Teams

Cha Cha Crawl

2021 Baltimore Mixed 40 & Over · Baltimore Mixed 40 & Over 8.0

15 players · average NTRP 4.22 / MARYLAND

View scouting list →
Schedule4 played
2021-08-07Won 20
W#1 DoublesJared Fly / Audrey Liu vs Eric Bass / Gail Zylberberg1-6, 7-5, 1-0
W#3 DoublesDONALD CRAWLEY / Carol Besse vs N/A6-0, 6-0
2021-08-01vs Mixed SuccessWon 10
W#1 DoublesJared Fly / Heidi Sung vs James Smoot / Beyza Akcam7-6, 7-6
2021-07-27vs Mixed SuccessLost 01
L#1 DoublesDONALD CRAWLEY / Susie Chung vs Michael Jarman / Terri Mrozinski6-4, 1-6, 0-1
2021-07-19Won 10
W#3 DoublesDONALD CRAWLEY / Carol Besse vs Samuel Miller / Marcella Miller7-5, 6-1
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 Baltimore Mixed 40 & Over 8.0 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 3.87 estimated across 14 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.

4.40
Matthew Geppi
published 4.5
4.16
Jared Fly
usually #1 Doubles 100% · published 4.5
4.06
Carol Besse
usually #3 Doubles 100% · published 4.5
4.04
Henry Cha
published 4.5
4.04
Jean Lim
published
3.90
Susan Rhee
published
3.85
DONALD CRAWLEY
usually #1 Doubles 40%, also #3 Doubles 40% · published 4
3.85
David Trang
published 4.5
3.83
Virginia Fung
published
3.79
3.78
Susie Chung
published
3.63
Audrey Liu
published 4
3.50
Anirudh Sridharan
published 3.5
3.42
Rebecca Stewart
published
Tim Huber
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.

Carol Besse + DONALD CRAWLEY301162% games+17.7% vs expected
Christopher Morphew + Virginia Fung3357% games+10.6% vs expected
Henry Cha + Jean Lim4940% games−4.6% vs expected
Henry Cha + Rebecca Stewart224 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.

4.5
Matthew Geppi
225W–81L career · no lines in 2021
<1%77%23%
4.40
4.5
Jared Fly
206W–121L career · 2 lines in 2021
12%88%<1%
4.16
4.5
Carol Besse
288W–186L career · 2 lines in 2021
32%68%<1%
4.06
4.5
Henry Cha
25W–50L career · no lines in 2021
39%61%<1%
4.04
Jean Lim
18W–38L career · no lines in 2021
39%61%<1%
4.04
Susan Rhee
32W–20L career · no lines in 2021
<1%78%22%
3.90
4
DONALD CRAWLEY
473W–252L career · 5 lines in 2021
<1%87%12%
3.85
4.5
David Trang
0W–12L career · type A · no lines in 2021
88%12%<1%
3.85
Virginia Fung
60W–44L career · no lines in 2021
<1%89%10%
3.83
4
Christopher Morphew
5W–3L career · no lines in 2021
1%93%5%
3.79
Susie Chung
8W–7L career · no lines in 2021
2%94%4%
3.78
4
Audrey Liu
10W–23L career · no lines in 2021
16%84%<1%
3.63
3.5
Anirudh Sridharan
15W–2L career · no lines in 2021
<1%49%51%
3.50
Rebecca Stewart
36W–20L career · no lines in 2021
<1%74%26%
3.42
Tim Huber
6W–7L career · no lines in 2021
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.