Teams

MSIL 3.5M A40&O Wang-Peoria

2022 MSIL Adult 40 & Over -MSIL West League · West MSIL A40 & Over 3.5M

9 players · average NTRP 3.50 / MID-SOUTH ILLINOIS

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 →
Schedule7 played
2022-07-25vs MSIL 3.5M A40&O Mean MachineLost 13
W#1 DoublesDouglas Kinas / Madhu Reddy vs Thomas Smith / Ravi Singhal6-1, 6-1
L#1 SinglesFei Wang vs Craig Conway3-6, 4-6
L#2 DoublesErik Siembab / Joe Mulcahey vs Don Varghese / Douglas Hundman3-6, 6-7
L#3 DoublesThuy Le / Ming Liao vs Mark Miller / Todd Kettering2-6, 6-2, 0-1
2022-07-11vs MSIL 3.5M A40&O Mean MachineLost 13
L#1 DoublesErik Siembab / Joe Mulcahey vs Craig Conway / Tod Nicholls1-6, 2-6
W#1 SinglesDouglas Kinas vs Joseph McCarron1-6, 6-4, 1-0
L#2 DoublesMadhu Reddy / James Davis vs Douglas Hundman / Gregg Mecherle4-6, 4-6
L#3 DoublesMichael Pershing / Fei Wang vs Todd Kettering / Don Varghese3-6, 4-6
2022-06-20vs MSIL 3.5M A40&O Mean MachineLost 13
L#1 DoublesThuy Le / Joe Mulcahey vs Joseph McCarron / Ravi Singhal6-2, 4-6, 0-1
W#1 SinglesSabari Giri vs Craig Conway6-0, 6-2
L#2 DoublesMing Liao / Xuefeng SONG vs Mark Miller / Don Varghese2-6, 6-4, 0-1
L#3 DoublesFei Wang / Michael Pershing vs Todd Kettering / Gregg Mecherle3-6, 3-6
2022-06-13vs MSIL 3.5M A40&O Mean MachineLost 12
W#1 DoublesSabari Giri / Michael Pershing vs David Martin / Ravi Singhal6-1, 6-4
L#2 DoublesFei Wang / Ming Liao vs Mark Miller / Don Varghese0-6, 1-6
L#3 DoublesThuy Le / James Davis vs Todd Kettering / Gregg Mecherle2-6, 3-6
2022-06-06vs MSIL 3.5M A40&O Mean MachineWon 31
W#1 DoublesDouglas Kinas / Madhu Reddy vs Mark Miller / Todd Kettering6-3, 7-5
W#1 SinglesSabari Giri vs Craig Conway6-3, 3-0
W#2 DoublesThuy Le / Joe Mulcahey vs Ravi Singhal / Joseph McCarron7-5, 6-4
L#3 DoublesJames Davis / Ming Liao vs Don Varghese / Gregg Mecherle7-5, 4-6, 0-1
2022-05-16vs MSIL 3.5M A40&O Mean MachineWon 30
W#1 DoublesSabari Giri / Erik Siembab vs Gregg Mecherle / Todd Kettering6-4, 6-7, 1-0
W#2 DoublesMadhu Reddy / Joe Mulcahey vs Don Varghese / David Martin7-6, 7-5
W#3 DoublesFei Wang / Thuy Le vs Joseph McCarron / Thomas Smith6-2, 6-1
2022-05-11vs MSIL 3.5M A40&O Mean MachineLost 12
W#1 DoublesSabari Giri / Ming Liao vs Tod Nicholls / Thomas Smith6-1, 6-1
L#2 DoublesJames Davis / Michael Pershing vs Todd Kettering / Ravi Singhal6-3, 6-7, 0-1
L#3 DoublesErik Siembab / Fei Wang vs Craig Conway / Don Varghese3-6, 0-6
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 standings2 teams · West MSIL A40 & Over 3.5M
TeamWLInd. WInd. LSets lostGames lost
1MSIL 3.5M A40&O Mean Machine6120821200
2MSIL 3.5M A40&O Wang-Peoria1682041285

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 3.19 estimated across 3 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.

3.45
Madhu Reddy
usually #2 Doubles 50%, also #1 Doubles 50% · published
Douglas Kinas
usually #1 Doubles 67%, also #1 Singles 33% · published 3.5
Fei Wang
usually #3 Doubles 67%, also #2 Doubles 17% · published 3.5
3.25
Erik Siembab
usually #1 Doubles 50%, also #3 Doubles 25% · published 3.5
2.87
Joe Mulcahey
usually #2 Doubles 60%, also #1 Doubles 40% · published
Michael Pershing
usually #3 Doubles 50%, also #2 Doubles 25% · published
Ming Liao
usually #3 Doubles 40%, also #2 Doubles 40% · published
Sabari Giri
usually #1 Doubles 60%, also #1 Singles 40% · published
Thuy Le
usually #3 Doubles 60%, also #2 Doubles 20% · 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.

Joe Mulcahey + Erik Siembab2637% games−14.8% vs expected
Fei Wang + Erik Siembab0539% gamesnot enough data
Joe Mulcahey + Thuy Le224 matchesnot enough data
Douglas Kinas + Madhu Reddy213 matchesnot enough data
Ming Liao + Fei Wang123 matchesnot enough data
Fei Wang + Thuy Le213 matchesnot enough data
Erik Siembab + Michael Pershing123 matchesnot enough data
Erik Siembab + Sabari Giri303 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.

Madhu Reddy
49W–19L career · 4 lines in 2022
<1%65%35%
3.45
3.5
Douglas Kinas
15W–9L career · 3 lines in 2022
not enough data
3.5
Fei Wang
18W–25L career · 6 lines in 2022
not enough data
3.5
Erik Siembab
90W–95L career · 4 lines in 2022
3%95%2%
3.25
Joe Mulcahey
30W–60L career · 5 lines in 2022
<1%83%17%
2.87
Michael Pershing
10W–17L career · 4 lines in 2022
not enough data
Ming Liao
4W–5L career · 5 lines in 2022
not enough data
Sabari Giri
16W–4L career · 5 lines in 2022
not enough data
Thuy Le
15W–8L career · 5 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.