Teams

SFV - Tri Purple Warriors

2022 Mixed Tri-Level 18+ SFV · SFV Tri-Level Mixed 3.0-4.0

12 players · average NTRP 3.25 / SO.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 →
Schedule4 played
2022-11-06vs SFV - Pure DriveLost 01
L#3 DoublesRoger Hance / Nichole Burston vs Pramit Singh / Diana Amado0-6, 1-6
2022-10-08vs SFV - Paseo RanchersWon 10
W#2 DoublesShyam Markus / Michele Venegas vs Melanie Delgado / Gil Garteiz6-3, 6-0
2022-10-02vs SFV LLW - Nice Aces - Lee TsaiWon 10
W#3 DoublesNichole Burston / Roger Hance vs Melissa Jansson / Manny Kreitenberg6-1, 6-7, 1-0
2022-09-17vs SFV - Triple TroubleSplit 11
W#2 DoublesMichele Venegas / Shyam Markus vs Sara Heum / Nazar Makadsi6-3, 7-5
L#3 DoublesRobert Wasserman / Nichole Burston vs Holly Culhane / Ola Heum0-6, 3-6
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 SFV Tri-Level Mixed 3.0-4.0 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 2.92 estimated across 10 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.

3.74
Shyam Markus
published 4
3.20
Michele Venegas
usually #2 Doubles 100% · published 3.5
3.07
Nichole Burston
usually #3 Doubles 100% · published 3
3.00
Susan Friedman
published
2.90
Rahul Chhablani
published
2.75
Angie Wu
published 3
2.72
Cobe Crosby
published 3
2.67
Chris Burston
published 3
2.60
Karen Crosby
published
2.51
Suzanne Wainfeld
published
Nichole Carlin
published
Raman Sain
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.

Karen Crosby + Cobe Crosby134 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.

4
Shyam Markus
46W–31L career · no lines in 2022
3%95%2%
3.74
3.5
Michele Venegas
97W–95L career · 2 lines in 2022
6%93%1%
3.20
3
Nichole Burston
45W–38L career · 3 lines in 2022
<1%30%70%
3.07
Susan Friedman
9W–18L career · no lines in 2022
50%50%<1%
3.00
Rahul Chhablani
19W–18L career · no lines in 2022
<1%77%23%
2.90
3
Angie Wu
7W–26L career · no lines in 2022
3%95%3%
2.75
3
Cobe Crosby
1W–6L career · type S · no lines in 2022
4%94%2%
2.72
3
Chris Burston
4W–5L career · no lines in 2022
9%90%1%
2.67
Karen Crosby
2W–9L career · no lines in 2022
22%78%<1%
2.60
Suzanne Wainfeld
1W–11L career · no lines in 2022
47%53%<1%
2.51
Nichole Carlin
3W–10L career · no lines in 2022
not enough data
Raman Sain
2W–0L 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.