Teams

Mixed Tri Shinder

AZ Slaughter Mixed Tri Level · AZ Slaughter

12 players · average NTRP 3.83 / CENTRAL ARIZONA

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 →
Flight standings6 teams · AZ Slaughter
TeamWLInd. WInd. LSets lostGames lost
1Mixed Tri Shinder4110512124
2Mixed Tri Taylor4110516137
3Mixed Tri Rhodehouse3210512110
4Mixed Tri Perrin236919146
5Mixed Tri Also Super Seriously Mixed2351023160
6Mixed Tri Super Seriously Mixed0541124167

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 3.66 estimated across 6 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.

4.11
Kendall Hanks
published
4.07
Aditya Sharma
published 4.5
3.87
Arielle Shinder
published 4
Deborah White
published 4
3.57
Mario Vargas
published
Craig Kosnik
published 3.5
3.17
Boyan Vassilev
published 3.5
3.13
Denise Echeverria
published 3.5
Kyle Faino
published
Silviya Dimitrova
published
Tacker Frink
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.

Kendall Hanks + Aditya Sharma8755% games+11.2% vs expected
Craig Kosnik + Arielle Shinder4256% games+6.6% vs expected
Aditya Sharma + Arielle Shinder3252% gamesnot enough data
Arielle Shinder + Tacker Frink404 matchesnot enough data
Kyle Faino + Arielle Shinder123 matchesnot enough data
Kendall Hanks + Craig Kosnik123 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.

Kendall Hanks
141W–98L career · no lines in 2022
20%80%<1%
4.11
4.5
Aditya Sharma
141W–99L career · no lines in 2022
29%71%<1%
4.07
4
Arielle Shinder
113W–76L career · no lines in 2022
<1%84%16%
3.87
4
Deborah White
16W–2L career · no lines in 2022
not enough data
Mario Vargas
42W–52L career · no lines in 2022
30%70%<1%
3.57
3.5
Craig Kosnik
172W–143L career · no lines in 2022
not enough data
3.5
Boyan Vassilev
23W–24L career · no lines in 2022
9%90%1%
3.17
3.5
Denise Echeverria
117W–114L career · no lines in 2022
15%84%<1%
3.13
Kyle Faino
15W–13L career · no lines in 2022
not enough data
Silviya Dimitrova
3W–0L career · no lines in 2022
not enough data
Suzanne Jocelyn Legg-Matthews
46W–65L career · no lines in 2022
not enough data
Tacker Frink
11W–5L 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.