The best American freshman in NCAA Division I cross country in 2026 is Katy Zang of Indiana, ranked #5 overall among women by the USTFCCCA's XCRI and #2 on the HealthAI women's list. The top freshman man is Caden Leonard of North Carolina, XCRI #75 and #14 on the HealthAI men's list. In all, 11 first-year runners make the HealthAI rankings: 3 men and 8 women, based on results through November 2, 2026.
This post sits under our guide to the 2026 NCAA cross country rankings. The full lists, with every runner's case, are on the rankings page.
Who counts as a freshman on these lists?
Every runner below is listed as Fr (1), meaning true college year 1, on the HealthAI ranking. That ranking keeps only runners HealthAI has checked as American, aged 22 or under, and in college year 1 to 4, then leaves them in the XCRI order. All 11 freshmen are marked Provisional American: their official school bio lists a US hometown and a US high school. Nationality is never guessed from a name. Each hometown below is copied from the school bio.
Freshmen ranked elsewhere in the XCRI top 100 who are not on the HealthAI list are not covered here.
Who are the best American freshman women?
- Katy Zang, Indiana. HealthAI #2, XCRI #5. Hometown: Orient, Ohio. Best 2026: 3rd at Big Ten Champs, 19:13.9; 2nd at Notre Dame Invitational, 15:35.34. Rating 1194.2 ± 10.2 from 4 races, Tier 2.
- Allison Lee, Penn. HealthAI #32, XCRI #110. Hometown: Princeton, N.J. Best 2026: Won Ivy League Heptagonal Champs, 20:14.0 (by 11.1s); 35th at Pre-Nationals, 20:09.4. Rating 1140.0 ± 11.8 from 3 races, Tier 4.
- Addison Ritzenhein, Northern Arizona. HealthAI #34, XCRI #115. Hometown: Colorado. Best 2026: no 2026 race in HealthAI's official-results files yet. Rating 1139.2 ± 11.8 from 3 races, Tier 4.
- Cassidy Armstrong, Duke. HealthAI #39, XCRI #125. Hometown: Seattle, Wash. Best 2026: 28th at ACC Champs, 19:53.2; 33rd at Pre-Nationals, 20:06.5. Rating 1136.8 ± 11.8 from 3 races, Tier 4.
- Sundara Weber, Duke. HealthAI #42, XCRI #131. Hometown: Sandwich, Ill. Best 2026: 39th at ACC Champs, 20:08.9; 53rd at Pre-Nationals, 20:24.8. Rating 1134.7 ± 11.8 from 3 races, Tier 5.
- Maggie McCormick, Florida. HealthAI #44, XCRI #134. Hometown: Brightwaters, N.Y. Best 2026: 23rd at SEC Champs, 19:50.4; 40th at Nuttycombe, 20:11.7. Rating 1133.3 ± 11.8 from 3 races, Tier 5.
- Lily Alder, BYU. HealthAI #45, XCRI #137. Hometown: Utah. Best 2026: 27th at Big 12 Champs, 20:38.8; 12th at Cowboy Jamboree, 20:29.0. Rating 1135.2 ± 11.8 from 3 races, Tier 5.
- Latham West, Portland. HealthAI #49, XCRI #150. Hometown: Bonney Lake, Wash. Best 2026: Won WCC Champs, 20:31.2 (by 5.3s); 44th at Pre-Nationals, 20:17.9. Rating 1129.4 ± 11.8 from 3 races, Tier 5.
Zang stands apart. She is the only one of these 11 freshmen inside the XCRI top 50, and the only one of them with 4 rated races. Two other freshmen won their conference titles: Allison Lee at the Ivy League Heptagonals and Latham West at the WCC.
Who are the best American freshman men?
- Caden Leonard, North Carolina. HealthAI #14, XCRI #75. Hometown: Southlake, Texas. Best 2026: 9th at ACC Champs, 23:00.0; 19th at Pre-Nationals, 23:34.9. Rating 1144.2 ± 15.4 from 3 races, Tier 3.
- Grady Lenn, Wisconsin. HealthAI #29, XCRI #103. Hometown: Green Bay, Wis. Best 2026: 10th at Big Ten Champs, 23:19.1; 54th at Nuttycombe, 23:31.1. Rating 1136.5 ± 15.4 from 3 races, Tier 3.
- Sean Fries, Stanford. HealthAI #34, XCRI #110. Hometown: Minnetonka, Minn. Best 2026: 27th at ACC Champs, 23:17.4; 63rd at Nuttycombe, 23:36.1. Rating 1134.3 ± 15.4 from 3 races, Tier 3.
All three men sit in Tier 3, the same tier as many of the juniors and seniors around them.
Can you compare these freshmen by their times?
No. The times above come from different courses on different days. This season the SEC course ran about 50 seconds faster than the Big 12 course, so Maggie McCormick's 19:50.4 at SEC and Lily Alder's 20:38.8 at Big 12 say little about who is fitter. Katy Zang's 15:35.34 at Notre Dame and her 19:13.9 at the Big Ten meet are not a gap in form either: they are simply different races. XCRI adjusts every race for how fast it ran, which is why the rating, not the clock, sets the order. Our explainer on how the XCRI rankings work covers the adjustment in detail.
Why are freshman rankings especially uncertain?
Under the XCRI method, every rating comes with an uncertainty (the ± figure) that shrinks as an athlete races more. Any athlete with fewer than 3 races is marked provisional. None of these 11 freshmen is provisional today: Zang has 4 races and the rest have 3. But that is still a thin record, and three things make first-year numbers move more than most:
- Small samples. Three races is the minimum to drop the provisional tag. With 3 races, a man's uncertainty here is ± 15.4 and a woman's ± 11.8. With 4, Zang's falls to ± 10.2.
- Gaps smaller than the error. Grady Lenn (1136.5) and Sean Fries (1134.3) are 2.2 points apart, far inside their ± 15.4. On the women's side, Lily Alder is rated 1135.2 yet listed behind Maggie McCormick at 1133.3. Inside a tier, XCRI treats differences like these as within the uncertainty.
- One season only. XCRI counts this season's races and nothing earlier, and every race counts the same. A freshman has no earlier college season behind the number, and each new race shifts an average built on only three or four.
The ages on these lists are also estimates. Each freshman is listed at 18 est, worked out from high school graduation year rather than a published date of birth.
Read the ranks as a snapshot of the season so far, not a verdict on anyone's ceiling.
How your HealthAI coach applies this
Your HealthAI coach does not rank you against other runners. It builds your own training: a 2-week plan written from the runs you log in the health portal and your check-ins on sleep, soreness and energy, then adjusted as those change. For a first-year college runner, that means training shaped by how your body is handling a new season, one check-in at a time. See how it works for college runners, or see plans, from $30 a month.
Your coach builds this around your training data. Start at HealthAI.coach.
Sources
- USTFCCCA XCRI rankings
- USTFCCCA XCRI: how it works
- Official results from TFRRS and meet results, as listed on the rankings page