Teams

ADeMacy

2022 Cap Mixed 40 & over · 6.0 Mixed

8 players · average NTRP 3.08 / NORTH CAROLINA

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Schedule7 played
2022-07-21vs BKaulback 40+ 6.0 MixedWon 10
W#2 DoublesKathryn Nani / Jeremy Broglin vs Laurie Holderness / Brian Pickett6-2, 6-3
2022-07-14vs LElliott 40+Lost 02
L#1 DoublesJeremy Broglin / Elizabeth Carroll vs Lori Elliott / Ronald Elliott2-6, 0-6
L#3 DoublesWilliam Santa Rosa / Lauren King vs Matthew Pare / Elena Ryzhikova3-6, 6-4, 0-1
2022-07-07vs SKingLost 02
L#2 DoublesAllison DeMacy / Eddie King vs Charles King / Ellina Max5-7, 2-6
L#3 DoublesMelissa Proctor / William Santa Rosa vs Courtney Kaprelian / Peter Kaprelian5-7, 5-7
2022-06-30vs JNance40+MixedLost 01
L#3 DoublesJessica Williams / William Santa Rosa vs Garrett Lovejoy / Tina Parker3-6, 2-6
2022-06-26vs JWOLBORSKY MIXED 6.0Lost 01
L#2 DoublesKathryn Nani / Michael Caiola vs Jennifer Wolborsky / Marc Kaufman3-6, 2-6
2022-06-16Won 10
W#1 DoublesKathryn Nani / Jeremy Broglin vs Sarah Glover / Jay Blanchfield7-6, 5-7, 1-0
2022-06-09vs PAlford 40+Lost 01
L#1 DoublesAllison DeMacy / Eddie King vs William Slocum / Melissa House3-6, 4-6
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 6.0 Mixed 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 2.94 estimated across 7 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.

3.73
Allison DeMacy
usually #1 Doubles 50%, also #2 Doubles 25% · published 4
3.46
Kristen Levine
published
3.25
Elizabeth Carroll
published 3.5
2.59
Kathryn Nani
usually #2 Doubles 67%, also #1 Doubles 33% · published 3
2.58
Jeremy Broglin
usually #1 Doubles 67%, also #2 Doubles 33% · published 3
2.47
William Santa Rosa
usually #3 Doubles 100% · published 2.5
2.46
Eddie King
published 2.5
Michael Caiola
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.

Kathryn Nani + William Santa Rosa123 matchesnot enough data
Kathryn Nani + Jeremy Broglin213 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
Allison DeMacy
272W–119L career · 4 lines in 2022
4%94%2%
3.73
Kristen Levine
29W–14L career · no lines in 2022
<1%61%39%
3.46
3.5
Elizabeth Carroll
9W–9L career · no lines in 2022
3%95%3%
3.25
3
Kathryn Nani
55W–93L career · 3 lines in 2022
25%75%<1%
2.59
3
Jeremy Broglin
63W–86L career · 3 lines in 2022
26%74%<1%
2.58
2.5
William Santa Rosa
34W–84L career · 3 lines in 2022
0%59%41%
2.47
2.5
Eddie King
12W–14L career · no lines in 2022
0%61%39%
2.46
Michael Caiola
1W–1L 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.