Teams

Mike's 3.5M #1

2022 Adult 18 and Over League · 3.5 Men

12 players · average NTRP 3.57 / MAUI

View scouting list →
Schedule4 played
2022-07-09vs Mike's 3.5M #3Won 10
W#1 DoublesRobin Hirata / Clarence Kenui vs Don Booth / Gerald Kalua6-2, 6-2
2022-07-03vs Mike's 3.5M #4Won 10
W#2 DoublesJames Bauer / Clarence Kenui vs Eugene Gelmanovich / Jonathan Lau6-2, 6-2
2022-06-19Won 10
W#1 DoublesJeff Bettendorf / Clarence Kenui vs Mark Lausterer / Gerry Viloria6-4, 6-3
2022-06-05vs Mike's 3.5M #2Won 10
W#1 DoublesJames Bauer / Clarence Kenui vs Charles Bisquera / Tamio Iwado6-3, 6-3
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.

Flight standings for 3.5 Men have not been collected yet. Where we have them we show every team in the flight ranked, with this team highlighted. The crawler is still filling in older seasons and flights.

ScoutingWhere each opponent usually plays

Signed-in extra: whether this captain plays strict strength order or mixes it up, from every doubles line they have put out. Create a free account to see it.

Roster averages 3.30 estimated across 6 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.

3.45
Emerson Timmins
usually #2 Doubles 67%, also #1 Doubles 17% · published 4
3.41
James Simmons
usually #2 Doubles 100% · published 3.5
3.35
Edgar Cordero
published 3.5
3.31
Jeff Bettendorf
usually #2 Doubles 67%, also #1 Doubles 33% · published
Eugene Hong
published 3.5
James Bauer
usually #1 Doubles 50%, also #2 Doubles 50% · published 3.5
3.24
Clarence Kenui
usually #1 Doubles 75%, also #2 Doubles 25% · published 3.5
3.04
Gordie Brown
published 3.5
Michael Kinoshita
usually #2 Doubles 67%, also #3 Doubles 33% · published
Robert Claxton
usually #1 Doubles 100% · published
Robin Hirata
published
Roy Matsuyama
published
Established pairs

Doubles pairs from this roster with three or more matches together anywhere — ordered by performance against what the rating gap predicted, not by record.

Robin Hirata + Robert Claxton4158% gamesnot enough data
Eugene Hong + Clarence Kenui224 matchesnot enough data
Robin Hirata + Roy Matsuyama213 matchesnot enough data
Robin Hirata + Emerson Timmins303 matchesnot enough data
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. Lines played in this team’s season are shown beside each name.

4
Emerson Timmins
79W–95L career · 6 lines in 2022
64%36%<1%
3.45
3.5
James Simmons
36W–37L career · 1 line in 2022
<1%76%24%
3.41
3.5
Edgar Cordero
22W–18L career · no lines in 2022
<1%87%13%
3.35
Jeff Bettendorf
77W–71L career · 3 lines in 2022
1%92%7%
3.31
3.5
Eugene Hong
29W–12L career · no lines in 2022
not enough data
3.5
James Bauer
61W–40L career · 6 lines in 2022
not enough data
3.5
Clarence Kenui
65W–33L career · 4 lines in 2022
3%95%2%
3.24
3.5
Gordie Brown
45W–40L career · no lines in 2022
38%62%<1%
3.04
Michael Kinoshita
30W–63L career · 3 lines in 2022
not enough data
Robert Claxton
19W–10L career · 3 lines in 2022
not enough data
Robin Hirata
20W–18L career · no lines in 2022
not enough data
Roy Matsuyama
36W–35L career · no lines in 2022
not enough data

Three percentages are where each player stands right now: the chance they are below their band, inside it, or above it, on the way they are playing this season. The number on the right is our estimated dynamic rating, which USTA never publishes. This is today rather than a forecast of December, because a forecast has to assume future matches and cannot know whether someone will even be offered them. 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.

Not affiliated with or endorsed by the USTA. Ratings labelled as published are USTA year-end figures; anything we describe as an estimate is ours, not USTA’s. Match data is from USTA TennisLink.