Teams

Scanio - You've Been Served

2025 Montgomery Singles · Montgomery Singles 3.0 Men

7 players · average NTRP 3.00 / MARYLAND

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Schedule10 played
2025-09-26vs Randle - RUTHless Racquets 3.0Won 30
W#1 SinglesRandy Lee vs Milad Ebrahimi6-2, 6-1
W#2 SinglesNeeraj Gupta vs Daniel Volker6-1, 6-1
W#3 SinglesJesse Brooks vs Jason Levit6-1, 6-1
2025-09-12vs Randle - RUTHless Racquets 3.0Lost 01
L#1 SinglesNobuyasu Sugimoto vs Ray Krickel3-6, 7-5, 0-1
2025-09-03vs Randle - RUTHless Racquets 3.0Lost 03
L#1 SinglesNeeraj Gupta vs Juan Luis Garcia6-3, 2-6, 1-0
L#2 SinglesKeiichi Nakatani vs Andrew Lutas4-6, 3-6
L#3 SinglesJesse Brooks vs Matthew Mueller3-6, 3-5
2025-08-20vs Randle - RUTHless Racquets 3.0Won 21
W#1 SinglesRandy Lee vs Andrew Lutas6-2, 6-3
W#2 SinglesKeiichi Nakatani vs Juan Luis Garcia0-6, 7-6, 1-0
L#3 SinglesSalvatore Scanio vs Alex Embry5-7, 2-4
2025-08-16vs Randle - RUTHless Racquets 3.0Lost 02
L#1 SinglesSalvatore Scanio vs Juan Luis Garcia3-6, 4-6
L#2 SinglesJesse Brooks vs Ray Krickel2-6, 6-3, 1-0
2025-08-11vs Randle - RUTHless Racquets 3.0Won 30
W#1 SinglesRandy Lee vs Daniel Volker6-3, 6-1
W#2 SinglesJesse Brooks vs Shashank Bhatia6-2, 5-5
W#3 SinglesKeiichi Nakatani vs Jason Levit6-1, 6-4
2025-08-02vs Randle - RUTHless Racquets 3.0Won 10
W#1 SinglesNobuyasu Sugimoto vs Alex Embry6-4, 7-6
2025-07-30vs Randle - RUTHless Racquets 3.0Lost 01
L#1 SinglesNobuyasu Sugimoto vs Ray Krickel3-6, 6-3, 0-1
2025-07-23vs Randle - RUTHless Racquets 3.0Won 10
W#1 SinglesNeeraj Gupta vs Juan Luis Garcia6-4, 6-2
2025-07-15vs Randle - RUTHless Racquets 3.0Lost 01
L#1 SinglesNobuyasu Sugimoto vs Andrew Lutas4-6, 5-7
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 Montgomery Singles 3.0 Men 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 2.99 estimated across 6 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
Randy Lee
usually #1 Singles 100% · published
3.09
Neeraj Gupta
usually #1 Singles 67%, also #2 Singles 33% · published
2.94
Jesse Brooks
usually #3 Singles 50%, also #2 Singles 50% · published
2.91
Bill Keating
published 3
2.86
Nobuyasu Sugimoto
usually #1 Singles 100% · published 3
2.79
Salvatore Scanio
usually #3 Singles 50%, also #1 Singles 50% · published
Keiichi Nakatani
usually #2 Singles 67%, also #3 Singles 33% · published
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.

Randy Lee
15W–19L career · 3 lines in 2025
1%91%8%
3.32
Neeraj Gupta
18W–21L career · 3 lines in 2025
24%76%<1%
3.09
Jesse Brooks
8W–10L career · 4 lines in 2025
<1%67%33%
2.94
3
Bill Keating
26W–45L career · no lines in 2025
<1%75%25%
2.91
3
Nobuyasu Sugimoto
47W–74L career · 4 lines in 2025
<1%85%15%
2.86
Salvatore Scanio
14W–24L career · 2 lines in 2025
1%94%5%
2.79
Keiichi Nakatani
2W–2L career · 3 lines 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.