Teams

SFV - Trilogy

2022 SCTA Tri-Level 18+ SFV · SFV - Men's 3.0-4.0

9 players · average NTRP 3.70 / SO.CALIFORNIA

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 →

Flight standings for SFV - Men's 3.0-4.0 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 3.58 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.

4.03
Stephen Nettelhorst
usually #1 Doubles 80%, also #3 Doubles 20% · published 4
3.97
Jared Mano
usually #2 Doubles 40%, also #1 Doubles 40% · published
3.64
Artin Davodian
usually #3 Doubles 83%, also #1 Doubles 17% · published 3.5
3.47
Burke Franklin
usually #1 Doubles 100% · published 4
3.42
Jose MacKinney
published
3.31
Lee Tsai
usually #3 Doubles 75%, also #2 Doubles 25% · published 3.5
3.24
Guillermo Giuliani
published 3.5
Nazar Makadsi
published
RUBEN SIMON
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.

Jared Mano + Burke Franklin2350% gamesnot enough data
Jared Mano + Lee Tsai213 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.

4
Stephen Nettelhorst
157W–52L career · 5 lines in 2022
<1%41%59%
4.03
Jared Mano
91W–52L career · 5 lines in 2022
<1%60%40%
3.97
3.5
Artin Davodian
167W–59L career · 6 lines in 2022
<1%14%86%
3.64
4
Burke Franklin
157W–97L career · 2 lines in 2022
58%42%<1%
3.47
Jose MacKinney
7W–8L career · no lines in 2022
<1%<1%>99%
3.42
3.5
Lee Tsai
212W–155L career · 4 lines in 2022
1%92%7%
3.31
3.5
Guillermo Giuliani
5W–4L career · no lines in 2022
3%94%2%
3.24
Nazar Makadsi
4W–7L career · no lines in 2022
not enough data
RUBEN SIMON
0W–1L career · no 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.