A40 3.0W CSC Schuele
2025 NEOTA Adult 40 & Over · NEOTA A40&O 3.0 Women
17 players · average NTRP 2.80 / NORTHEASTERN OHIO
No matches recorded for this roster in this league — it may be a placeholder registration, or the season may not have started.
Schedule10 played
i
Flight standings26 teams · NEOTA A40&O 3.0 Women
| Team | W | L | Sets lost | Games lost |
|---|---|---|---|---|
| 1A40 3.0W PM1 Sloan | 10 | 0 | 37 | 393 |
| 2A40 3.0W LT2 Sirak | 9 | 1 | 28 | 341 |
| 3NEO/Gelal/A40/3.0W | 9 | 1 | 31 | 341 |
| 4A40 3.0W MV2 Hunter | 7 | 3 | 45 | 388 |
| 5A40 3.0W CV Urbanowski | 7 | 3 | 45 | 407 |
| 6A40 3.0W MV1 Cunningham | 7 | 3 | 46 | 398 |
| 7A40 3.0W AO1 Drapcho | 6 | 4 | 47 | 439 |
| 8A40 3.0W BR Sweeney | 6 | 4 | 47 | 422 |
| 9A40 3.0W CC Stoica | 6 | 4 | 49 | 417 |
| 10A40 3.0W WE Allan | 6 | 4 | 56 | 437 |
| 11A40 3.0W CSC Schuele | 5 | 5 | 56 | 454 |
| 12A40 3.0W CRC Gardner | 5 | 5 | 62 | 441 |
| 13A40 3.0W NC1 Adams | 5 | 5 | 63 | 479 |
| 14A40 3.0W WR2 Strobach | 5 | 5 | 63 | 494 |
| 15A40 3.0W TP1 Dean | 4 | 6 | 54 | 448 |
| 16A40 3.0W PW2 McCarthy | 4 | 6 | 58 | 464 |
| 17A40 3.0W PCC Innes | 4 | 6 | 59 | 461 |
| 18A40 3.0W GR Neely | 4 | 6 | 60 | 446 |
| 19A40 3.0W PM2 Whitlam | 4 | 6 | 62 | 469 |
| 20A40 3.0W WR1 Mollison | 3 | 7 | 68 | 484 |
| 21A40 3.0W AO2 Glass | 3 | 7 | 68 | 497 |
| 22A40 3.0W PW1 Keller | 3 | 7 | 70 | 508 |
| 23A40 3.0W WCC McFarland | 3 | 7 | 71 | 503 |
| 24A40 3.0W LT1 Barker | 3 | 7 | 79 | 533 |
| 25A40 3.0W AVB Pallante | 2 | 8 | 70 | 494 |
| 26A40 3.0W TP2 Stewart | 0 | 10 | 77 | 513 |
Ordered by team wins, then losses, then sets lost — the order USTA uses to seed a flight. Individual wins are lines, not ties.
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 2.55 estimated across 14 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.
Doubles pairs from this roster with three or more matches together anywhere — ordered by performance against what the rating gap predicted, not by record.
| Jeri Taylor + Molly Marudas | 4–2 | 61% games | not enough data |
| Catherine Curley + Karen Schuele | 3–3 | 54% games | not enough data |
| Karen Schuele + Sherry Shaw | 0–5 | 31% games | not enough data |
| Jeri Taylor + Tara Hata | 3–1 | 4 matches | not enough data |
| Jeri Taylor + Lynda Montgomery | 0–4 | 4 matches | not enough data |
| Jeri Taylor + Julie Lamb | 1–3 | 4 matches | not enough data |
| Tara Hata + Catherine Curley | 1–3 | 4 matches | not enough data |
| Tara Hata + Julie Lamb | 1–3 | 4 matches | not enough data |
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.
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.