Teams

LCTA40/Zielke/Doty

2022 USTA 40 & Over Adult Mixed Doubles-LCTA · 7.0

13 players · average NTRP 3.70 / SOUTH CAROLINA

No matches recorded for this roster in this league — it may be a placeholder registration, or the season may not have started.

View scouting list →
Schedule5 played
2022-06-09vs LCTA40/Balcer/MPRLost 01
L#3 DoublesShaun Roberson / Jennifer Waggoner vs Jason Haney / Cacky Rivers7-5, 4-6, 0-1
2022-06-02vs LCTA40/Houser/MPRWon 10
W#2 DoublesShaun Roberson / Karen Hughes vs John Wall / Staci Houser1-6, 6-4, 1-0
2022-05-19vs LCTA40/Howle/MPRWon 10
W#3 DoublesShaun Roberson / Beth Armstrong vs Edward Oswald / Ashley Ravenel6-3, 4-6, 1-0
2022-05-05vs LCTA40/Holder/PineForestLost 01
L#1 DoublesShaun Roberson / Beth Armstrong vs Thomas Lenkiewicz / Janice Greathouse3-6, 7-5, 1-0
2022-04-28vs LCTA40/Hatmaker/LegendOaksWon 10
W#3 DoublesShaun Roberson / Karen Hughes vs Bryan Hatmaker / Carita Hatmaker6-2, 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 standings for 7.0 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 3.25 estimated across 9 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.

3.77
Shaun Roberson
usually #3 Doubles 44%, also #1 Doubles 44% · published 4
3.64
Eric Epstein
published 4
3.35
Matt Zielke
published
3.34
Landa Tucker
published
3.27
Gregg Passmore
published 3.5
Beth Armstrong
published 3.5
3.12
Melanie Ivonowski
published
3.10
Karri King
published
3.00
Abigail Miller
published 3.5
2.64
Jennifer Waggoner
published
Karen Hughes
published
Kyle Degarady
published
William Furman
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.

Matt Zielke + Karri King134 matchesnot enough data
Karri King + Gregg Passmore134 matchesnot enough data
Abigail Miller + Gregg Passmore033 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
Shaun Roberson
317W–188L career · 9 lines in 2022
2%94%4%
3.77
4
Eric Epstein
31W–43L career · no lines in 2022
14%85%<1%
3.64
Matt Zielke
67W–49L career · no lines in 2022
<1%87%13%
3.35
Landa Tucker
36W–25L career · no lines in 2022
<1%88%11%
3.34
3.5
Gregg Passmore
90W–92L career · no lines in 2022
2%94%4%
3.27
3.5
Beth Armstrong
80W–18L career · no lines in 2022
not enough data
Melanie Ivonowski
39W–74L career · no lines in 2022
18%82%<1%
3.12
Karri King
21W–42L career · no lines in 2022
21%79%<1%
3.10
3.5
Abigail Miller
11W–29L career · no lines in 2022
51%49%<1%
3.00
Jennifer Waggoner
45W–37L career · no lines in 2022
15%85%<1%
2.64
Karen Hughes
56W–20L career · no lines in 2022
not enough data
Kyle Degarady
26W–5L career · no lines in 2022
not enough data
William Furman
38W–17L 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.