What are composite team rankings?
A few years ago, MileSplit developed a data based number-cruncher system to rank cross country teams called "composite" team rankings. The rather complicated algorithm takes into account both cross country and track seasons, based on various categories and weights. It even indicates what the computer believes the biggest weakness is at this point.
Teams that did not have much of a track season or did not have at least four of their top distance runners out for track may see their scores drop. However, teams that busted it and looked great this past spring will show higher. Hopefully it is a good balance to predict who is strong coming in! It does not necessarily take into account any new freshman or transfers.
The score represents the team's weighted composite average rank across all categories. The highest column represents the highest ranking they received in a category, and conversely the lowest is the worst ranking they received in a category.
If you pull up the XC Team Scores page, you'll see a link to "Composite" scoring. This is a type of scoring that gives a team a rank on a number of different categories, with different weights on each:
- XC 5K Team Rank (normal)
- XC 5K 1-5 Split
- XC 5K 1-5 Average
- XC 5K 1-4 Rank (normal)
- XC 5K 1-4 Split
- XC 5K 1-4 Average
- XC 5K 1-3 Split
- XC 5K 1-2 Split
- Outdoor 1600m Top 4 (normal)
- Outdoor 1600m Top 4 Average
- Outdoor 3200m Top 4 (normal)
- Outdoor 3200m Top 4 Average
By using all of these factors and weighting them appropriately, we should get a really good and balanced idea of who are the best teams. This is especially designed for returning teams.
Rankings
| Rank | Team | Score | Highest | Lowest | Weakness |
|---|---|---|---|---|---|
| 1 | Urbandale High School (IA) | 18 | 1 | 8 | 4000m 1-4 Gap (21.10), Not Enough Data |
| 2 | Johnston High School (IA) | 21.2 | 1 | 21 | 4000m 1-2 Gap (24.94), Not Enough Data |
| 3 | Bettendorf High School (IA) | 22.2 | 3 | 13 | 4000m 1-4 Average (15:10.34), Not Enough Data |
| 4 | Monticello High School (IA) | 23.7 | 3 | 36 | 4000m 1-3 Gap (55.00), Not Enough Data |
| 5 | Waukee High School (IA) | 24.1 | 8 | 20 | 4000m 1-2 Gap (22.00), Not Enough Data |
| 6 | Ames High School (IA) | 24.4 | 9 | 19 | 4000m 1-5 Gap (1:04.83), Not Enough Data |
| 7 | Dubuque Hempstead High School (IA) | 25.1 | 6 | 22 | 4000m 1-4 Average (15:29.98), Not Enough Data |
| 8 | Iowa City West High School (IA) | 25.3 | 4 | 32 | 4000m 1-4 Gap (1:00.78), Not Enough Data |
| 9 | Linn-Mar High School (IA) | 25.7 | 6 | 35 | 4000m 1-2 Gap (42.68), Not Enough Data |
| 10 | Cascade, Western Dubuque High School (IA) | 26.4 | 1 | 38 | 4000m 1-5 Gap (1:31.00), Not Enough Data |
| 11 | Ankeny Centennial HS (IA) | 26.5 | 13 | 24 | 4000m 1-4 Gap (55.00), Not Enough Data |
| 12 | Muscatine High School (IA) | 27.5 | 4 | 40 | 4000m 1-2 Gap (45.33), Not Enough Data |
| 13 | Southeast Polk High School (IA) | 28.1 | 9 | 37 | 4000m 1-4 Gap (1:20.06), Not Enough Data |
| 14 | Regina High School (IA) | 28.3 | 1 | 31 | 4000m 1-4 Average (15:49.85), Not Enough Data |
| 15 | Williamsburg High School (IA) | 28.7 | 7 | 36 | 4000m 1-5 Gap (1:30.00), Not Enough Data |
| 16 | Pleasant Valley High School (IA) | 29.8 | 6 | 42 | 4000m 1-2 Gap (1:04.74), Not Enough Data |
| 17 | Decorah High School (IA) | 30.4 | 5 | 28 | 4000m 1-4 Average (15:37.00), Not Enough Data |
| 18 | Des Moines Roosevelt High School (IA) | 30.7 | 15 | 30 | 4000m 1-5 Gap (1:19.00), Not Enough Data |
| 19 | Osage High School (IA) | 30.7 | 4 | 40 | 4000m 1-4 Gap (1:25.80), Not Enough Data |
| 20 | Fort Madison High School (IA) | 31.6 | 15 | 41 | 4000m 1-5 Gap (1:46.00), Not Enough Data |
| 21 | Iowa City High School (IA) | 31.7 | 16 | 38 | 4000m 1-2 Gap (44.01), Not Enough Data |
| 22 | Valley High School (IA) | 31.7 | 18 | 29 | 4000m 1-4 Gap (58.00), Not Enough Data |
| 23 | Pocahontas Area High School (IA) | 32.0 | 18 | 39 | 4000m 1-2 Gap (44.03), Not Enough Data |
| 24 | Ankeny High School (IA) | 33.9 | 12 | 32 | 4000m 1-4 Average (15:52.25), Not Enough Data |
| 25 | Cedar Rapids Kennedy High School (IA) | 34 | 24 | 34 | 4000m 1-2 Gap (42.37), Not Enough Data |
| 26 | Gilbert High School (IA) | 34 | 17 | 30 | 4000m 1-4 Average (15:43.83), Not Enough Data |
| 27 | Mid-Prairie High School (IA) | 37.8 | 21 | 45 | 4000m 1-4 Gap (1:52.00), Not Enough Data |
| 28 | Assumption High School (IA) | 38.6 | 17 | 50 | 4000m 1-5 Gap (3:00.69), Not Enough Data |
| 29 | Epworth, Western Dubuque High School (IA) | 39.4 | 2 | 47 | 4000m 1-4 Average (16:11.50), Not Enough Data |
| 30 | Central High School (IA) | 39.4 | 24 | 47 | 4000m 1-3 Gap (1:41.00), Not Enough Data |
| 31 | Pekin High School (IA) | 39.4 | 23 | 48 | 4000m 1-4 Gap (2:13.30), Not Enough Data |
| 32 | Lewis Central High School (IA) | 40.2 | 12 | 40 | 4000m 1-5 Gap (1:38.25), Not Enough Data |
| 33 | Winterset High School (IA) | 41 | 16 | 45 | 4000m 1-4 Average (16:08.17), Not Enough Data |
| 34 | Vinton-Shellsburg High School (IA) | 41.5 | 26 | 49 | 4000m 1-5 Gap (2:42.00), Not Enough Data |
| 35 | Center Point-Urbana High School (IA) | 44.3 | 28 | 46 | 4000m 1-4 Average (16:09.00), Not Enough Data |
| 36 | Marion High School (IA) | 44.5 | 33 | 49 | 4000m 1-4 Gap (2:17.47), Not Enough Data |
| 37 | Charles City High School (IA) | 46 | 35 | 48 | 4000m Top 5, Not Enough Data |