MPRC-Avenoso

2026 Adult 18 & Over · 4.0 Men

10 players · average NTRP 4 · USTA/PACIFIC NW / NORTHERN OREGON

Scouting

Roster averages 3.75 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.

3.91

Gregg Palmer

usually #2 Doubles 57%, also #1 Doubles 29% · published 4

3.91

Lane Elliott

usually #1 Singles 60%, also #1 Doubles 20% · published 4

3.91

Kirt Eftekhar

usually #3 Doubles 50%, also #2 Doubles 30% · published 4

3.86

Frank O'Mahony

usually #2 Singles 75%, also #3 Doubles 25% · published 4

3.77

David Hoiland

usually #2 Doubles 67%, also #3 Doubles 33% · published 4

3.76

Patrick Brewer

usually #1 Doubles 100% · published 4

3.67

Ken Avenoso

usually #1 Doubles 67%, also #2 Doubles 17% · published 4

3.63

Zhitong Chen

usually #3 Doubles 100% · published 4

3.59

Seth Yount

usually #3 Doubles 80%, also #2 Doubles 20% · published 4

3.54

John Yu

usually #3 Doubles 50%, also #1 Doubles 25% · published 4

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.

Gregg Palmer

181W–77L career

0%94%6%

3.91

Lane Elliott

7W–16L career

0%91%9%

3.91

Kirt Eftekhar

76W–29L career

0%96%4%

3.91

Frank O'Mahony

31W–6L career

0%94%6%

3.86

David Hoiland

135W–59L career

0%100%0%

3.77

Patrick Brewer

68W–59L career

1%99%0%

3.76

Ken Avenoso

69W–67L career

4%96%0%

3.67

Zhitong Chen

76W–42L career

11%88%0%

3.63

Seth Yount

178W–57L career

13%87%0%

3.59

John Yu

136W–64L career

22%78%0%

3.54

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.