Teams

FF:Mao’sters:Mao

2023 Fall Tri-Level · 4.0 Women

5 players · average NTRP 4.00 / MAINE

View scouting list →
Schedule8 played
2023-12-07vs WOOD:BubbleTrouble:PondWon 10
W#1 DoublesDeanna Mao / Lisa Ford vs Heidi Allen / Susie Coughlin7-5, 6-2
2023-12-05vs Apex:DoyleWon 10
W#1 DoublesPolly Colvin MacKenzie / Lisa Ford vs Heidi Rentz / Diana Doyle6-1, 6-1
2023-11-17vs WOOD:BubbleTrouble:PondLost 01
L#1 DoublesDeanna Mao / Alice Wagg vs Susie Coughlin / Joanna Pond3-6, 4-6
2023-11-12vs Apex:McArdleLost 01
L#1 DoublesPolly Colvin MacKenzie / Deanna Mao vs Meredith McArdle / Anne Vaillancourt6-2, 5-7, 0-1
2023-10-15vs Apex:ColpittsLost 01
L#1 DoublesDeanna Mao / Lorraine Fagela vs JOANNE SULLIVAN / Odette Thurston4-6, 1-6
2023-10-01vs Apex:DoyleWon 10
W#1 DoublesAlice Wagg / Polly Colvin MacKenzie vs Heidi Rentz / Pauline Smith6-7, 6-0, 1-0
2023-09-30vs Apex:ColpittsWon 10
W#1 DoublesPolly Colvin MacKenzie / Deanna Mao vs JOANNE SULLIVAN / Odette Thurston6-3, 1-6, 1-0
2023-09-17vs Apex:McArdleWon 10
W#1 DoublesPolly Colvin MacKenzie / Deanna Mao vs Anne Vaillancourt / Meredith McArdle6-0, 6-2
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 standings9 teams · 4.0 Women
TeamWLInd. WInd. LSets lostGames lost
1Apex:Konieczko6363772
2ACOPI:TryHarder:Holm6363776
3Apex:Colpitts5353754
4WOOD:BubbleTrouble:Pond5353766
5FF:Mao’sters:Mao5353861
6Apex:McArdle5353970
7Apex:Marroquin54541073
8Apex:DoubleTrouble:Kapothanasis18181696
9Apex:Doyle08081697

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 3.70 estimated across 2 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.

3.86
Deanna Mao
usually #1 Doubles 100% · published 4
Alice Wagg
usually #1 Doubles 100% · published 4
3.54
Polly Colvin MacKenzie
usually #1 Doubles 100% · published
Lisa Ford
usually #1 Doubles 100% · published
Lorraine Fagela
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.

Deanna Mao + Polly Colvin MacKenzie9360% games+1.0% vs expected
Deanna Mao + Lisa Ford4159% games+0.9% vs expected
Lorraine Fagela + Polly Colvin MacKenzie224 matchesnot enough data
Lorraine Fagela + Alice Wagg213 matchesnot enough data
Alice Wagg + Lisa Ford213 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
Deanna Mao
110W–66L career · 6 lines in 2023
<1%86%14%
3.86
4
Alice Wagg
7W–5L career · 2 lines in 2023
not enough data
Polly Colvin MacKenzie
93W–72L career · 5 lines in 2023
37%63%<1%
3.54
Lisa Ford
18W–6L career · 2 lines in 2023
not enough data
Lorraine Fagela
62W–48L career · 1 line in 2023
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.