Teams

Evolution

2022 Montgomery Combo Fall · Montgomery Combo Fall 7.5 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 7.5 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 3.33 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.

3.94
Mekkla Thompson
usually #1 Doubles 80%, also #2 Doubles 20% · published 4
3.77
Elizabeth Hunter
published 4
3.68
Megan Kessler
usually #1 Doubles 100% · published 4
3.65
Vera Ryss
usually #3 Doubles 50%, also #1 Doubles 33% · published 4
3.62
Elizabeth Pugh
published 3.5
3.53
Nicole Ifill
usually #2 Doubles 67%, also #3 Doubles 17% · published 3.5
3.31
Carol Gover
usually #2 Doubles 39%, also #3 Doubles 39% · published 3.5
3.27
Regina Farrington
usually #1 Doubles 43%, also #3 Doubles 29% · published 3.5
3.26
Katya Vert-Wong
published
3.24
Yvette Fontenot
published
3.23
Betsy Mencher
published 3.5
3.22
Jackie Livesay
published 3.5
3.15
Shirley Hsieh-Lau
usually #2 Doubles 67%, also #3 Doubles 33% · published 3.5
2.89
Telesia Hundley
published
2.78
Carey Greenauer
published 3
2.66
Dora Macia
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.

Regina Farrington + Vera Ryss10456% gamesnot enough data
Carol Gover + Nicole Ifill2347% gamesnot enough data
Carol Gover + Shirley Hsieh-Lau2343% gamesnot enough data
Regina Farrington + Shirley Hsieh-Lau224 matchesnot enough data
Shirley Hsieh-Lau + Vera Ryss314 matchesnot enough data
Nicole Ifill + Shirley Hsieh-Lau123 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
Mekkla Thompson
161W–109L career · 5 lines in 2022
<1%67%32%
3.94
4
Elizabeth Hunter
3W–4L career · no lines in 2022
2%94%4%
3.77
4
Megan Kessler
76W–38L career · 7 lines in 2022
8%91%1%
3.68
4
Vera Ryss
103W–42L career · 6 lines in 2022
13%87%<1%
3.65
3.5
Elizabeth Pugh
1W–7L career · no lines in 2022
<1%18%82%
3.62
3.5
Nicole Ifill
253W–215L career · 6 lines in 2022
<1%41%59%
3.53
3.5
Carol Gover
120W–213L career · 13 lines in 2022
1%92%7%
3.31
3.5
Regina Farrington
179W–186L career · 7 lines in 2022
2%94%4%
3.27
Katya Vert-Wong
6W–16L career · no lines in 2022
2%94%3%
3.26
Yvette Fontenot
17W–27L career · no lines in 2022
3%95%2%
3.24
3.5
Betsy Mencher
2W–5L career · no lines in 2022
4%94%2%
3.23
3.5
Jackie Livesay
13W–17L career · no lines in 2022
5%94%1%
3.22
3.5
Shirley Hsieh-Lau
81W–131L career · 6 lines in 2022
12%87%<1%
3.15
Telesia Hundley
1W–8L career · no lines in 2022
<1%81%19%
2.89
3
Carey Greenauer
4W–5L career · no lines in 2022
2%94%4%
2.78
3
Dora Macia
3W–2L career · no lines in 2022
11%89%<1%
2.66

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.