RallyIQ

ATP · Right-handed · 10 charted matches · 2024–2026

Ethan Quinn

Archetype: High-risk · Runs around the backhand

Against an average opponent

Serve points won 64.3% ±3.2 raw 63.9% · tour 63.4% · 845 points
Return points won 38.2% ±3.3 raw 36.7% · tour 36.6% · 830 points

Serve and return points won, refitted against every opponent at once so a record built on weak or strong opposition is put on the same scale. Career, all surfaces, with a 90% margin. Raw is the plain share of points won.

Value per 100 shots

Direction choice −0.06 ±0.07 better than 41% of ATP · raw −0.06
Shot selection ±0.00 ±0.19 better than 53% of ATP · raw +0.01
Execution −2.26 ±0.66 better than 1% of ATP · raw −2.08
Tactical adaptability −0.11 first serves toward what's working, set to set · 10 matches
Adaptation speed +0.04 same, every two to three service games · per 100 first serves
Points left on the table 2.56 per 100 shots vs best direction · lower than 55% of ATP

Points gained per 100 shots compared with an average tour player in the same position, adjusted for the strength of the opponents faced, with a 90% margin (shots clustered by match). Raw is before the opponent adjustment. Built on 3,778 shots.

Shot expected value

The share of points Ethan Quinn goes on to win after each option in the positions they face most often, shrunk toward tour average when the sample is small. Showing the 8 most-used options; teal marks the best one with at least 30 shots.

Rally, shots 5–8: drive to your backhand side

position worth 46% to the average player · 185 shots

OptionUsedWin %Tour
BH crosscourt 40% 48.4%±8.5 47.6%
BH through the middle 19% 47.8%±11.0 43.7%
BH slice crosscourt 14% 51.1%±12.1 42.5%
FH inside-out 9% 48.2%±13.7 51.8%
BH down the line 8% 37.9%±13.5 46.4%
BH slice through the middle 7% 27.4%±12.8 35.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 160 shots

OptionUsedWin %Tour
FH down the line 25% 50.5%±10.6 51.5%
FH crosscourt 21% 44.4%±11.2 52.7%
BH through the middle 16% 47.5%±12.2 46.8%
FH through the middle 15% 46.4%±12.4 47.0%
BH crosscourt 11% 48.2%±13.5 49.1%

Return +1: drive to your backhand side

position worth 44% to the average player · 117 shots

OptionUsedWin %Tour
BH crosscourt 30% 48.0%±11.1 46.9%
BH through the middle 21% 37.7%±12.0 43.0%
BH slice crosscourt 15% 42.6%±13.2 40.9%
BH slice through the middle 13% 30.0%±12.7 32.6%
BH down the line 13% 42.4%±13.7 44.2%
FH inside-out 9% 57.8%±14.8 51.7%

Rally, shots 5–8: drive to your forehand side

position worth 44% to the average player · 95 shots

OptionUsedWin %Tour
FH crosscourt 62% 48.5%±9.2 46.6%
FH through the middle 19% 35.0%±12.7 41.5%
FH down the line 19% 49.9%±13.3 44.7%

Serve under pressure

Pressure predictability index +7 How much less varied Ethan Quinn's first-serve direction gets on break points. Positive means easier to read. Based on 80 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 41% 48% 70% / 73%
Body 16% 5% ▼ 62% / 63%
T 44% 48% 78% / 75%

422 normal · 21 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 38% 58% ▲ 75% / 73%
Body 9% 8% 67% / 63%
T 53% 34% ▼ 71% / 72%

341 normal · 59 break-point 1st serves

Is the serve mix in equilibrium?

Game theory says a well-mixed server wins equally often with every direction they use. If one direction wins more, it's underused and points are being left behind. This is the minimax test Walker and Wooders ran on Wimbledon finals, applied to every charted first serve. Win rates include faults. "Optimal" allows for returners reading a habit. No measurable response (−0.05 ± 0.15 points per 100 serves for every 10 points of habitual usage), measured from ATP servers whose mix drifted between matches. Shifts stay within the range servers' habits actually vary, the only range that response was measured over.

Deuce court

1st serveUsagePoints wonOptimal
Wide41% 61.9%±5.5 n=182 41%
Body15% 56.7%±8.3 n=67 2% ▼
T44% 66.2%±5.2 n=194 57% ▲

Consistent with an optimal mix (p = 0.16).
Optimal mix: +0.9 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide41% 63.1%±5.7 n=163 37% ▼
Body9% 64.5%±9.7 n=36 0% ▼
T50% 66.8%±5.1 n=201 63% ▲

Consistent with an optimal mix (p = 0.68).
Optimal mix: +0.5 per 100 first serves.

Exploitability 0.68 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of ATP servers. Tested on matches they weren't fitted on, ATP mixes picked this way win 0.33 per 100 first serves on average.

