Teams

Kau Belles 6.5

2022 Montgomery Combo Fall · Montgomery Combo Fall 6.5 Women

16 players · average NTRP 3.58 / MARYLAND

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 Montgomery Combo Fall 6.5 Women 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 3.34 estimated across 13 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
Chanpen Teeranon
usually #1 Doubles 57%, also #2 Doubles 29% · published 4
3.69
Kelsey Forbes
published 4
3.65
Zoie Acadia
usually #1 Doubles 100% · published 4
3.65
Vera Ryss
usually #3 Doubles 50%, also #1 Doubles 33% · published 4
3.53
Nicole Ifill
usually #2 Doubles 67%, also #3 Doubles 17% · published 3.5
3.34
Ruxandra Badiu
usually #2 Doubles 44%, also #3 Doubles 33% · published 3.5
3.33
Yulan Jin
usually #3 Doubles 50%, also #2 Doubles 25% · published 3.5
3.27
Regina Farrington
usually #1 Doubles 43%, also #3 Doubles 29% · published 3.5
Brenda Kaechele
published 3.5
3.17
Nikki Eyman
usually #1 Doubles 50%, also #2 Doubles 50% · published 3.5
3.15
Shirley Hsieh-Lau
usually #2 Doubles 67%, also #3 Doubles 33% · published 3.5
3.11
Prashila Dullabh
usually #3 Doubles 50%, also #2 Doubles 25% · published 3
2.96
Maria Angelica Camp
usually #2 Doubles 75%, also #3 Doubles 25% · published 3
2.83
Jonaki Bose
published
Kamlesh Dhallan
published
Karen Jones
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.

Ruxandra Badiu + Yulan Jin10172% games+11.0% vs expected
Regina Farrington + Vera Ryss10456% gamesnot enough data
Nicole Ifill + Prashila Dullabh10360% gamesnot enough data
Chanpen Teeranon + Yulan Jin8065% gamesnot enough data
Regina Farrington + Zoie Acadia2546% gamesnot enough data
Regina Farrington + Chanpen Teeranon4159% gamesnot enough data
Regina Farrington + Shirley Hsieh-Lau224 matchesnot enough data
Ruxandra Badiu + Nikki Eyman404 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
Chanpen Teeranon
209W–208L career · 7 lines in 2022
3%94%2%
3.74
4
Kelsey Forbes
141W–114L career · no lines in 2022
7%92%1%
3.69
4
Zoie Acadia
359W–171L career · 4 lines in 2022
12%88%<1%
3.65
4
Vera Ryss
103W–42L career · 6 lines in 2022
13%87%<1%
3.65
3.5
Nicole Ifill
253W–215L career · 6 lines in 2022
<1%41%59%
3.53
3.5
Ruxandra Badiu
478W–217L career · 9 lines in 2022
<1%88%11%
3.34
3.5
Yulan Jin
237W–178L career · 4 lines in 2022
1%90%9%
3.33
3.5
Regina Farrington
179W–186L career · 7 lines in 2022
2%94%4%
3.27
3.5
Brenda Kaechele
1W–1L career · no lines in 2022
not enough data
3.5
Nikki Eyman
233W–188L career · 4 lines in 2022
10%89%1%
3.17
3.5
Shirley Hsieh-Lau
81W–131L career · 6 lines in 2022
12%87%<1%
3.15
3
Prashila Dullabh
91W–60L career · 4 lines in 2022
<1%20%80%
3.11
3
Maria Angelica Camp
144W–113L career · 4 lines in 2022
<1%61%39%
2.96
Jonaki Bose
12W–3L career · no lines in 2022
1%90%9%
2.83
Kamlesh Dhallan
9W–4L career · no lines in 2022
not enough data
Karen Jones
1W–2L 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.