Teams

SD 3.5 La Jolla TC/ Bruno

2026 SoCal Fall Doubles- SD WD · SD - Women - 3.5

15 players · average NTRP 3.41 / SAN DIEGO

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 standings for SD - Women - 3.5 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 3.28 estimated across 15 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.

3.57
Lori Lovering
published 3.5
3.48
Sarah Bruno
published
3.47
Darcy Karpman
published 3.5
3.45
Jessica Shehab
published 3.5
3.40
Jennifer Bucky
published 3.5
3.35
Bonnie Reilly
published 3.5
3.31
Alison Burkett
published 3.5
3.31
Sherrie Black
published
3.30
Tina Mertel
published 3.5
3.30
Kiska Higgs
published
3.26
Cheryl Shah
published 3.5
3.21
Janet Costa
published
3.20
Alexis MacMillan
published 3.5
3.05
Paige Kratz
published 3
2.61
Irene Coppedge
published 3
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.

Jennifer Bucky + Jessica Shehab4161% games+12.8% vs expected
Darcy Karpman + Sarah Bruno4165% games+9.8% vs expected
Sarah Bruno + Jessica Shehab6457% games+6.1% vs expected
Darcy Karpman + Jennifer Bucky171551% games−0.5% vs expected
Darcy Karpman + Cheryl Shah8650% gamesnot enough data
Jennifer Bucky + Lori Lovering4253% gamesnot enough data
Tina Mertel + Sarah Bruno404 matchesnot enough data
Paige Kratz + Irene Coppedge213 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.

3.5
Lori Lovering
47W–14L career · no lines in 2026
<1%31%69%
3.57
Sarah Bruno
21W–18L career · no lines in 2026
<1%57%43%
3.48
3.5
Darcy Karpman
94W–53L career · no lines in 2026
<1%58%42%
3.47
3.5
Jessica Shehab
82W–42L career · no lines in 2026
<1%64%36%
3.45
3.5
Jennifer Bucky
67W–47L career · no lines in 2026
<1%76%23%
3.40
3.5
Bonnie Reilly
33W–19L career · no lines in 2026
1%85%14%
3.35
3.5
Alison Burkett
5W–7L career · no lines in 2026
1%90%9%
3.31
Sherrie Black
5W–3L career · no lines in 2026
1%90%8%
3.31
3.5
Tina Mertel
36W–29L career · no lines in 2026
2%91%8%
3.30
Kiska Higgs
6W–12L career · no lines in 2026
2%91%8%
3.30
3.5
Cheryl Shah
41W–42L career · no lines in 2026
3%92%4%
3.26
Janet Costa
4W–3L career · no lines in 2026
7%91%2%
3.21
3.5
Alexis MacMillan
5W–5L career · no lines in 2026
8%91%2%
3.20
3
Paige Kratz
102W–65L career · no lines in 2026
<1%37%63%
3.05
3
Irene Coppedge
25W–61L career · no lines in 2026
21%78%<1%
2.61

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.