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IRV-Gilbertson/Naffziger

2022 Mixed 40 & Over · 6.0 Mixed

9 players · average NTRP 3.06 · USTA/PACIFIC NW / NORTHERN OREGON

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Scouting

Roster averages 2.84 estimated across 8 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.

3.28
Omar Martinez
usually #1 Doubles 75%, also #2 Doubles 25% · published 3.5
3.02
Erin Gleason
usually #2 Doubles 100% · published 3.5
2.85
Michelle Boucher
usually #1 Doubles 100% · published 3
2.83
Joel Greenblum
usually #3 Doubles 67%, also #2 Doubles 33% · published 3
2.81
Deborah Cohen
usually #3 Doubles 60%, also #2 Doubles 40% · published 3
2.80
Paul Ecker
usually #2 Doubles 67%, also #3 Doubles 33% · published 3
—
Megan Ullmann
usually #1 Doubles 100% · published 3
2.65
Craig Beard
usually #1 Doubles 80%, also #2 Doubles 20% · published 0
2.49
Ken Naffziger
usually #3 Doubles 100% · published 2.5
Results8 ties
2022-03-20Won 2–1
L#1 DoublesBrad Mathewson / Michelle Boucher vs Andrea Kropp / Karl Kropp6-1, 6-0
W#2 DoublesOmar Martinez / Deborah Cohen vs Andrew Geisler / Tamara Phillips2-6, 6-3, 1-0
W#3 DoublesIrene Gilbertson / Ken Naffziger vs N/A6-0, 6-0
2022-02-26Split 1–1
L#1 DoublesCraig Beard / Megan Ullmann vs Robin Burak / Matt Savage6-2, 6-3
W#2 DoublesDana Austin / Joel Greenblum vs JT Smith / Stephanie Smith4-6, 6-4, 1-0
2022-02-19Lost 0–2
L#1 DoublesCraig Beard / Dana Austin vs John Phillips / Deanna Phillips6-0, 6-3
L#3 DoublesPaul Ecker / Deborah Cohen vs Brendan Finn / Edwardeen Hilts6-4, 6-3
2022-02-12Lost 0–2
L#1 DoublesMegan Ullmann / Craig Beard vs Mihye Ko / Chinwoo Kim6-1, 6-1
L#2 DoublesErin Gleason / Michael Gentry vs Misug Kim / Daniel M Kim6-0, 6-3
2022-01-30Won 2–1
W#1 DoublesMegan Ullmann / Craig Beard vs Crystal Ounaphom / Kevin Grainger4-6, 6-4, 1-0
W#2 DoublesDeborah Cohen / Michael Gentry vs Cheri Mosbrucker / Keith Mosbrucker6-2, 6-4
L#3 DoublesIrene Gilbertson / Ken Naffziger vs Sharon Wise / Ronald Skoletsky7-6, 6-4
2022-01-29Lost 0–3
L#1 DoublesMichelle Boucher / Omar Martinez vs Kiersten Lake / Paul OHollaren6-2, 6-3
L#2 DoublesErin Gleason / Craig Beard vs Theresa Gonzales / Monte Gonzales6-2, 6-3
L#3 DoublesIrene Gilbertson / Ken Naffziger vs Autumn Bunch / Mark Persinger6-1, 6-2
2022-01-23Won 2–1
W#1 DoublesDana Austin / Omar Martinez vs Valerie Neill / John Brady6-3, 7-5
W#2 DoublesKate Quisling / Paul Ecker vs Ilona Vondolovski / Christian Molstrom6-3, 6-4
L#3 DoublesDeborah Cohen / Joel Greenblum vs Raquel Rich / Michael Rich6-4, 6-4
2022-01-08Lost 0–3
L#1 DoublesMegan Ullmann / Omar Martinez vs Sara Vanderhoff / Scott Vanderhoff6-1, 6-3
L#2 DoublesIrene Gilbertson / Paul Ecker vs Sara Crate / Jay Hopson6-3, 6-1
L#3 DoublesDeborah Cohen / Joel Greenblum vs Sarah Robertson / Greg Popma6-4, 6-4
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
Omar Martinez
75W–48L career
6%87%6%
3.28
3.5
Erin Gleason
43W–17L career
35%65%0%
3.02
3
Michelle Boucher
45W–40L career
1%93%6%
2.85
3
Joel Greenblum
8W–8L career
4%86%10%
2.83
3
Deborah Cohen
65W–38L career
0%99%1%
2.81
3
Paul Ecker
36W–49L career
0%98%1%
2.80
3
Megan Ullmann
20W–15L career
not enough data
—
0
Craig Beard
3W–19L career
13%87%1%
2.65
2.5
Ken Naffziger
14W–17L career
0%38%62%
2.49

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.