Teams

LA - Sets and the City

2022 SoCal Tri-Level - LA · LA - Women 5.0

14 players · average NTRP 4.42 / SO.CALIFORNIA

View scouting list →
Schedule8 played
L#3 DoublesAlexandra Pichugina / Monica Mitchell vs Carol Choy / Loretta Peng2-6, 1-6
L#3 DoublesLauren Woodward / Monica Mitchell vs Jasmine Dai / Jane Wang3-6, 0-6
L#3 DoublesAlexandra Pichugina / Monica Mitchell vs Jasmine Dai / Jane Wang5-7, 2-6
L#2 DoublesMichelle Zhong / Brynna Pietz vs Mandi Collier / Tricia Guinto6-4, 5-7, 0-1
L#2 DoublesBrynna Pietz / Anna Lyke vs Aki Eguchi / Leticia Alcala1-6, 1-6
L#3 DoublesSharon Li / Monica Mitchell vs Stacy Rubeli / Jenna Tempkin3-6, 1-6
L#3 DoublesAlexandra Pichugina / Lauren Woodward vs Carol Choy / Loretta Peng2-6, 2-6
L#2 DoublesBrynna Pietz / Anna Lyke vs Kristina Chen / Stephanie Ellis3-6, 0-6
W#3 DoublesAlexandra Pichugina / Monica Mitchell vs Alona Kavinoky / Alisha Shohet6-0, 6-4
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 LA - Women 5.0 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 4.23 estimated across 11 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.

4.82
Andrea Rivera
published 5
4.74
4.66
Jennifer Beindorf
published
4.53
Lauren DiFazio
published
4.46
Blair Brzeski
published 4.5
4.22
Brynna Pietz
usually #2 Doubles 60%, also #1 Doubles 40% · published 4.5
4.18
Anusha Arcalgud
published 4.5
3.89
Lauren Woodward
usually #2 Doubles 50%, also #3 Doubles 50% · published 4
3.77
Monica Mitchell
usually #3 Doubles 100% · published
3.69
3.59
Sharon Li
published
Kathy Lundberg
published
Rachel Harbert
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.

Brynna Pietz + Lauren DiFazio10071% gamesnot 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.

Madeleine Gandawidjaja
5W–0L career · no lines in 2022
1%91%8%
4.82
5
Andrea Rivera
1W–1L career · no lines in 2022
not enough data
Jessica Widmark Hillman
8W–3L career · no lines in 2022
3%95%2%
4.74
Jennifer Beindorf
15W–7L career · no lines in 2022
12%88%<1%
4.66
Lauren DiFazio
122W–58L career · no lines in 2022
42%58%<1%
4.53
4.5
Blair Brzeski
3W–2L career · no lines in 2022
<1%61%39%
4.46
4.5
Brynna Pietz
89W–60L career · 5 lines in 2022
5%94%2%
4.22
4.5
Anusha Arcalgud
9W–15L career · no lines in 2022
8%91%1%
4.18
4
Lauren Woodward
139W–67L career · 4 lines in 2022
<1%80%19%
3.89
Monica Mitchell
77W–72L career · 5 lines in 2022
2%94%4%
3.77
4
Alexandra Pichugina
5W–8L career · no lines in 2022
7%92%1%
3.69
Sharon Li
13W–10L career · no lines in 2022
24%75%<1%
3.59
Kathy Lundberg
1W–1L career · no lines in 2022
not enough data
Rachel Harbert
4W–5L 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.