Teams

Pubbers

Adult 40 & Over Spring · 3.5 Men - Central Day NJD

10 players · average NTRP 3.17 / NEW JERSEY

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Schedule2 played
2022-05-22vs CENTRAL 1/Jersey AcesLost 03
L#1 DoublesGregory Quirus / Kirk LeCompte vs Chandra Rayavarapu / Shiv Kore2-6, 6-5, 0-1
L#1 SinglesPhill Karali vs Sreedhar Boyineni2-6, 1-4
L#2 DoublesJohn Kaurloto / Christopher Costa vs Chitta Sahoo / Venkat Tamavada0-6, 0-6
2022-04-24vs Jersey SlammersLost 04
L#1 DoublesKirk LeCompte / Shawn Copeland vs Biswajit Datta / Krish Ramanmenon0-6, 3-6
L#1 SinglesGregory Quirus vs Sanjay Likhar1-6, 2-6
L#2 DoublesVineet Bansal / Gary Adams vs Nikunj Patel / Mahendra Dharma0-6, 2-6
L#3 DoublesRakesh Gupta / John Kaurloto vs SANTHANARAJA RAJU / Alomgir Miah2-6, 1-6
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 - Central Day NJD 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 3.15 estimated across 4 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.

3.32
Phill Karali
usually #1 Singles 100% · published
Gregory Quirus
usually #1 Singles 50%, also #1 Doubles 50% · published 3.5
3.19
Kirk LeCompte
usually #1 Doubles 100% · published
3.12
Shawn Copeland
usually #1 Doubles 100% · published
2.98
Curtis Hillegas
published 3
Christopher Costa
usually #2 Doubles 100% · published 3
Gary Adams
usually #2 Doubles 100% · published
John Kaurloto
usually #3 Doubles 50%, also #2 Doubles 50% · published
Rakesh Gupta
usually #3 Doubles 100% · published
Vineet Bansal
usually #2 Doubles 100% · 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.

Gregory Quirus + Kirk LeCompte0540% games+2.4% vs expected
Gregory Quirus + Shawn Copeland1436% games−6.1% vs expected
John Kaurloto + Curtis Hillegas0619% games−17.0% vs expected
John Kaurloto + Christopher Costa044 matchesnot enough data
Christopher Costa + Curtis Hillegas044 matchesnot enough data
John Kaurloto + Phill Karali033 matchesnot enough data
Christopher Costa + Gregory Quirus033 matchesnot enough data
Curtis Hillegas + Shawn Copeland123 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.

Phill Karali
81W–66L career · 1 line in 2022
1%91%8%
3.32
3.5
Gregory Quirus
2W–25L career · 2 lines in 2022
not enough data
Kirk LeCompte
12W–27L career · 2 lines in 2022
8%92%1%
3.19
Shawn Copeland
9W–20L career · 1 line in 2022
18%82%<1%
3.12
3
Curtis Hillegas
6W–23L career · no lines in 2022
<1%56%44%
2.98
3
Christopher Costa
0W–16L career · 1 line in 2022
not enough data
Gary Adams
0W–1L career · 1 line in 2022
not enough data
John Kaurloto
3W–31L career · 2 lines in 2022
not enough data
Rakesh Gupta
0W–1L career · 1 line in 2022
not enough data
Vineet Bansal
0W–1L career · 1 line 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.