Ohio Boys Preseason Composite XC Team Rankings

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Find out who our data based ranking system projects in the preseason as the top returning boys cross country squads in the state of Ohio.

RankTeamScoreHighestLowestWeakness
1Hudson (OH)4.721185000m 1-5 Gap (49.06)
2Medina (OH)7.322171600m 1-4 Average (4:38.89)
3Centerville (OH)7.442315000m 1-2 Gap (20.00)
4Lancaster (OH)7.921235000m 1-4 Average (16:32.34)
5Hilliard Davidson (OH)9.841375000m 1-2 Gap (26.93)
6St. Xavier (Cin.) (OH)113415000m 1-5 Gap (1:33.70)
7Lexington (OH)11.11295000m 1-4 Gap (50.28)
8Pickerington North (OH)14.35405000m 1-5 Gap (1:31.28)
9St. Ignatius (OH)15.45275000m 1-4 Average (16:37.38)
10St. Edward (OH)16.17235000m 1-4 Average (16:31.95)
11Massillon Jackson (OH)16.12465000m 1-4 Average (16:52.85)
12Defiance (OH)17.26335000m 1-4 Average (16:44.58)
13Olentangy Liberty (OH)17.46383200m 1-4 Average (10:25.38)
14Mason (OH)18.21425000m 1-4 Gap (1:25.55)
15Kings (OH)20.11423200m 1-4 Average (10:27.89)
16East Canton (OH)20.213425000m 1-2 Gap (39.38)
17Dublin Jerome (OH)20.76425000m 1-3 Gap (54.50)
18Unioto (OH)21.48393200m 1-4 Average (10:25.43)
19Dublin Coffman (OH)23.22505000m 1-5 Gap (2:34.70)
20Olentangy Orange (OH)24.211475000m Top 5
21Elder (OH)24.22375000m 1-4 Average (16:47.24)
22Kenston (OH)24.78491600m Top 4
23Carroll (OH)25.09313200m 1-4 Average (10:22.17)
24Hilliard Darby (OH)25.17355000m 1-5 Average (16:53.13)
25Perrysburg High School (OH)25.13463200m 1-4 Average (10:31.91)
26Bay (OH)26.112225000m 1-3 Gap (24.00), Not Enough Data
27Fairfield-Leesburg (OH)27.219405000m 1-2 Gap (36.00)
28Anderson (OH)27.812485000m Top 4
29Rocky River (OH)27.810285000m 1-3 Gap (35.10), Not Enough Data
30Whitmer (OH)29.213485000m Top 5
31Pickerington Central (OH)29.92495000m 1-5 Gap (2:30.19)
32Turpin (OH)31.64483200m Top 4
33Solon (OH)32.22435000m 1-4 Gap (1:40.20), Not Enough Data
34Gahanna Lincoln (OH)34.419451600m 1-4 Average (4:44.90)
35Dublin Scioto (OH)34.417485000m 1-4 Gap (1:53.97)
36Buckeye Valley (OH)35.516495000m 1-2 Gap (1:43.40)
37Strongsville (OH)35.724425000m 1-4 Average (16:49.39), Not Enough Data
38Heath (OH)37.420455000m 1-4 Average (16:52.56), Not Enough Data
39Woodridge (OH)37.53501600m 1-4 Average (4:46.97)
40Mentor (OH)3811505000m 1-5 Average (17:04.19), Not Enough Data
41Vandalia-Butler (OH)38.130433200m Top 4, Not Enough Data
42Thomas Worthington (OH)39.15505000m 1-3 Gap (2:07.30), Not Enough Data
43Granville (OH)39.312495000m 1-4 Average (16:57.29), Not Enough Data
44LaSalle (OH)40.311403200m 1-4 Average (10:27.48), Not Enough Data
45Worthington Kilbourne (OH)41.312483200m 1-4 Average (10:33.48)
46Walsh Jesuit (OH)42.832505000m Top 5
47Edison-Milan (OH)43.121465000m 1-5 Average (16:59.94), Not Enough Data
48Ashland HS (OH)43.815495000m 1-5 Average (17:01.88), Not Enough Data
49New Philadelphia (OH)44.729475000m 1-2 Gap (1:15.69), Not Enough Data

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.

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