Teams

LCTA18/Keiper/CTC

2022 LCTA 18 & Over Fall League · 18 & over Fall League Men 3.5

11 players · average NTRP 3.62 / 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 →
Schedule4 played
2022-10-17vs LCTA18/LeePassmore/DotyParkWon 10
W#2 SinglesAdam Smith vs Andrew Merritt6-3, 6-3
2022-10-10Won 10
W#2 SinglesAdam Smith vs Callan Barr6-2, 6-3
2022-09-26Won 10
W#1 SinglesAdam Smith vs Scott Levy6-0, 6-1
2022-09-12vs LCTA18/Steiner/StAndrewsWon 10
W#2 SinglesAdam Smith vs George Ramsay6-0, 6-0
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 standings for 18 & over Fall League Men 3.5 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 3.56 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.

4.20
Nicholas Connolly
published
3.92
Chris Wigginton
published 4
3.65
Morgan Philoxene
published
3.50
Bradley Harrison
published 3.5
3.50
Adam Smith
usually #2 Singles 60%, also #1 Singles 20% · published 3.5
3.43
Will Scanlon
published
3.37
William Keiper
published
3.34
Xan McLaughlin
published
Craig Modzelewski
published 3.5
3.14
Joel Trantham
published
Jeffrey Shealy
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.

Chris Wigginton + Bradley Harrison7262% games+8.2% vs expected
Will Scanlon + Bradley Harrison10262% games+4.9% vs expected
Morgan Philoxene + Bradley Harrison6253% games+2.8% vs expected
William Keiper + Jeffrey Shealy314 matchesnot enough data
Bradley Harrison + Jeffrey Shealy404 matchesnot enough data
Morgan Philoxene + Will Scanlon213 matchesnot enough data
Will Scanlon + Jeffrey Shealy123 matchesnot enough data
Chris Wigginton + Nicholas Connolly123 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.

Nicholas Connolly
37W–18L career · no lines in 2022
7%92%1%
4.20
4
Chris Wigginton
125W–66L career · no lines in 2022
<1%73%27%
3.92
Morgan Philoxene
29W–17L career · no lines in 2022
12%87%<1%
3.65
3.5
Bradley Harrison
51W–24L career · no lines in 2022
<1%50%50%
3.50
3.5
Adam Smith
129W–51L career · 5 lines in 2022
<1%51%49%
3.50
Will Scanlon
82W–44L career · no lines in 2022
<1%71%29%
3.43
William Keiper
62W–21L career · no lines in 2022
<1%84%16%
3.37
Xan McLaughlin
47W–30L career · no lines in 2022
<1%88%11%
3.34
3.5
Craig Modzelewski
16W–6L career · no lines in 2022
not enough data
Joel Trantham
22W–13L career · no lines in 2022
14%86%<1%
3.14
Jeffrey Shealy
13W–8L 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.