Teams

BC-Lee/Camara

2022 Mixed 40 & Over · 7.0

18 players · average NTRP 3.50 / NORTHWEST WASHINGTON

View scouting list →
Schedule7 played
2022-07-31vs WSC-Love All-WhitneyWon 21
W#1 DoublesJennifer Gardner / Alfred Yu vs Siobhan Whitney / Ajoy Krishnamoorthy6-4, 6-2
L#2 DoublesShawna Dash / Alex Camara vs Kenn Wildes / Elena Ivanova2-6, 5-7
W#3 DoublesLeilani de Jong / Shawn Akavan vs Kristen Mosebar / Gaurav Kanade2-6, 6-2, 1-0
2022-07-23vs CP-Cloud Warriors-ViriththamullaWon 21
W#1 DoublesSusan Hurt / Kenneth Cho vs Wendy Reynolds / Scott Reynolds7-6, 2-6, 1-0
W#2 DoublesJoanne Sakoda / Steven Rogers vs Gamage Viriththamulla / Chrissy Bauer7-5, 6-0
L#3 DoublesJason Holm / Marilyn Johnson vs Lance Wilken / Sherri Wolson6-2, 1-6, 0-1
2022-07-17vs PSC-Song/Zhu 7.0Lost 03
L#1 DoublesNancy Fletcher / Matthew Scher vs Lu Ruan / Heng Liu5-7, 1-6
L#2 DoublesMarilyn Johnson / Alex Camara vs Jasmine Kreizenbeck / Kevin Ying0-6, 3-6
L#3 DoublesHelen Lee / Chris Nelson vs Eva Chen / Kevin Lee6-4, 3-6, 1-0
2022-07-16vs TCSP-BursiekLost 12
L#1 DoublesAlex Camara / Marilyn Johnson vs Meghan Maguire / Arun Sundaram2-6, 4-6
W#2 DoublesMatthew Scher / Nancy Fletcher vs Christa Glenn / Brook Goddard6-2, 6-2
L#3 DoublesShawna Dash / Erwin Chung vs Jamie Lampitt / Joseph Lampitt6-4, 5-7, 0-1
2022-07-09vs PL-CarterWon 21
W#1 DoublesSteven Rogers / Joanne Sakoda vs Tetyana Sych / Oleg Sych7-5, 6-4
W#2 DoublesShawna Dash / Erwin Chung vs David Linehan / Barbara Wood6-1, 6-3
L#3 DoublesLeilani de Jong / Jason Holm vs Scott Fletcher / Renee Fletcher6-3, 0-6, 0-1
2022-07-03vs FC-Ball Busters-MarLost 12
W#1 DoublesMarilyn Johnson / Alfred Yu vs Medilyn Barrett / Jeremy Cheung1-6, 6-2, 1-0
L#2 DoublesJennifer Gardner / Matthew Scher vs Anita Marrero / Randy Chin4-6, 1-6
L#3 DoublesJoanne Sakoda / Chris Nelson vs Angela Cummings / Stephane Perreault5-7, 4-6
2022-06-18vs CAC/SL-All Mixed Up-AgarwalLost 03
L#1 DoublesSteven Rogers / Joanne Sakoda vs Steven Nguyen / Sarah Lai3-6, 7-6, 0-1
L#2 DoublesSusan Hurt / Kenneth Cho vs Tri Dang / Mei Yang3-6, 3-6
L#3 DoublesHelen Lee / Matthew Scher vs Anup Agarwal / Kim Carey3-6, 6-4, 1-0
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 standings30 teams · 7.0
TeamWLInd. WInd. LSets lostGames lost
1HBSQ-Furman70201390
2PL-Samma Mish Mashers-Escalona701838130
3FC-Ball Busters-Mar7016513156
4PSC-Song/Zhu 7.06118311154
5CAC/SL-Brohams-Wanat6116512161
6WSC-Azure-Popoaei6115614147
7MI-Bertram6117415167
8TCSP-tennis crush-Wickham5215615172
9PSC-Zhang/Mu5215615153
10CAC/SL-All Mixed Up-Agarwal5214717177
11EDG-Fun-Juhn52111023184
12EDG-Netsetters-Gliner4312921187
13TCSP-Fast and the 40+ Nguyen43111021177
14CP-Doubles Trouble-Han43111022160
15FC-Scorpions-Calpe34101124194
16BELL-Mixed Up'Hamsters-Harwood3491227212
17BC-Lee/Camara3481329207
18TCSP-Bursiek3471430214
19CP-Key in Bowl-Chen2471124173
20BETC-Kean/Shutt 7.02591224193
21CP-Cloud Warriors-Viriththamulla2581331209
22EDG-Namba 7.02571431226
23RTC-Mixed Madness 40+ Hansberry2571432234
24PL-Carter2571433216
25MI-Double Shot-Holland2541735226
26TCSP-Double Trouble-Arron1661534236
27AYTC-It's Not Racquet Science-Chow0631531200
28WSC-Love All-Whitney0761532217
29AYTC-This is 40-Love-Padilla0751633231
30BTA-Tennis Jam-Cecil-Moore0721938235

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 3.23 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.

