, ave MOV, sd MOV, true) ).
d. Because I'm a firm believer in confronting the reality that chance plays a much larger role in things like sports than we choose to admit, my model deals with chance by calculating the probability of winning for both teams. When I run the model, if both teams are predicted to win or lose, I call the game a toss-up. If there is a clear winner, that game counts as a win.
e. I run the model a couple thousand times and record the results of each run.
f. I count the results for each team. For both wins and toss ups I calculate the average, max, min, and median of the results.
g. Finally, I set predicted number of wins this way: Number of Wins + ½ of tossup games rounded to the nearest integer (if ½ of toss up games is 2.5 I count it as 3).
The Southeastern Conference
[TABLE="width: 529, align: left"]
<colgroup><col><col><col><col><col span="8"></colgroup><tbody>[TR]
[TD]Rank[/TD]
[TD]Team[/TD]
[TD]Conference[/TD]
[TD]Exp. Wins[/TD]
[TD]p(5)[/TD]
[TD]p(6)[/TD]
[TD]p(7)[/TD]
[TD]p(8)[/TD]
[TD]p(9)[/TD]
[TD]p(10)[/TD]
[TD]p(11)[/TD]
[TD]p(12)[/TD]
[/TR]
[TR]
[TD]8[/TD]
[TD]Georgia[/TD]
[TD]SEC East[/TD]
[TD]9.54[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]0.97[/TD]
[TD]0.88[/TD]
[TD]0.66[/TD]
[TD]0.36[/TD]
[TD]0.13[/TD]
[TD]0.03[/TD]
[/TR]
[TR]
[TD]16[/TD]
[TD]Vanderbilt[/TD]
[TD]SEC East[/TD]
[TD]8.82[/TD]
[TD]1.00[/TD]
[TD]0.99[/TD]
[TD]0.93[/TD]
[TD]0.75[/TD]
[TD]0.44[/TD]
[TD]0.17[/TD]
[TD]0.04[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]25[/TD]
[TD]South Carolina[/TD]
[TD]SEC East[/TD]
[TD]8.58[/TD]
[TD]0.99[/TD]
[TD]0.96[/TD]
[TD]0.87[/TD]
[TD]0.66[/TD]
[TD]0.38[/TD]
[TD]0.16[/TD]
[TD]0.05[/TD]
[TD]0.01[/TD]
[/TR]
[TR]
[TD]26[/TD]
[TD]Florida[/TD]
[TD]SEC East[/TD]
[TD]8.54[/TD]
[TD]0.99[/TD]
[TD]0.96[/TD]
[TD]0.86[/TD]
[TD]0.65[/TD]
[TD]0.38[/TD]
[TD]0.16[/TD]
[TD]0.04[/TD]
[TD]0.01[/TD]
[/TR]
[TR]
[TD]78[/TD]
[TD]Tennessee[/TD]
[TD]SEC East[/TD]
[TD]5.60[/TD]
[TD]0.69[/TD]
[TD]0.37[/TD]
[TD]0.12[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]89[/TD]
[TD]Missouri[/TD]
[TD]SEC East[/TD]
[TD]5.12[/TD]
[TD]0.54[/TD]
[TD]0.26[/TD]
[TD]0.09[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]101[/TD]
[TD]Kentucky[/TD]
[TD]SEC East[/TD]
[TD]4.10[/TD]
[TD]0.20[/TD]
[TD]0.04[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]1[/TD]
[TD]Alabama[/TD]
[TD]SEC West[/TD]
[TD]10.94[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]0.98[/TD]
[TD]0.84[/TD]
[TD]0.47[/TD]
[TD]0.13[/TD]
[/TR]
[TR]
[TD]5[/TD]
[TD]Texas A&M[/TD]
[TD]SEC West[/TD]
[TD]9.90[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]0.96[/TD]
[TD]0.80[/TD]
[TD]0.46[/TD]
[TD]0.15[/TD]
[TD]0.03[/TD]
[/TR]
[TR]
[TD]38[/TD]
[TD]LSU[/TD]
[TD]SEC West[/TD]
[TD]7.84[/TD]
[TD]0.99[/TD]
[TD]0.93[/TD]
[TD]0.75[/TD]
[TD]0.45[/TD]
[TD]0.18[/TD]
[TD]0.04[/TD]
[TD]0.01[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]51[/TD]
[TD]Mississippi State[/TD]
[TD]SEC West[/TD]
[TD]7.06[/TD]
[TD]0.95[/TD]
[TD]0.80[/TD]
[TD]0.52[/TD]
[TD]0.23[/TD]
[TD]0.06[/TD]
[TD]0.01[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]70[/TD]
[TD]Mississippi[/TD]
[TD]SEC West[/TD]
[TD]5.93[/TD]
[TD]0.74[/TD]
[TD]0.48[/TD]
[TD]0.23[/TD]
[TD]0.07[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]99[/TD]
[TD]Arkansas[/TD]
[TD]SEC West[/TD]
[TD]4.34[/TD]
[TD]0.31[/TD]
[TD]0.11[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]100[/TD]
[TD]Auburn[/TD]
[TD]SEC West[/TD]
[TD]4.27[/TD]
[TD]0.30[/TD]
[TD]0.11[/TD]
[TD]0.03[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
</tbody>[/TABLE]
b. I calculate an āadvantage' score for each team by subtracting an opponent's Def Z-score from the team's Off Z- score (Off Advantage) and by subtracting an opponent's Off Z-score from the team's Def Z-score (Def Advantage). I then add those to advantage scores together to get combined advantage score.
c. Using data from all games from 2007-2011 I calculated the average MOV and standard deviation MOV for each combined advantage score. With this information I used excel to calculate the probability of a MOV of at least 1 (less than 1 would be a loss). For the excel nerds, that calculation is (1-(normdist(1, ave MOV, sd MOV, true) ).
d. Because I'm a firm believer in confronting the reality that chance plays a much larger role in things like sports than we choose to admit, my model deals with chance by calculating the probability of winning for both teams. When I run the model, if both teams are predicted to win or lose, I call the game a toss-up. If there is a clear winner, that game counts as a win.
e. I run the model a couple thousand times and record the results of each run.
f. I count the results for each team. For both wins and toss ups I calculate the average, max, min, and median of the results.
g. Finally, I set predicted number of wins this way: Number of Wins + ½ of tossup games rounded to the nearest integer (if ½ of toss up games is 2.5 I count it as 3).
