Teams

LOTC-Ferrer/Berkman 9.0

2025 Coed 18-39 · 9.0 Coed Combo

12 players · average NTRP 4.36 · USTA/PACIFIC NW / NORTHERN OREGON

View scouting list →
Scouting

Roster averages 3.98 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.

Avery Liening
published 5
4.13
Sarah Ferrer
published 4.5
4.09
Rebecca Yu
usually #1 Female Singles 83%, also #1 Female Doubles 17% · published 4.5
4.08
Matt Simmering
usually #1 Male Singles 80%, also #1 Male Doubles 20% · published 4.5
4.07
Ellen Mader
usually #1 Female Doubles 63%, also #1 Mixed Doubles 25% · published 4.5
4.06
Mike Zielinski
usually #1 Male Singles 50%, also #1 Male Doubles 50% · published 4
4.05
Tarynn Berkman
published 4.5
3.97
Mitchell Earle
usually #1 Male Singles 80%, also #1 Male Doubles 20% · published 0
3.91
Kristin Taylor
published 4.5
3.82
William Creger
usually #1 Male Singles 71%, also #1 Male Doubles 29% · published 4
Jacob Bethards
usually #1 Male Doubles 67%, also #1 Male Singles 33% · published 4
3.61
Matt Deems
usually #1 Male Doubles 100% · published 4
Results8 ties
2025-03-08Split 11
W#1 Male DoublesMatt Deems / Jacob Bethards vs Marshall Zhang / Bao Bui6-5
L#1 Male SinglesJacob Bethards vs John Bui6-0
2025-03-02Lost 13
L#1 Female DoublesEllen Mader / Kristin Taylor vs Kaytlynn Kolb / Kaitlin Bos6-4
L#1 Female SinglesRebecca Yu vs Kaitlin Bos6-2
W#1 Male DoublesMike Zielinski / Matt Simmering vs Aiden Brasier / Elijah Nelson6-5
L#1 Male SinglesMatt Simmering vs Juan Padilla6-0
2025-02-23Split 11
W#1 Female SinglesRebecca Yu vs Erica Drake6-4
L#1 Male DoublesWilliam Creger / Christopher Evola vs Jason Qian / Mingyang Liu6-4
2025-02-15Won 20
W#1 Male DoublesMitchell Earle / Matt Simmering vs Aidan Lee / Darren Ly6-3
W#1 Male SinglesMitchell Earle vs Kyahn Daraee6-5
2025-01-31Lost 02
L#1 Male DoublesJacob Bethards / Matt Simmering vs WILLIAM EDWARDS / Joe Mcroberts6-4
L#1 Male SinglesMatt Simmering vs WILLIAM EDWARDS6-5
2025-01-18Lost 03
L#1 Female DoublesTarynn Berkman / Ellen Mader vs Megan Flores / Grace Lee6-1
L#1 Male DoublesMitchell Earle / William Creger vs Bao Bui / Franklin Truong6-3
L#1 Male SinglesMitchell Earle vs Bobby Cruz6-3
2025-01-11Lost 02
L#1 Male DoublesJacob Bethards / Mitchell Earle vs Dante Sterling / Khang Chu6-2
L#1 Male SinglesMitchell Earle vs Dante Sterling6-4
2025-01-05Won 21
W#1 Female DoublesTarynn Berkman / Rebecca Yu vs Gigi Davies / Wanqi Huang6-2
W#1 Male DoublesMike Zielinski / Matt Deems vs Dante Sterling / Khang Chu6-5
L#1 Male SinglesMike Zielinski vs Dante Sterling6-0
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.

5
Avery Liening
9W–2L career
not enough data
4.5
Sarah Ferrer
145W–57L career
1%99%0%
4.13
4.5
Rebecca Yu
64W–49L career
4%96%0%
4.09
4.5
Matt Simmering
104W–61L career
4%96%0%
4.08
4.5
Ellen Mader
97W–47L career
5%95%0%
4.07
4
Mike Zielinski
57W–38L career
0%65%35%
4.06
4.5
Tarynn Berkman
78W–28L career
7%93%0%
4.05
0
Mitchell Earle
15W–14L career
23%77%0%
3.97
4.5
Kristin Taylor
49W–39L career
36%64%0%
3.91
4
William Creger
71W–41L career
1%96%3%
3.82
4
Jacob Bethards
9W–20L career
not enough data
4
Matt Deems
92W–49L career
23%76%1%
3.61

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.