Teams

CGM-Huggins/Groves

2020 Adult 55 & Over · 7.0 Men

2 players · average NTRP 3 · USTA/PACIFIC NW / NORTHERN OREGON

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Scouting

Roster averages 2.82 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.

2.82
Steven Darling
usually #1 Doubles 80%, also #2 Doubles 20% · published 3
Jon Mandeville
usually #1 Doubles 50%, also #3 Doubles 25% · published 3
Results6 ties
2019-11-16Lost 01
L#1 DoublesDon Dowling / Steven Darling vs Steven Keo / Frank Brown6-1, 6-0
2019-11-10Lost 01
L#1 DoublesSteven Darling / Don Dowling vs Ken Dragoon / Paul Kachel6-4, 6-4
2019-11-03Lost 01
L#2 DoublesJon Mandeville / Steven Darling vs Ron Reimers / David Butts6-4, 2-6, 1-0
2019-10-26Lost 01
L#1 DoublesSteven Darling / Jon Mandeville vs John Knudson-Martin / Kevin Semonsen6-2, 7-5
2019-10-05Lost 01
L#1 DoublesJon Mandeville / Steven Darling vs Craig Frasier / Atul Bhargava6-4, 6-2
2019-09-15Lost 01
L#3 DoublesDon Dowling / Jon Mandeville vs Edward Lang / Jim Lekas6-0, 6-1
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
Steven Darling
63W–87L career
0%99%1%
2.82
3
Jon Mandeville
31W–39L career
not enough data

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.