Teams

SUNNYVALE MTC 18AM4.0A

2025 ADULT 18&Over · Men's 4.0

9 players · average NTRP 3.50 / 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 →
Schedule2 played
2025-05-31vs SUNNYVALE MTC 18AM4.0FLost 23
W#1 DoublesFreddy di Chiaro / Tejas Naik vs David Cao / Larry Hui6-0, 6-1
L#1 SinglesAbhishek Kottamasu vs Lu Li3-6, 4-6
L#2 DoublesJair Saavedra / Shiv Trisal vs Harrison Tsang / James Yin1-6, 7-6, 0-1
W#2 SinglesRamprasaath R. Selvaraju vs Edison Zhou6-2, 6-1
L#3 DoublesVinay Nataraj / Omkar Rege vs Yongfa Fan / Jingping Wang3-6, 1-6
2025-04-27vs SUNNYVALE MTC 18AM4.0FLost 03
L#1 DoublesSwapnil Pawar / Omkar Rege vs Lejian Dai / Jackie Guo3-6, 0-6
L#2 DoublesAbhishek Kottamasu / Tejas Naik vs Lu Li / Henry Zheng6-3, 2-6, 1-0
L#3 DoublesJair Saavedra / Ramprasaath R. Selvaraju vs Yongfa Fan / Shuchun Zhao6-2, 1-6, 0-1
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 Men's 4.0 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 3.61 estimated across 7 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.

4.01
Freddy di Chiaro
usually #1 Doubles 100% · published
3.89
Tejas Naik
usually #1 Doubles 50%, also #2 Doubles 50% · published
3.73
Ramprasaath R. Selvaraju
usually #2 Singles 50%, also #3 Doubles 50% · published
3.67
Jair Saavedra
usually #2 Doubles 50%, also #3 Doubles 50% · published
3.41
Omkar Rege
usually #3 Doubles 50%, also #1 Doubles 50% · published
3.34
Swapnil Pawar
usually #1 Doubles 100% · published
Abhishek Kottamasu
usually #1 Singles 50%, also #2 Doubles 50% · published 3.5
3.23
Vinay Nataraj
usually #3 Doubles 100% · published
Shiv Trisal
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.

Jair Saavedra + Tejas Naik3260% games+0.3% vs expected
Freddy di Chiaro + Tejas Naik303 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.

Freddy di Chiaro
5W–0L career · 1 line in 2025
<1%48%52%
4.01
Tejas Naik
7W–4L career · 2 lines in 2025
<1%78%21%
3.89
Ramprasaath R. Selvaraju
2W–4L career · 2 lines in 2025
5%92%3%
3.73
Jair Saavedra
16W–16L career · 2 lines in 2025
<1%11%89%
3.67
Omkar Rege
1W–6L career · 2 lines in 2025
73%27%<1%
3.41
Swapnil Pawar
0W–6L career · 1 line in 2025
87%13%<1%
3.34
3.5
Abhishek Kottamasu
0W–4L career · 2 lines in 2025
not enough data
Vinay Nataraj
0W–8L career · 1 line in 2025
97%3%<1%
3.23
Shiv Trisal
0W–1L career · 1 line in 2025
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.