Teams

SFV Grand Slammers

SFV-Mixed 40 & Over · SFV 40 & Over MXD Doubles 7.0

9 players · average NTRP 3.50 / SO.CALIFORNIA

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Schedule5 played
L#3 DoublesGreg Siegel / Sanaz Ossanloo vs Tony Lujan / Sylvia Yaafe2-6, 3-6
2021-05-29vs SFV PV CrushersLost 01
L#1 DoublesCAROLINA MEDINA / Greg Siegel vs Chad Fenwick / Vanessa Rodriguez1-6, 2-6
2021-05-16Won 10
W#1 DoublesGreg Siegel / Tammy Scher vs Evan Cohen / Sharon Aguila6-2, 6-3
2021-05-01vs SFV Pure DriveLost 01
L#1 DoublesGreg Siegel / Michelle Halpern vs Mike Spigno / Amy Randles6-1, 4-6, 0-1
2021-04-24Won 10
W#1 DoublesTammy Scher / Greg Siegel vs Alex Choi / Carol Stevenson6-3, 7-6
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 SFV 40 & Over MXD Doubles 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 3.38 estimated across 7 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.

3.85
Lan Chao
published
3.45
Michelle Halpern
published
3.45
CAROLINA MEDINA
published 3.5
3.30
Chang Yi
published 3.5
3.29
Greg Siegel
usually #1 Doubles 80%, also #3 Doubles 20% · published 3.5
3.23
Oscar Campos
published
3.08
Tammy Scher
published
Jeff Sutterman
published
Sanaz Ossanloo
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.

Michelle Halpern + Greg Siegel213 matchesnot enough data
CAROLINA MEDINA + Greg Siegel303 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.

Lan Chao
23W–5L career · no lines in 2021
<1%88%12%
3.85
Michelle Halpern
25W–9L career · no lines in 2021
<1%65%35%
3.45
3.5
CAROLINA MEDINA
13W–2L career · no lines in 2021
<1%66%34%
3.45
3.5
Chang Yi
13W–6L career · no lines in 2021
1%93%6%
3.30
3.5
Greg Siegel
173W–158L career · 5 lines in 2021
1%93%6%
3.29
Oscar Campos
0W–5L career · no lines in 2021
4%94%2%
3.23
Tammy Scher
4W–26L career · no lines in 2021
28%72%<1%
3.08
Jeff Sutterman
1W–0L career · no lines in 2021
not enough data
Sanaz Ossanloo
2W–4L career · no lines in 2021
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.