Teams

CGM-Kropp

2026 Mixed 18 & Over · 7.0 Mixed

10 players · average NTRP 3.45 · USTA/PACIFIC NW / NORTHERN OREGON

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Scouting

Roster averages 3.15 estimated across 9 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.

3.31
Andrea Kropp
usually #2 Doubles 67%, also #3 Doubles 33% · published 3.5
3.25
Adrian Alaniz
usually #1 Doubles 75%, also #2 Doubles 25% · published 3.5
3.25
Karl Kropp
usually #2 Doubles 67%, also #1 Doubles 33% · published 3.5
3.25
Paul Barner
usually #1 Doubles 67%, also #3 Doubles 33% · published 3.5
Ray Baxter
usually #3 Doubles 100% · published 3.5
3.21
Vicki Blunt
usually #1 Doubles 100% · published 3.5
3.20
Cinthia Erickson
usually #2 Doubles 50%, also #1 Doubles 50% · published 3.5
3.14
ALFREDO ALANIS
usually #3 Doubles 75%, also #2 Doubles 25% · published 3.5
3.00
Donna Baxter
usually #3 Doubles 100% · published 3.5
2.77
ROSY ALANIS
usually #3 Doubles 43%, also #1 Doubles 29% · published 3
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
Andrea Kropp
51W–81L career
0%99%1%
3.31
3.5
Adrian Alaniz
6W–6L career · type T
6%91%3%
3.25
3.5
Karl Kropp
11W–28L career
4%94%2%
3.25
3.5
Paul Barner
7W–12L career · type M
8%87%5%
3.25
3.5
Ray Baxter
7W–22L career
not enough data
3.5
Vicki Blunt
89W–109L career
2%98%0%
3.21
3.5
Cinthia Erickson
37W–32L career
3%97%0%
3.20
3.5
ALFREDO ALANIS
35W–53L career
7%93%0%
3.14
3.5
Donna Baxter
15W–57L career · type A
35%65%0%
3.00
3
ROSY ALANIS
43W–68L career
1%98%1%
2.77

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.