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SAC-Robblee/Hays

2020 Mixed 18 & Over · 6.0 Mixed

8 players · average NTRP 3.17 · USTA/PACIFIC NW / NORTHERN OREGON

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Scouting

Roster averages 2.98 estimated across 4 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.

3.37
Kim Tellin
usually #3 Doubles 50%, also #2 Doubles 33% · published 3.5
3.13
Hoon Shin
usually #1 Doubles 60%, also #2 Doubles 40% · published 3.5
2.90
Jinmi Kemple
usually #3 Doubles 60%, also #2 Doubles 40% · published 3
—
Jason Leong
usually #3 Doubles 50%, also #1 Doubles 50% · published 3
—
Steven Harrison
usually #3 Doubles 75%, also #2 Doubles 25% · published 3
2.51
Dave Sato
usually #2 Doubles 50%, also #1 Doubles 50% · published 3
—
Anup Pandya
usually #2 Doubles 50%, also #1 Doubles 50% · published 0
—
Stephen Galati
usually #3 Doubles 50%, also #2 Doubles 50% · published 0
Results8 ties
2019-11-17Won 3–0
W#1 DoublesDiana Crawford / Hoon Shin vs Hal Bond / Kalynn Belden7-5, 3-6, 1-0
W#2 DoublesAnn Hays / Anup Pandya vs Alisa Rakoz / Karl Kropp7-5, 6-4
W#3 DoublesKim Tellin / Jong Kim vs Margaret Huck / Andrew Huck6-4, 6-7, 1-0
2019-11-08Lost 0–3
L#1 DoublesSusan Robblee / Dave Sato vs William Seidl / Erin Casey6-1, 6-1
L#2 DoublesAnn Hays / Steven Harrison vs Lisa Bledsoe / Michael McTague6-2, 1-6, 1-0
L#3 DoublesCyndi Peck / Stephen Galati vs Maya Mori / Jamil Panni6-0, 6-1
2019-11-02Won 3–0
W#1 DoublesSusan Simmons / Dave Sato vs Kevin McMullen / Kate Quisling7-5, 6-3
W#2 DoublesJinmi Kemple / Stephen Galati vs Laurel Hallock Koppelman / Paul Ecker6-1, 6-1
W#3 DoublesSteven Harrison / Cyndi Peck vs Wendy Buchanan / Harrison Latto6-3, 5-0
2019-11-01Lost 1–2
W#1 DoublesSusan Robblee / Jason Leong vs Wendy Vaughn / Ty Bettis6-4, 2-6, 1-0
L#2 DoublesAnn Hays / Dave Sato vs Steve Snyder / Michele Snyder6-2, 6-3
L#3 DoublesJinmi Kemple / Steven Harrison vs Paula Morgan / Christopher Shaw6-3, 6-3
2019-10-27Lost 0–2
L#1 DoublesAnn Hays / Anup Pandya vs Nicola Ash / Nick Hooker6-2, 6-4
L#3 DoublesJason Leong / Jinmi Kemple vs Carol Glenn / Robert Glenn6-0, 6-4
2019-10-11Lost 1–2
L#1 DoublesSusan Robblee / Anup Pandya vs Joshua Smith / Leslie Cole6-3, 6-4
L#2 DoublesKim Tellin / Stephen Galati vs Mark Alan / Sarie Crothers7-6, 6-3
W#3 DoublesJinmi Kemple / Jong Kim vs Dana Austin / Kevin McMullen6-1, 6-4
2019-09-22Split 1–1
L#2 DoublesJinmi Kemple / Dave Sato vs Erin Canova / Shanu Shaharuvan Sukoor6-3, 7-6
W#3 DoublesSusan Simmons / Steven Harrison vs Rebecca Arguello / Ryan Ona6-4, 6-2
2019-09-07Lost 1–2
L#1 DoublesSusan Robblee / Hoon Shin vs Erin Casey / William Seidl6-4, 6-4
W#2 DoublesKim Tellin / Anup Pandya vs Lisa Bledsoe / Joshua Lewis7-5, 6-3
L#3 DoublesDiana Crawford / Stephen Galati vs Celina Baguiao / Paul Kim7-6, 4-6, 1-0
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.
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.

3.5
Kim Tellin
110W–71L career
0%97%2%
3.37
3.5
Hoon Shin
112W–53L career
13%87%0%
3.13
3
Jinmi Kemple
75W–78L career
0%96%4%
2.90
3
Jason Leong
16W–20L career
not enough data
—
3
Steven Harrison
45W–35L career
not enough data
—
3
Dave Sato
40W–110L career
31%69%0%
2.51
0
Anup Pandya
22W–6L career
not enough data
—
0
Stephen Galati
13W–20L career
not enough data
—

Three percentages are the year-end projection — chance of moving down, staying, moving up — and the number on the right is our estimated dynamic rating, which USTA never publishes. 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.