Teams

PL-Aces & Lobs-Khullar

2024 Adult 18 & Over · 3.0 Men

2 players · average NTRP 3.5 · USTA/PACIFIC NW / NORTHWEST WASHINGTON

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Scouting

Roster averages 3.08 estimated across 2 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.

3.12
Rajesh Gatti
usually #1 Doubles 39%, also #2 Doubles 39% · published 3.5
3.04
Manivel Chandrasekaran
usually #3 Doubles 80%, also #1 Doubles 20% · published 3.5
Results6 ties
2024-05-11Lost 01
L#3 DoublesAmit Kejriwal / Rajesh Gatti vs Kaushik Purohit / Xin Che6-1, 6-4
2024-05-04Won 10
W#1 DoublesSudhakar Pitchumani / Rajesh Gatti vs Andy Quach / Remi Dargent3-6, 6-4, 1-0
2024-04-28Lost 01
L#1 DoublesRajesh Gatti / Sudhakar Pitchumani vs Erwin Gao / Yu Xiao5-7, 6-3, 1-0
2024-04-26Won 10
W#3 DoublesRajesh Gatti / Amit Kejriwal vs Zach Zaborowski / Manny McBride6-3, 6-4
2024-04-19Won 10
W#2 DoublesRajesh Gatti / Vishwanath Nayak vs Spencer Addicott / Kalpesh Bhimani6-4, 6-2
2024-04-14Won 10
W#3 DoublesSudhakar Pitchumani / Rajesh Gatti vs David Hasbrook / Michael Robinson6-0, 6-2
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.

3.5
Rajesh Gatti
74W–71L career
9%91%0%
3.12
3.5
Manivel Chandrasekaran
47W–51L career
23%77%0%
3.04

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.