Teams

SAC-Boyce

2026 Adult 40 & Over · 3.5 Women

10 players · average NTRP 3.2 · USTA/PACIFIC NW / NORTHERN OREGON

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Scouting

Roster averages 3.05 estimated across 10 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.

3.38
Kim Tellin
usually #3 Doubles 57%, also #1 Doubles 29% · published 3.5
3.37
Timothea Barnatan
usually #1 Doubles 57%, also #2 Doubles 29% · published 3.5
3.21
Cathy Gatzke
usually #1 Doubles 100% · published 3.5
3.18
Shari Levelle
usually #1 Doubles 100% · published 3.5
3.16
Lara Greenberg
usually #1 Singles 40%, also #1 Doubles 30% · published 3
3.01
Toni Eastwood
usually #2 Doubles 50%, also #3 Doubles 25% · published 3
2.94
Grainne Koeberl
usually #1 Doubles 50%, also #3 Doubles 50% · published 3
2.82
Lina Gao
usually #2 Doubles 44%, also #1 Singles 22% · published 3
2.76
Melissa Tom
usually #2 Doubles 50%, also #1 Singles 50% · published 3
2.69
Melissa Maxwell
usually #2 Doubles 75%, also #1 Doubles 13% · 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
Kim Tellin
110W–71L career
0%97%3%
3.38
3.5
Timothea Barnatan
95W–117L career
0%98%2%
3.37
3.5
Cathy Gatzke
53W–92L career
2%98%0%
3.21
3.5
Shari Levelle
63W–57L career
3%97%0%
3.18
3
Lara Greenberg
73W–43L career
0%33%67%
3.16
3
Toni Eastwood
44W–73L career
0%79%21%
3.01
3
Grainne Koeberl
56W–65L career
0%93%7%
2.94
3
Lina Gao
46W–86L career
0%99%1%
2.82
3
Melissa Tom
39W–38L career
1%98%0%
2.76
3
Melissa Maxwell
23W–25L career
3%96%0%
2.69

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.