Teams

Arbor Park - Drink Team

Adult 40 & Over 3.0 - 4.5 Men Wednesday · 4.5 Men

13 players · average NTRP 4.50 / TEXAS

View scouting list →
Schedule6 played
2026-03-25vs LLTC - GooniesLost 12
W#1 DoublesTim Rogers / Ramkumar Aduru vs George Hernandez / Vishesh Singh6-4, 3-6, 1-0
L#1 SinglesHakim Baghdadli vs Nazario Denova2-6, 4-6
L#2 DoublesJose Salinas / Jerry Agrapidis vs Alain Tran / Michael Giordanelli2-6, 3-6
2026-03-18vs LLTC - Old SchoolLost 03
L#1 DoublesRamkumar Aduru / Francisco Feregrino vs Tomas Huynh / Warren Miller4-6, 3-6
L#1 SinglesJose Salinas vs Travis Smith4-6, 1-6
L#2 DoublesJerry Agrapidis / Justice Awuku vs Bjoern Steckel / Nick Hiemstra1-6, 1-6
2026-02-25vs LLTC - GooniesLost 04
L#1 DoublesJerry Lopez / Francisco Feregrino vs Vishesh Singh / George Hernandez2-6, 1-6
L#1 SinglesJose Salinas vs Carlos Anaya4-6, 3-6
L#2 DoublesGurpreet Kalra / James Cohick vs Dirk Mueller / Bill Zindler2-6, 3-6
L#3 DoublesJustice Awuku / Jerry Agrapidis vs Luther Saiki / Nathan Daniels2-6, 1-6
2026-02-18vs LLTC - Old SchoolLost 13
L#1 DoublesHong-Shig Shim / Jerry Lopez vs Ryan Cooper / Albert Piasecki2-6, 3-6
L#1 SinglesRamkumar Aduru vs Bjoern Steckel3-6, 2-6
W#2 DoublesJerry Agrapidis / Tim Rogers vs Nick Hiemstra / Jeffrey Jordan6-2, 6-1
L#3 DoublesCamilo Rodriguez / Hakim Baghdadli vs James Bui / Trent Ackhurst2-6, 2-6
2026-02-04vs LLTC - GooniesLost 03
L#1 DoublesJerry Lopez / Hong-Shig Shim vs Nazario Denova / Matt Dean2-6, 3-6
L#2 DoublesTim Rogers / Hakim Baghdadli vs Bill Zindler / Dirk Mueller3-6, 6-4, 0-1
L#3 DoublesJustice Awuku / Jerry Agrapidis vs Nathan Daniels / Luther Saiki3-6, 1-6
2026-01-28vs LLTC - Old SchoolSplit 22
W#1 DoublesCamilo Rodriguez / Ervin Magarino vs Albert Piasecki / Ryan Cooper6-4, 1-6, 1-0
L#1 SinglesJose Salinas vs Warren Miller2-6, 1-6
L#2 DoublesJerry Lopez / Francisco Feregrino vs Phong Regent / Tomas Huynh6-3, 2-6, 0-1
W#3 DoublesHong-Shig Shim / Tim Rogers vs Brent Wassell / Travis Smith6-4, 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 standings2 teams · 4.5 Men
TeamWLInd. WInd. LSets lostGames lost
1LLTC - Old School4215920184
2Arbor Park - Drink Team0642042267

Ordered by team wins, then losses, then sets lost — the order USTA uses to seed a flight. Individual wins are lines, not ties.

See the full flight, with every team’s record

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 3.90 estimated across 12 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.

4.25
Tim Rogers
usually #2 Doubles 50%, also #3 Doubles 25% · published
Camilo Rodriguez
published 4.5
4.13
Ervin Magarino
usually #1 Doubles 100% · published
4.10
Hong-Shig Shim
usually #1 Doubles 67%, also #3 Doubles 33% · published
4.02
Ramkumar Aduru
usually #1 Doubles 67%, also #1 Singles 33% · published
3.98
Jerry Lopez
usually #1 Doubles 75%, also #2 Doubles 25% · published
3.97
Hakim Baghdadli
usually #2 Doubles 33%, also #1 Singles 33% · published
3.90
Gurpreet Kalra
usually #2 Doubles 100% · published
3.83
Francisco Feregrino
usually #1 Doubles 67%, also #2 Doubles 33% · published
3.77
Jerry Agrapidis
usually #2 Doubles 60%, also #3 Doubles 40% · published
3.66
Jose Salinas
usually #1 Singles 75%, also #2 Doubles 25% · published
3.65
James Cohick
usually #2 Doubles 100% · published
3.56
Justice Awuku
usually #3 Doubles 67%, also #2 Doubles 33% · 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.

Tim Rogers + Hong-Shig Shim6352% games+5.9% vs expected
Tim Rogers + Ramkumar Aduru241355% games−2.3% vs expected
Jose Salinas + Jerry Agrapidis2646% games−4.7% vs expected
Jerry Lopez + Hong-Shig Shim3448% gamesnot enough data
Jerry Lopez + Francisco Feregrino2443% gamesnot enough data
Ramkumar Aduru + Hong-Shig Shim0532% gamesnot enough data
Camilo Rodriguez + Ervin Magarino3251% gamesnot enough data
Jerry Lopez + Tim Rogers303 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.

Tim Rogers
45W–27L career · 4 lines in 2026
4%93%4%
4.25
4.5
Camilo Rodriguez
13W–13L career · no lines in 2026
not enough data
Ervin Magarino
21W–11L career · 1 line in 2026
17%82%<1%
4.13
Hong-Shig Shim
26W–24L career · 3 lines in 2026
24%76%<1%
4.10
Ramkumar Aduru
41W–28L career · 3 lines in 2026
45%55%<1%
4.02
Jerry Lopez
27W–35L career · 4 lines in 2026
57%43%<1%
3.98
Hakim Baghdadli
4W–10L career · 3 lines in 2026
58%42%<1%
3.97
Gurpreet Kalra
34W–16L career · 1 line in 2026
<1%75%25%
3.90
Francisco Feregrino
31W–32L career · 3 lines in 2026
1%88%12%
3.83
Jerry Agrapidis
17W–25L career · 5 lines in 2026
95%5%<1%
3.77
Jose Salinas
20W–34L career · 4 lines in 2026
13%86%1%
3.66
James Cohick
2W–12L career · 1 line in 2026
99%1%<1%
3.65
Justice Awuku
1W–6L career · 3 lines in 2026
>99%<1%<1%
3.56

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.