Teams

PLEASANTON 18AM4.5A

2022 ADULT 18&Over · Men's 4.5

22 players · average NTRP 4.39 / NO. CALIFORNIA

No matches recorded for this roster in this league — it may be a placeholder registration, or the season may not have started.

View scouting list →

Flight standings for Men's 4.5 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 4.07 estimated across 18 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.

Austin Tay
published 5
4.45
Lee Shin
usually #1 Doubles 67%, also #2 Doubles 33% · published
4.36
Francisco MacIas
published 4.5
4.34
James Greig
published 4.5
4.25
Jaime Santos
published 4.5
4.25
Doug Ditmer
published 4.5
4.19
Sarang Kashyap
published
4.15
Justin Zertuche
published
4.11
Michael Attiyeh
published
4.09
Vidal Pedraza
published
4.06
Sanjay Backliwal
published
4.03
Harish Natarajan
published 4.5
4.02
Steve Berry
published
4.00
Jeremy Famularcano
published
3.95
Neeraj Sharma
published
3.81
Ed Heacox
published 4
3.81
Anton Hofmann
published 4
3.75
Arnold Soleta
published 4
3.67
Walt Jefferson
published
Jordan Cabrera
published
Matt Kim
published
Shane Swinnerton
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.

James Greig + Francisco MacIas2352% games−5.9% vs expected
Sanjay Backliwal + Harish Natarajan2343% games−8.3% vs expected
Jaime Santos + Neeraj Sharma213 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.

5
Austin Tay
2W–0L career · no lines in 2022
not enough data
Lee Shin
15W–9L career · 3 lines in 2022
<1%64%36%
4.45
4.5
Francisco MacIas
4W–6L career · no lines in 2022
<1%86%14%
4.36
4.5
James Greig
5W–3L career · no lines in 2022
<1%89%11%
4.34
4.5
Jaime Santos
23W–13L career · no lines in 2022
3%95%3%
4.25
4.5
Doug Ditmer
10W–4L career · no lines in 2022
3%95%3%
4.25
Sarang Kashyap
1W–3L career · no lines in 2022
7%92%1%
4.19
Justin Zertuche
4W–3L career · no lines in 2022
13%87%<1%
4.15
Michael Attiyeh
9W–22L career · no lines in 2022
19%80%<1%
4.11
Vidal Pedraza
5W–4L career · no lines in 2022
25%75%<1%
4.09
Sanjay Backliwal
10W–32L career · no lines in 2022
33%67%<1%
4.06
4.5
Harish Natarajan
15W–12L career · no lines in 2022
41%59%<1%
4.03
Steve Berry
1W–4L career · no lines in 2022
45%55%<1%
4.02
Jeremy Famularcano
11W–8L career · no lines in 2022
51%49%<1%
4.00
Neeraj Sharma
6W–16L career · no lines in 2022
66%34%<1%
3.95
4
Ed Heacox
11W–3L career · no lines in 2022
1%92%8%
3.81
4
Anton Hofmann
6W–3L career · no lines in 2022
1%92%7%
3.81
4
Arnold Soleta
7W–13L career · no lines in 2022
3%95%3%
3.75
Walt Jefferson
0W–4L career · no lines in 2022
99%1%<1%
3.67
Jordan Cabrera
1W–0L career · no lines in 2022
not enough data
Matt Kim
1W–1L career · no lines in 2022
not enough data
Shane Swinnerton
1W–1L 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.