5LIB-VOGLER 40 W/E WOMEN SINGLES SEM F1
2022 SEM FALL TEAM SINGLES · WOMEN 4.0 SINGLES SEM
10 players · average NTRP 4.00 / S.E. MICHIGAN
No matches recorded for this roster in this league — it may be a placeholder registration, or the season may not have started.
Schedule8 played
i
Flight standings10 teams · WOMEN 4.0 SINGLES SEM
| Team | W | L | Sets lost | Games lost |
|---|---|---|---|---|
| 12CHIP-SPARR 40 W/E WOMEN SINGLES SEM F1 | 6 | 2 | 12 | 137 |
| 23BEV-STRACHAN 40 W/E WOMEN SINGLES SEM F1 | 6 | 2 | 20 | 187 |
| 34LTF-WHITE 40 W/E WOMEN SINGLES SEM F2 | 6 | 2 | 20 | 175 |
| 43DEER-RACHWAL 40 W/E WOMEN SINGLES SEM F2 | 4 | 4 | 22 | 185 |
| 51WESS-DEMERINO 40 W/E WOMEN SINGLES SEM F2 | 4 | 4 | 26 | 195 |
| 61SCWB-FARRELL 40 W/E WOMEN SINGLES SEM F1 | 3 | 5 | 26 | 211 |
| 76BLOOM-FARWELL 40 W/E WOMEN SINGLES SEM F2 | 3 | 5 | 28 | 199 |
| 86HV-VANBUHLER 40 W/E WOMEN SINGLES SEM F1 | 3 | 5 | 29 | 189 |
| 95PEACH-HANLEY 40 W/E WOMEN SINGLES SEM F2 | 3 | 5 | 31 | 202 |
| 105LIB-VOGLER 40 W/E WOMEN SINGLES SEM F1 | 2 | 6 | 31 | 220 |
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 3.71 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.
Doubles pairs from this roster with three or more matches together anywhere — ordered by performance against what the rating gap predicted, not by record.
| Molly Lipham + Abigail Bremer | 6–3 | 53% games | −0.1% vs expected |
| Laura LeVasseur + Kerri-Ann Croftchik | 3–2 | 53% games | −1.2% vs expected |
| Abigail Bremer + Erin Case | 2–4 | 44% games | −3.6% vs expected |
| Molly Lipham + Laura LeVasseur | 4–2 | 47% games | −6.8% vs expected |
| Molly Lipham + Kerri-Ann Croftchik | 3–2 | 46% games | −8.4% vs expected |
| Kerri-Ann Croftchik + Abigail Bremer | 4–1 | 61% games | not enough data |
| Molly Lipham + Jennifer Morgan | 3–1 | 4 matches | not enough data |
| Molly Lipham + Jennifer Sauld | 2–1 | 3 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.