Louisiana 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 Louisiana.

RankTeamScoreHighestLowestWeakness
1St. Josephs Academy (LA)3.121143Mile 1-3 Gap (56.87)
2Mandeville (LA)3.361203Mile 1-2 Gap (30.72)
3Dominican (LA)5.281143Mile 1-4 Average (20:29.68)
4E.D. White (LA)8.104143Mile 1-4 Gap (1:06.10)
5Lafayette High (LA)8.361263Mile 1-3 Gap (1:36.00)
6St. Scholastica (LA)8.944303Mile 1-2 Gap (45.95)
7Mt. Carmel (LA)9.63183Mile 1-4 Average (20:44.05)
8Holy Savior Menard (LA)9.682253Mile 1-2 Gap (37.90)
9Louise S. McGehee (LA)11.75233Mile 1-2 Gap (35.40)
10St. Michael (LA)14.97333Mile 1-2 Gap (58.30)
11St. Thomas More (LA)16.07413Mile 1-2 Gap (1:33.10)
12Barbe (LA)17.04473Mile 1-2 Gap (2:05.00)
13Live Oak (LA)19.56333Mile 1-5 Average (22:05.70)
14Belle Chasse (LA)20.81363Mile 1-4 Average (21:58.62)
15Vandebilt Catholic (LA)22.04193Mile 1-3 Gap (1:03.86), Not Enough Data
16Newman (LA)22.511473Mile 1-3 Gap (3:14.92)
17Academy of Sacred Heart NO (LA)23.34283Mile 1-3 Gap (1:37.06), Not Enough Data
18University High School (LA)24.212343Mile 1-5 Average (22:11.18)
19St. Martin's Episcopal (LA)25.29243Mile 1-5 Gap (2:25.70), Not Enough Data
20Castor (LA)26.32433Mile 1-4 Average (22:21.96), Not Enough Data
21St. Thomas Aquinas (LA)26.91318--
22Zachary (LA)27.12433Mile Top 4, Not Enough Data
23Catholic High Point Coupee (LA)27.512423Mile 1-4 Gap (3:17.10)
24Woodlawn BR (LA)28.013223Mile 1-2 Gap (33.60), Not Enough Data
25Runnels (LA)29.32383Mile 1-5 Gap (3:36.70), Not Enough Data
26Loyola College Prep (LA)30.63483Mile 1-4 Average (22:34.55), Not Enough Data
27Parkview Baptist (LA)31.315413Mile 1-4 Gap (3:15.37), Not Enough Data
28Lusher Charter (LA)31.311423Mile 1-2 Gap (1:45.20), Not Enough Data
29Ouachita Parish (LA)31.44303Mile 1-4 Average (21:34.04), Not Enough Data
30Episcopal of Acadiana (LA)31.910393Mile 1-5 Gap (3:44.52), Not Enough Data
31Episcopal (LA)32.19483Mile 1-2 Gap (2:06.70), Not Enough Data
32Dutchtown (LA)34.723403Mile 1-3 Gap (2:20.34), Not Enough Data
33Beau Chene (LA)352383Mile 1-4 Average (22:07.12), Not Enough Data
34Cedar Creek (LA)35.420323Mile 1-4 Average (21:50.45), Not Enough Data
35Ursuline Academy (LA)35.413443Mile 1-3 Gap (2:33.50), Not Enough Data
36Lakeside (LA)35.717373Mile 1-2 Gap (1:07.70), Not Enough Data
37Parkway High School (LA)35.920443Mile 1-2 Gap (1:56.82), Not Enough Data
38West Feliciana (LA)36.722453Mile 1-2 Gap (1:59.80), Not Enough Data
39St. Louis High (LA)38.126463Mile 1-3 Gap (2:41.20), Not Enough Data
40Fontainebleau (LA)38.822473Mile 1-5 Gap (5:11.20), Not Enough Data
41Hahnville (LA)38.815503Mile 1-2 Gap (4:38.83), Not Enough Data
42Ponchatoula (LA)39.530363Mile 1-2 Gap (1:07.07), Not Enough Data
43St. Fredrick (LA)42.431453Mile Top 4, Not Enough Data
44Captain Shreve (LA)44.810503Mile 1-4 Gap (7:41.00), Not Enough Data
45Airline (LA)44.931463Mile 1-4 Average (22:25.00), Not Enough Data
46Ascension Catholic (LA)46.116493Mile 1-3 Gap (4:59.70), Not Enough Data
47Caddo Magnet (LA)47.228493Mile 1-4 Average (22:35.63), Not Enough Data
48Lakeshore (LA)47.242493Mile 1-2 Gap (3:48.87), 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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