Teams

Apex:SmashQueens:Morong

2022 ME Fall Tri-Level · 3.5 Women

4 players · average NTRP 3.00 / MAINE

View scouting list →
Schedule9 played
2022-12-03vs Apex:TBD:GreenLost 01
L#1 DoublesKimberly Kelly-Brewster / Andrea Otis-Higgins vs Jennifer Bowring / Kristie Green3-6, 6-4, 0-1
2022-12-03vs WOOD:BlurredLines:FendlerLost 01
L#1 DoublesDawn Morong / Kimberly Nappi vs Mary Gentile / Regina Yoon2-6, 1-6
2022-11-13vs WOOD:BlurredLines:FendlerLost 01
L#1 DoublesDawn Morong / Andrea Otis-Higgins vs Joanna Pond / Regina Yoon3-6, 0-6
2022-11-13vs MRC:TheSmash:ArauLost 01
L#1 DoublesDawn Morong / Kimberly Nappi vs Melissa Burroughs / Lana Arau0-6, 3-6
2022-10-29vs MRC:TheSmash:ArauLost 01
L#1 DoublesKimberly Nappi / Andrea Otis-Higgins vs Lana Arau / Kerry McCormick0-6, 0-6
2022-10-29vs Apex:TBD:GreenLost 01
L#1 DoublesKimberly Kelly-Brewster / Dawn Morong vs Jennifer Bowring / Barbara Cassidy2-6, 6-7
2022-10-16vs MRC:TheSmash:ArauLost 01
L#1 DoublesDawn Morong / Andrea Otis-Higgins vs Lana Arau / Melissa Burroughs0-6, 1-6
2022-10-16vs WOOD:BlurredLines:FendlerLost 01
L#1 DoublesDawn Morong / Andrea Otis-Higgins vs Patricia Lefevre / Regina Yoon4-6, 1-6
2022-09-18vs Apex:TBD:GreenWon 10
W#1 DoublesKimberly Nappi / Kimberly Kelly-Brewster vs Kristie Green / Jennifer Bowring6-3, 6-7, 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 standings8 teams · 3.5 Women
TeamWLInd. WInd. LSets lostGames lost
1Apex:MainelyAces:Pickering9090154
2MRC:TheSmash:Arau7171340
3WOOD:BlurredLines:Fendler6262561
4Apex:DoubleTrouble:Brown5454984
5ACOPI:CapitalPlayers:Moss36361278
6Apex:TBD:Green25251175
7Apex:NetAssets:Doyle181817107
8Apex:SmashQueens:Morong181817106

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 3.04 estimated across 3 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.

3.32
Kimberly Kelly-Brewster
usually #1 Doubles 100% · published
2.92
Andrea Otis-Higgins
usually #1 Doubles 100% · published 3
2.88
Dawn Morong
usually #1 Doubles 100% · published 3
Kimberly Nappi
usually #1 Doubles 100% · 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.

Dawn Morong + Kimberly Kelly-Brewster2344% games+7.4% vs expected
Dawn Morong + Kimberly Nappi1437% games+2.8% vs expected
Dawn Morong + Andrea Otis-Higgins134 matchesnot enough data
Kimberly Nappi + Andrea Otis-Higgins123 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.

Kimberly Kelly-Brewster
91W–101L career · 3 lines in 2022
1%91%8%
3.32
3
Andrea Otis-Higgins
141W–141L career · 5 lines in 2022
<1%72%28%
2.92
3
Dawn Morong
51W–79L career · 6 lines in 2022
<1%82%18%
2.88
Kimberly Nappi
37W–35L career · 4 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.