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Notes:

For the rankings origin story, please follow the link here. I have included a version of how the rankings are created at the end of the page so that you understand how it works!

  • The raw score is calculated using a custom algorithm that takes into account the margin of victory of each game, maxed out to 40 points for 11AA and 11AAA, and 50 points for 11A, 11B, 9AA, 9A and 9B.
  • The raw score is listed in the far right column under “Rating”. This number represents the projected margin of victory against the average team in 11-Man or 9-Man.
  • A 1-point increase in Rank+ is = to a 1% increase in raw score.
  • Rank+ is based on the raw scores comparison for all of 11-Man or 9-Man.
  • All Rank+ numbers are rounded to the nearest whole. Therefore, though teams may have the same Rank+, when broken down further they are separated by a Rank+ of .01 to .99. There are no ties (I do not believe in ties).

Power Rankings

11AAATeamRecordRank+Rating
1 Lincoln12-020866.07
2 Brandon Valley7-418753.47
3 O’Gorman9-318350.74
4 Harrisburg8-317445.48
5 Jefferson6-415835.77
6 Roosevelt3-714225.89
7 Washington2-813621.97
8 Stevens2-812918.06
9 Central0-91137.86
11AATeamRecordRank+Rating
1 Pierre11-117646.65
2 Yankton10-216037.04
3 Tea Area7-415935.89
4 Watertown7-415131.12
5 Aberdeen4-613521.36
6 Sturgis6-412917.49
7 Huron4-612716.48
8 Spearfish4-61159.05
9 Mitchell2-71052.88
10 Brookings1-895-3.05
11 Douglas1-876-14.49
11ATeamRecordRank+Rating
1 Dell Rapids12-014929.81
2 West Central10-213320.37
3 SFC8-312414.86
4 Canton7-312414.76
5 Dakota Valley6-41105.85
6 Lennox6-51095.33
7 Madison3-797-1.57
8 Vermillion3-683-10.65
9 Chamberlain4-682-11.03
10 Beresford2-779-13.07
11 Milbank2-764-21.95
12 Custer2-761-23.88
13 Belle Fourche1-851-29.73
14 Lakota Tech0-913-53.19
11BTeamRecordRank+Rating
1 Winner10-113622.15
2 Hot Springs11-113320.24
3 EP-J10-212414.65
4 Tri-Valley6-412012.23
5 Sioux Valley9-11169.98
6 St Thomas More4-51063.63
7 RC Christian8-31052.96
8 Deuel9-11010.73
9 B-E/E5-492-4.97
10 W/WS/SC7-290-6.27
11 Roncalli7-386-8.81
12 Webster Area4-583-10.62
13 Wagner6-483-10.66
14 Groton Area5-479-12.76
15 Parker5-475-15.01
16 C/WL3-570-18.54
17 T-D/A/AC/DC4-470-18.60
18 MV/P3-668-19.73
19 MC/M1-760-24.29
20 Mobridge-Pollock2-660-24.64
21 Sisseton3-556-27.17
22 Hill City3-552-29.50
23 Flandreau3-549-31.36
24 Lead-Deadwood1-743-34.77
25 M/H-H2-632-41.79
26 Redfield1-729-43.25
27 Baltic0-825-45.71
28 Scotland/Menno1-721-48.51
29 Dakota Hills0-80-61.25
9AATeamRecordRank+Rating
1 Parkston12-020355.31
2 Howard10-218344.54
3 Hamlin9-217741.35
4 Hanson7-316936.79
5 Platte-Geddes9-215529.57
6 E-LB8-215529.25
7 Wall8-215228.09
8 F/M/FA7-314021.47
9 K/WL4-613519.04
10 L/FA5-413317.46
11 Stanley County7-213016.24
12 Bon Homme3-612613.82
13 Viborg-Hurley3-612412.69
14 Ipswich4-51094.94
15 Britton-Hecla5-489-5.86
16 GPL4-589-6.02
17 White River3-573-14.42
18Garretson1-768-17.07
19 Dupree3-561-21.10
20 Bennett County2-653-25.02
21 Florence/Henry0-846-29.19
9ATeamRecordRank+Rating
1 Warner12-018143.66
2 Canistota8-316434.11
3 Alcester-Hudson9-114926.24
4 Philip10-114825.81
5 Deubrook Area8-414222.46
6 Wolsey-Wessington4-512815.03
7 Gregory5-512412.65
8 Chester5-51179.28
9 HC/B7-21084.11
10 Castlewood5-51063.33
11 Estelline/Hendricks4-589-2.59
12 Colman-Egan2-788-6.39
13 Centerville4-592-9.68
14 Timber Lake4-574-14.04
15 Burke2-772-14.93
16 Lyman6-371-15.80
17 W/SS2-649-27.27
18 O-R/R1-738-33.44
19 Northwestern0-828-38.60
20 I/LP0-827-39.10
21 Newell0-80-53.65
9BTeamRecordRank+Rating
1 Faulkton Area10-215127.50
2 De Smet8-313920.72
3 Avon10-213217.12
4 Corsica-Stickney7-312111.44
5 St. Mary5-41042.31
6 H/SA7-399-0.50
7 Hitchcock-Tulare5-595-2.56
8 Kadoka Area4-687-7.17
9 Potter County5-685-8.00
10 Sully Buttes3-682-9.56
11 Gayville-Volin3-780-10.77
12 Lemmon/McIntosh3-667-17.91
13 Colome2-755-24.22
14 Irene-Wakonda0-849-27.55
15 Faith1-848-27.86
16 Jones County2-747-28.48
17 New Underwood1-842-31.05
18 Arlington1-742-31.35
19 SBA1-716-45.15

Projections

Projections are now found under the Playoff Projections section.



System

So the summer before this, I did a ton of research into computerized rankings and what makes a good system. I am a huge numbers guy and I wanted an unbiased ranking for the state.

I take the scores from each game, put them into my system. Now each team started with a random rating and to be honest, it makes no difference what that starting rating is, as I’ll explain in a second.

The computer then takes those ratings and uses it to make a forecast of the game score. Then I input the actual game score. The difference between those two numbers is the error.

I then have the computer square the error for each game and sum up all the errors from every game in the state. (I separate 11-Man & 9-Man into two different pages. Formula is the same for both.) Then I have the system try to make the sum of the squared errors as low as possible.

This action changes the teams ratings so that the forecast is as close to the margin of victory as possible. Therefore the more data (more games) the system has, the more accurate it is.

I then take those raw ratings for each class and figure out the average rating for that class. From there, I set that average to 100, with each point being a 1% increase in raw rating. You’ll see this 100-based scale most common in baseball.

Also of note I set limits to how high you can beat a team. For 9-Man, it’s the mercy rule & for non-mercy rule classes, it’s one standard deviation of the average final scores. Last year that was 40 points and it tends to stay the same.

Basically, what that means is if you mercy rule a team, it doesn’t help or hurt you to score more than 50.

But overall, in simplest terms, wins tell the computer what your floor is and loses tell the computer what your ceiling is. The computer takes all those ceilings & floors and tells you what you averaged out that season.