Teams

SGV Valley Cats-Johnson-WN/ SA,SU8

2026 SoCal Doubles 18 & Over - San Gabriel Valley · SGV - Women 4.5

17 players · average NTRP 4.32 / 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 →
Flight standings3 teams · SGV - Women 4.5
TeamWLInd. WInd. LSets lostGames lost
1SGV Valley Cats-Johnson-WN/ SA,SU8000000
2SGV Mo Better Tennis-DeRosa-WN/SU10000000
3SGV Relentless Queens-Laguna-WN/SA8000000

Ordered by team wins, then losses, then sets lost — the order USTA uses to seed a flight. Individual wins are lines, not ties.

See the full flight, with every team’s record

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 4.04 estimated across 16 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.

4.47
Jennifer Prakash
published
4.31
Jennifer Bonanni
published 4.5
4.28
Alexia Monti
published 4.5
Christina Markey
published 4.5
4.21
Rebecca Mall
published 4.5
4.20
Olga Marina
published
4.04
Joanna Morley
published
4.03
Kate Angelo
published 4
3.99
Stacy Sarner
published 4.5
3.96
Megan Colligan
published 4
3.95
Joanna Ku
published
3.94
AB Young
published 4
3.94
Casondra Ruga
published 4
3.88
Stacie Smiley
published 4.5
3.87
Kelly Nielson
published 4.5
3.86
Nancy Carell
published
3.67
Jennifer Lichtman
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.

Stacy Sarner + Megan Colligan23759% games+11.9% vs expected
Rebecca Mall + Stacie Smiley4262% games+4.6% vs expected
Jennifer Lichtman + Kate Angelo6161% games+3.6% vs expected
Kelly Nielson + Stacie Smiley562358% games+2.0% vs expected
Megan Colligan + Kate Angelo682062% games+1.5% vs expected
Nancy Carell + Jennifer Prakash3257% gamesnot enough data
Jennifer Lichtman + Megan Colligan404 matchesnot enough data
Rebecca Mall + Nancy Carell314 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.

Jennifer Prakash
10W–2L career · no lines in 2026
<1%58%42%
4.47
4.5
Jennifer Bonanni
37W–20L career · type S · no lines in 2026
1%90%9%
4.31
4.5
Alexia Monti
7W–2L career · no lines in 2026
2%92%6%
4.28
4.5
Christina Markey
1W–3L career · no lines in 2026
not enough data
4.5
Rebecca Mall
143W–45L career · no lines in 2026
7%91%2%
4.21
Olga Marina
14W–13L career · no lines in 2026
8%91%2%
4.20
Joanna Morley
11W–1L career · no lines in 2026
<1%<1%>99%
4.04
4
Kate Angelo
215W–71L career · no lines in 2026
<1%42%58%
4.03
4.5
Stacy Sarner
124W–86L career · no lines in 2026
52%48%<1%
3.99
4
Megan Colligan
174W–69L career · no lines in 2026
<1%62%38%
3.96
Joanna Ku
8W–8L career · no lines in 2026
<1%63%37%
3.95
4
AB Young
4W–3L career · no lines in 2026
<1%67%33%
3.94
4
Casondra Ruga
166W–50L career · no lines in 2026
<1%68%32%
3.94
4.5
Stacie Smiley
81W–36L career · no lines in 2026
80%20%<1%
3.88
4.5
Kelly Nielson
67W–30L career · no lines in 2026
83%17%<1%
3.87
Nancy Carell
10W–5L career · no lines in 2026
<1%1%99%
3.86
Jennifer Lichtman
24W–8L career · no lines in 2026
<1%<1%>99%
3.67

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.