The Southeastern Conference
[TABLE="width: 529, align: left"]
<colgroup><col><col><col><col><col span="8"></colgroup><tbody>[TR]
[TD]Rank[/TD]
[TD]Team[/TD]
[TD]Conference[/TD]
[TD]Exp. Wins[/TD]
[TD]p(5)[/TD]
[TD]p(6)[/TD]
[TD]p(7)[/TD]
[TD]p(8)[/TD]
[TD]p(9)[/TD]
[TD]p(10)[/TD]
[TD]p(11)[/TD]
[TD]p(12)[/TD]
[/TR]
[TR]
[TD]8[/TD]
[TD]Georgia[/TD]
[TD]SEC East[/TD]
[TD]9.54[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]0.97[/TD]
[TD]0.88[/TD]
[TD]0.66[/TD]
[TD]0.36[/TD]
[TD]0.13[/TD]
[TD]0.03[/TD]
[/TR]
[TR]
[TD]16[/TD]
[TD]Vanderbilt[/TD]
[TD]SEC East[/TD]
[TD]8.82[/TD]
[TD]1.00[/TD]
[TD]0.99[/TD]
[TD]0.93[/TD]
[TD]0.75[/TD]
[TD]0.44[/TD]
[TD]0.17[/TD]
[TD]0.04[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]25[/TD]
[TD]South Carolina[/TD]
[TD]SEC East[/TD]
[TD]8.58[/TD]
[TD]0.99[/TD]
[TD]0.96[/TD]
[TD]0.87[/TD]
[TD]0.66[/TD]
[TD]0.38[/TD]
[TD]0.16[/TD]
[TD]0.05[/TD]
[TD]0.01[/TD]
[/TR]
[TR]
[TD]26[/TD]
[TD]Florida[/TD]
[TD]SEC East[/TD]
[TD]8.54[/TD]
[TD]0.99[/TD]
[TD]0.96[/TD]
[TD]0.86[/TD]
[TD]0.65[/TD]
[TD]0.38[/TD]
[TD]0.16[/TD]
[TD]0.04[/TD]
[TD]0.01[/TD]
[/TR]
[TR]
[TD]78[/TD]
[TD]Tennessee[/TD]
[TD]SEC East[/TD]
[TD]5.60[/TD]
[TD]0.69[/TD]
[TD]0.37[/TD]
[TD]0.12[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]89[/TD]
[TD]Missouri[/TD]
[TD]SEC East[/TD]
[TD]5.12[/TD]
[TD]0.54[/TD]
[TD]0.26[/TD]
[TD]0.09[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]101[/TD]
[TD]Kentucky[/TD]
[TD]SEC East[/TD]
[TD]4.10[/TD]
[TD]0.20[/TD]
[TD]0.04[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]1[/TD]
[TD]Alabama[/TD]
[TD]SEC West[/TD]
[TD]10.94[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]0.98[/TD]
[TD]0.84[/TD]
[TD]0.47[/TD]
[TD]0.13[/TD]
[/TR]
[TR]
[TD]5[/TD]
[TD]Texas A&M[/TD]
[TD]SEC West[/TD]
[TD]9.90[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]1.00[/TD]
[TD]0.96[/TD]
[TD]0.80[/TD]
[TD]0.46[/TD]
[TD]0.15[/TD]
[TD]0.03[/TD]
[/TR]
[TR]
[TD]38[/TD]
[TD]LSU[/TD]
[TD]SEC West[/TD]
[TD]7.84[/TD]
[TD]0.99[/TD]
[TD]0.93[/TD]
[TD]0.75[/TD]
[TD]0.45[/TD]
[TD]0.18[/TD]
[TD]0.04[/TD]
[TD]0.01[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]51[/TD]
[TD]Mississippi State[/TD]
[TD]SEC West[/TD]
[TD]7.06[/TD]
[TD]0.95[/TD]
[TD]0.80[/TD]
[TD]0.52[/TD]
[TD]0.23[/TD]
[TD]0.06[/TD]
[TD]0.01[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]70[/TD]
[TD]Mississippi[/TD]
[TD]SEC West[/TD]
[TD]5.93[/TD]
[TD]0.74[/TD]
[TD]0.48[/TD]
[TD]0.23[/TD]
[TD]0.07[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]99[/TD]
[TD]Arkansas[/TD]
[TD]SEC West[/TD]
[TD]4.34[/TD]
[TD]0.31[/TD]
[TD]0.11[/TD]
[TD]0.02[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
[TR]
[TD]100[/TD]
[TD]Auburn[/TD]
[TD]SEC West[/TD]
[TD]4.27[/TD]
[TD]0.30[/TD]
[TD]0.11[/TD]
[TD]0.03[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[TD]0.00[/TD]
[/TR]
</tbody>[/TABLE]