3.75
Erwin Chung
usually #3 Doubles 50%, also #2 Doubles 25% · published 4
3.73
Kenneth Cho
usually #2 Doubles 50%, also #1 Doubles 33% · published 4
3.44
Matthew Scher
usually #2 Doubles 50%, also #3 Doubles 25% · published 3.5
3.35
Shawna Dash
usually #2 Doubles 67%, also #3 Doubles 33% · published 3.5
3.29
Alfred Yu
usually #1 Doubles 60%, also #2 Doubles 20% · published 3.5
Joanne Sakoda
usually #1 Doubles 50%, also #3 Doubles 25% · published 3.5
3.23
Jennifer Gardner
usually #2 Doubles 50%, also #1 Doubles 50% · published 3.5
3.23
Nancy Fletcher
usually #2 Doubles 50%, also #1 Doubles 50% · published 3.5
3.20
Helen Lee
usually #3 Doubles 100% · published 3.5
3.20
Jill Hancock
usually #1 Doubles 100% · published 3.5
3.12
Chris Nelson
usually #3 Doubles 100% · published 3.5
3.05
Leilani de Jong
usually #3 Doubles 100% · published 3.5
3.05
Susan Hurt
usually #2 Doubles 60%, also #1 Doubles 40% · published 3.5
2.92
Alex Camara
usually #2 Doubles 67%, also #1 Doubles 33% · published 3.5
Shawn Akavan
usually #3 Doubles 100% · published 3
2.64
Jason Holm
usually #3 Doubles 100% · published 3
Marilyn Johnson
usually #1 Doubles 63%, also #3 Doubles 25% · published
Steven Rogers
usually #1 Doubles 67%, also #2 Doubles 33% · 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.

Alex Camara + Shawna Dash5451% games+3.9% vs expected
Nancy Fletcher + Matthew Scher141252% games+3.2% vs expected
Steven Rogers + Joanne Sakoda3356% gamesnot enough data
Alex Camara + Marilyn Johnson134 matchesnot enough data
Shawna Dash + Erwin Chung314 matchesnot enough data
Jill Hancock + Matthew Scher134 matchesnot enough data
Kenneth Cho + Leilani de Jong314 matchesnot enough data
Nancy Fletcher + Alfred Yu123 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
Erwin Chung
23W–23L career · 4 lines in 2022
3%95%3%
3.75
4
Kenneth Cho
84W–73L career · 6 lines in 2022
4%94%2%
3.73
3.5
Matthew Scher
99W–109L career · 4 lines in 2022
<1%68%32%
3.44
3.5
Shawna Dash
117W–85L career · 3 lines in 2022
<1%88%12%
3.35
3.5
Alfred Yu
44W–38L career · 5 lines in 2022
1%94%5%
3.29
3.5
Joanne Sakoda
64W–30L career · 4 lines in 2022
not enough data
3.5
Jennifer Gardner
140W–84L career · 2 lines in 2022
4%94%2%
3.23
3.5
Nancy Fletcher
81W–72L career · 2 lines in 2022
4%94%2%
3.23
3.5
Helen Lee
45W–71L career · 2 lines in 2022
6%93%1%
3.20
3.5
Jill Hancock
142W–94L career · 1 line in 2022
6%93%1%
3.20
3.5
Chris Nelson
50W–70L career · 2 lines in 2022
19%81%<1%
3.12
3.5
Leilani de Jong
51W–53L career · 2 lines in 2022
35%65%<1%
3.05
3.5
Susan Hurt
60W–33L career · 5 lines in 2022
36%64%<1%
3.05
3.5
Alex Camara
74W–146L career · type A · 3 lines in 2022
74%26%<1%
2.92
3
Shawn Akavan
13W–17L career · 1 line in 2022
not enough data
3
Jason Holm
27W–42L career · 2 lines in 2022
14%85%<1%
2.64
Marilyn Johnson
50W–29L career · 8 lines in 2022
not enough data
Steven Rogers
30W–57L career · 3 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.