Teams

PL-Coffey

2021 Adult 18 & Over · 3.5 Men

2 players · average NTRP 3.5 · USTA/PACIFIC NW / NORTHWEST WASHINGTON

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Scouting

Roster averages 3.41 estimated across 2 rated players. 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.

3.70
Norm Escover
usually #1 Singles 60%, also #2 Singles 40% · published 3.5
3.12
Rajesh Gatti
usually #1 Doubles 67%, also #2 Doubles 33% · published 3.5
Results6 ties
2021-06-26Won 10
W#1 SinglesNorm Escover vs Chenyang Li6-3, 6-4
2021-06-19Split 11
L#1 DoublesRajesh Gatti / Mohan Varthakavi vs Ethan Chung / SHREERAJ SUTARIA6-1, 6-2
W#1 SinglesNorm Escover vs Adam Casey7-5, 6-6
2021-06-05Lost 01
L#1 DoublesRajesh Gatti / Mohan Varthakavi vs Blaine Inafuku / Aaron Haffner6-4, 6-3
2021-05-29Won 10
W#2 SinglesNorm Escover vs N/A6-0, 6-0
2021-05-15Lost 02
L#2 DoublesRajesh Gatti / Mohan Varthakavi vs Justin Low / Andrew Lee6-3, 3-6, 1-0
L#2 SinglesNorm Escover vs Skanda Iyer6-4, 6-4
2021-05-08Lost 01
L#1 SinglesNorm Escover vs Justin Pae6-3, 6-6
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.

3.5
Norm Escover
107W–55L career
0%30%70%
3.70
3.5
Rajesh Gatti
74W–71L career
9%91%0%
3.12

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.