Teams

MV-Schill

2025 Coed 18-39 · 6.0 Coed Combo

1 players · average NTRP 2.5 · USTA/PACIFIC NW / NORTHERN OREGON

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Scouting

Roster averages 2.67 estimated across 1 rated player. No lineup is published in advance, so the column below is where each player has actually been used — a captain's habits are the best available forecast. Sign in and claim your record to see who you have played.

2.67
Sarah Schill
usually #1 Female Doubles 63%, also #1 Female Singles 25% · published 2.5
Results8 ties
2025-03-08Lost 01
L#1 Female DoublesSarah Schill / Carrie Schill vs Mary Morgan / Samantha Nakata6-5
2025-03-02Lost 01
L#1 Female SinglesSarah Schill vs Jenica Susi6-0
2025-02-23Won 10
W#1 Female DoublesSarah Schill / Hailey Straube vs Elana Grabel / Becca Perry6-3
2025-02-22Lost 01
L#1 Female DoublesCarrie Schill / Sarah Schill vs Michelle Chow / Jessica Li6-1
2025-02-09Lost 01
L#1 Female SinglesSarah Schill vs Jessica Becker6-1
2025-01-26Lost 01
L#2 Mixed DoublesSarah Schill / Robert Pisarchuk vs Austin Curran / Wei Hua6-2
2025-01-25Won 10
W#1 Female DoublesCarrie Schill / Sarah Schill vs Bri Koral / Holly Phillips6-4
2025-01-11Lost 01
L#1 Female DoublesSarah Schill / Hailey Straube vs Genelynne Jian / Heidi Seinige6-4
A tie can be incomplete. Tell us if someone is missing.
i
Grouped by tie — one fixture, several lines. A line shows only when a player on it is someone we have indexed, so an early-season tie for a newly-added team can look short. This also means the line count here will not match the header, which counts individual player appearances.
Roster

Ordered by our estimated dynamic rating, which is why two players at the same published level are not tied — a published 4.0 says nothing about where inside the band someone sits.

2.5
Sarah Schill
21W–34L career
0%7%93%
2.67

Three percentages are the year-end projection — chance of moving down, staying, moving up — and the number on the right is our estimated dynamic rating, which USTA never publishes. Percentages are blank where a player has too few matches this season, or at a level where the model does not yet beat a base-rate guess; the estimate is a weaker claim than a probability and survives where those do not.