Teams

Sets Appeal

2022 Montgomery Combo Mixed Fall · Montgomery Combo Mixed 8.5

18 players · average NTRP 4.39 / MARYLAND

View scouting list →
Schedule10 played
2022-12-01vs MoCo Cady 8.5 MixedLost 12
W#1 DoublesWilliam Wong / Christen Harsha vs Kenneth Fowler / Danielle Desfosses6-3, 4-6, 1-0
L#2 DoublesErika Trost / Oliver Lee vs Ryan Cinoman / Dian Zhang7-6, 4-6
L#3 DoublesLeila Lam / Richard Laukitis vs Caitlin Lee / Daniel Park3-6, 2-6
2022-11-21vs MillerSplit 11
L#1 DoublesEle Pratt / Chris Downs vs Harris Rosenblatt / Michele Bloom4-6, 2-6
W#2 DoublesOliver Lee / Erika Trost vs Heather Sine / Ricardo Green6-2, 6-1
2022-11-16vs Your Pace or MineSplit 11
L#1 DoublesPhillip Ramil / Christen Harsha vs Duane Wright / Jingping Yang3-6, 2-6
W#3 DoublesLeila Lam / Geoffrey Montgomery vs Chanpen Teeranon / Byron Levy6-4, 6-1
2022-11-12vs MoCo Cady 8.5 MixedSplit 11
L#1 DoublesLeila Lam / Richard Laukitis vs Danielle Desfosses / Sean Der3-6, 3-6
W#2 DoublesChristen Harsha / Matt Morgan vs Jennifer Nyman / Dwayne Herndon6-1, 6-3
2022-10-29vs Your Pace or MineLost 12
W#1 DoublesWilliam Wong / Christen Harsha vs Sarah Monsheimer / John Lee6-3, 6-3
L#2 DoublesSimone Feldman / Geoffrey Montgomery vs Laura McInerney / Gregory Chambers4-6, 6-7
L#3 DoublesEle Pratt / Richard Laukitis vs Jennie Kim / Hayan Marouf3-6, 2-6
2022-10-21vs MoCo Cady 8.5 MixedLost 02
L#1 DoublesSimone Feldman / Richard Laukitis vs Jennifer Nyman / Kenneth Fowler4-6, 4-6
L#2 DoublesErika Trost / Oliver Lee vs Caitlin Lee / Daniel Park6-7, 1-6
2022-10-16vs Your Pace or MineWon 10
W#1 DoublesChristen Harsha / Phillip Ramil vs Gregory Chambers / Laura McInerney7-5, 6-3
2022-10-11vs MillerWon 10
W#2 DoublesChristen Harsha / Oliver Lee vs Margie Davis / Ricardo Green6-3, 6-0
2022-10-03vs MoCo Cady 8.5 MixedWon 20
W#1 DoublesChristen Harsha / Matt Morgan vs Daniel Park / Caitlin Lee6-4, 6-7
W#2 DoublesOliver Lee / Erika Trost vs Jenni Bae / Ryan Cinoman6-4, 6-4
2022-09-29vs MillerWon 20
W#1 DoublesChristen Harsha / Matt Morgan vs Cecilia Jones / Aravind Krishna7-6, 6-4
W#3 DoublesSimone Feldman / Phillip Ramil vs Dao Phan-Vissering / Roberto Ramos6-3, 6-4
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 Montgomery Combo Mixed 8.5 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 4.06 estimated across 12 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.

4.58
Erika Trost
usually #2 Doubles 100% · published 5
4.58
Christen Harsha
usually #1 Doubles 75%, also #2 Doubles 25% · published 5
4.40
Oliver Lee
published
4.26
Simone Feldman
published
Bavi Sadayappan
published 4.5
4.22
Leila Lam
published
4.19
Richard Laukitis
usually #1 Doubles 50%, also #3 Doubles 50% · published 4.5
4.11
Chris Downs
published 4.5
3.84
Geoffrey Montgomery
usually #2 Doubles 50%, also #3 Doubles 50% · published 4
3.78
Phillip Ramil
usually #1 Doubles 67%, also #3 Doubles 33% · published 4
3.73
Ele Pratt
usually #3 Doubles 50%, also #1 Doubles 50% · published 4
3.60
Carolina Posada
published 4
3.45
William Wong
published
Kara Stevenson
published
Kenny Callender
published
Matt Morgan
published
Sumeet Chawla
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.

Phillip Ramil + Christen Harsha7554% games+1.8% vs expected
Geoffrey Montgomery + Christen Harsha2343% gamesnot enough data
Geoffrey Montgomery + Simone Feldman044 matchesnot enough data
Geoffrey Montgomery + Erika Trost123 matchesnot enough data
Simone Feldman + Phillip Ramil213 matchesnot enough data
Ele Pratt + William Wong033 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.

5
Erika Trost
383W–194L career · 4 lines in 2022
27%73%<1%
4.58
5
Christen Harsha
482W–135L career · 8 lines in 2022
28%72%<1%
4.58
Oliver Lee
31W–16L career · no lines in 2022
<1%77%23%
4.40
Simone Feldman
79W–66L career · no lines in 2022
2%95%3%
4.26
4.5
Bavi Sadayappan
2W–5L career · no lines in 2022
not enough data
Leila Lam
21W–5L career · no lines in 2022
5%94%1%
4.22
4.5
Richard Laukitis
167W–99L career · 4 lines in 2022
7%92%1%
4.19
4.5
Chris Downs
4W–8L career · no lines in 2022
19%81%<1%
4.11
4
Geoffrey Montgomery
320W–242L career · 2 lines in 2022
<1%88%11%
3.84
4
Phillip Ramil
142W–56L career · 3 lines in 2022
2%94%5%
3.78
4
Ele Pratt
102W–79L career · type M · 2 lines in 2022
4%94%2%
3.73
4
Carolina Posada
18W–10L career · no lines in 2022
22%78%<1%
3.60
William Wong
9W–5L career · no lines in 2022
65%35%<1%
3.45
Kara Stevenson
3W–4L career · no lines in 2022
not enough data
Kenny Callender
3W–3L career · no lines in 2022
not enough data
Matt Morgan
5W–1L career · no lines in 2022
not enough data
Sumeet Chawla
23W–12L career · no lines in 2022
not enough data
Tim Huber
6W–7L 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.