Teams

PL-Wood

2024 Mixed 18 & Over · 6.0

3 players · average NTRP 3.33 · USTA/PACIFIC NW / NORTHWEST WASHINGTON

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Scouting

Roster averages 3.01 estimated across 3 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.

3.18
Gregory Snow
usually #1 Doubles 100% · published 3.5
3.04
Manivel Chandrasekaran
usually #3 Doubles 80%, also #1 Doubles 20% · published 3.5
2.80
Jill Snow
usually #1 Doubles 100% · published 3
Results5 ties
2023-11-25Lost 01
L#1 DoublesGregory Snow / Jill Snow vs Darla Donnelly / Hesper Yu4-6, 6-3, 1-0
2023-11-11Lost 01
L#1 DoublesTom Miller / Jill Snow vs Janelle Stewart / Bryan Goode6-2, 3-6, 1-0
2023-11-04Lost 02
L#1 DoublesJill Snow / Gregory Snow vs Jennifer Turner / Matthew Rust7-6, 6-1
L#3 DoublesLisa Small / Manivel Chandrasekaran vs Jane Repensek / Gang Feng6-4, 7-5
2023-10-27Won 10
W#1 DoublesJill Snow / Gregory Snow vs Chester Weir / Janice Merlino6-2, 7-5
2023-10-08Lost 01
L#3 DoublesLisa Small / Manivel Chandrasekaran vs Ellen Acuario / David Zhao6-2, 4-6, 1-0
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
Gregory Snow
100W–74L career
3%97%0%
3.18
3.5
Manivel Chandrasekaran
47W–51L career
23%77%0%
3.04
3
Jill Snow
51W–47L career
5%87%8%
2.80

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.