Ohio Girls 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 girls cross country squads in the state of Ohio.

1Centerville (OH)2.721205000m 1-3 Gap (22.90)
2Gahanna Lincoln (OH)73265000m 1-3 Gap (53.00)
3Hilliard Davidson (OH)8.762275000m 1-2 Gap (23.30)
4Olentangy Liberty (OH)9.082335000m 1-4 Gap (1:36.40)
5Minster (OH)12.45365000m 1-2 Gap (40.80)
6Troy (OH)12.81435000m 1-4 Gap (1:57.50)
7McDonald (OH)12.84285000m 1-5 Gap (1:43.00)
8Granville (OH)14.63345000m 1-2 Gap (33.00)
9Brunswick (OH)14.61455000m 1-4 Gap (2:04.30)
10Ursuline Academy (OH)14.97355000m 1-5 Gap (1:56.50)
11Springboro (OH)15.22395000m 1-3 Gap (1:27.80)
12Turpin (OH)16.25495000m 1-2 Gap (1:39.20)
13Mason (OH)17.45385000m 1-2 Gap (48.30)
14Upper Arlington (OH)17.56295000m 1-4 Average (19:32.85)
15Hudson (OH)18.41373200m 1-4 Average (12:38.73)
16Saint Joseph Academy (OH)18.98385000m 1-5 Gap (1:59.90)
17Medina (OH)18.96445000m 1-2 Gap (1:16.70)
18Olentangy (OH)20.15423200m 1-4 Average (12:44.89)
19Stow-Munroe Falls (OH)23.37351600m 1-4 Average (5:36.35)
20Lakota East (OH)24.414293200m Top 4
21Kings (OH)25.08465000m Top 5
22Olentangy Orange (OH)26.94495000m 1-5 Gap (3:28.90)
23Louisville (OH)27.112485000m 1-4 Average (19:53.22), Not Enough Data
24Minerva (OH)27.511395000m 1-4 Average (19:46.44)
25Tippecanoe (OH)27.910491600m 1-4 Average (5:42.76)
26Chagrin Falls (OH)2919475000m 1-3 Gap (1:48.10)
27Defiance (OH)29.17495000m 1-5 Average (20:08.18)
28Marysville (OH)30.54491600m Top 4
29Twinsburg (OH)30.612415000m 1-5 Gap (2:05.69), Not Enough Data
30Beavercreek (OH)30.710451600m Top 4
31Woodridge (OH)32.63285000m 1-4 Average (19:32.71), Not Enough Data
32Thomas Worthington (OH)34.522455000m 1-2 Gap (1:16.76), Not Enough Data
33Gilmour Academy (OH)34.515465000m 1-5 Gap (2:40.90)
34St. Ursula Academy-Cincinnati (OH)36.02495000m Top 5
35Beaumont School (OH)36.520485000m 1-4 Gap (2:51.40)
36Solon (OH)37.313505000m 1-2 Gap (1:56.80)
37Massillon-Perry (OH)38.127395000m 1-4 Gap (1:50.20), Not Enough Data
38Sylvania Northview (OH)38.130433200m 1-4 Average (12:44.96)
39Miamisburg (OH)38.84505000m 1-4 Average (19:56.84), Not Enough Data
40Shaker Heights (OH)41.124495000m 1-4 Gap (2:57.70)
41Padua Franciscan (OH)43.63503200m 1-4 Average (12:52.88)
42Teays Valley (OH)44.527505000m Top 4, 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.