Repeating the previous direction to the same court: +5.1±4.2 points per 100 against switching. Negative means returners read repeats. Tour-wide, repeating costs women about 0.4 points per 100 and costs men nothing, so men's returners don't measurably anticipate direction. (242 repeats, 581 switches.)

Return by serve direction

Return points won against each serve direction, compared with the tour average.

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 25 46% +8.6±11.0
1stAd courtT 109 26% −1.8±6.1
1stAd courtWide 98 23% −4.4±6.1
1stDeuce courtBody 31 38% +1.0±10.2
1stDeuce courtT 117 30% +4.5±6.2
1stDeuce courtWide 126 28% +0.5±5.9
2ndAd courtBody 52 51% +1.6±9.1
2ndAd courtT 26 46% −3.2±11.0
2ndAd courtWide 85 49% +0.8±7.7
2ndDeuce courtBody 49 54% +5.0±9.2
2ndDeuce courtT 60 40% −9.8±8.5
2ndDeuce courtWide 50 54% +6.2±9.2

Signature patterns

Recurring sequences that win more than Ethan Quinn's own baseline, ranked by edge weighted by how often they're used.

Serve → +1

  1. Body serve (deuce court) → FH crosscourt used 5.2% · won 62% · −14.0±10.5 vs own baseline

Return

  1. vs wide serve (ad court) → BH through the middle, deep used 6.2% · won 44% · +10.3±11.6 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, mid used 8.4% · won 41% · +6.6±10.7 vs own baseline
  3. vs T serve (ad court) → FH slice through the middle, mid used 7.1% · won 36% · +2.2±10.9 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 8.4% · won 50% · +6.4±11.8 vs own baseline
  2. FH crosscourt → FH crosscourt used 14.3% · won 49% · +4.7±10.1 vs own baseline
  3. BH crosscourt → BH crosscourt used 9.7% · won 48% · +3.5±11.4 vs own baseline
  4. BH crosscourt → FH crosscourt used 8.4% · won 44% · +0.4±11.7 vs own baseline
  5. BH through the middle → BH crosscourt used 8.8% · won 38% · −6.4±11.4 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Ethan Quinn wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.

  1. BH crosscourt → BH crosscourt → BH crosscourt used 1.7% · won 54% · +7.1±11.2 vs own baseline · +12.3 vs tour on the same sequence Disrupted by Tallon Griekspoor (2/9), Hubert Hurkacz (4/6)
  2. FH crosscourt → FH through the middle → FH down the line used 1.1% · won 47% · −0.1±12.7 vs own baseline · −6.0 vs tour on the same sequence
  3. FH crosscourt → FH crosscourt → FH crosscourt used 1.9% · won 45% · −2.2±11.0 vs own baseline · −5.5 vs tour on the same sequence Disrupted by Tallon Griekspoor (3/8), Marton Fucsovics (4/6)
  4. BH through the middle → FH down the line → BH crosscourt used 1.2% · won 36% · −11.4±11.9 vs own baseline · −25.6 vs tour on the same sequence

Strengths and vulnerabilities

Value per 100 shots compared with the average player hitting (strengths) or facing (vulnerabilities) the same shot. Only shot types seen at least 120 times.

Hurts opponents most with

FH to their backhand · rally+1.5158
Wide 1st serve · deuce court+0.1182
T 1st serve · deuce court−0.2194
Wide 1st serve · ad court−0.8163
FH to their forehand · rally−1.6189

Most exposed to

FH to their forehand · rally−0.2146
T 1st serve · deuce court+0.6175
BH to the middle · return+1.0154
T 1st serve · ad court+1.1171
FH to their backhand · rally+1.1147

Active players who are best at the shot in the top weakness: Roberto Carballes Baena, Roberto Bautista Agut, Miomir Kecmanovic, Pedro Martinez, Camilo Ugo Carabelli

Tactical fingerprint

Each bar shows how far a style trait is from the ATP average, in standard deviations.

T serves · ad50%
Chipped returns33%
Unforced errors / shot13.4%
Deep returns38%
Point-ending shots30.5%
Points at net14%
Backhand slice26%
Run-around forehands22%
Through the middle25%
Serve & volley11%
1st serve in62%
Forehand share53%
Drop shots / shot1.6%
BH down the line20%
T serves · deuce44%
Wide serves · deuce41%
FH down the line28%
Avg rally length3.4
Wide serves · ad41%

Plays most like

  1. Zhizhen Zhang 2019–2026 plan v
  2. Lucas Pouille 2015–2024 plan v
  3. Zizou Bergs 2021–2026 plan v
  4. Kevin Anderson 2011–2022 plan v
  5. Tim Van Rijthoven 2021–2023 plan v
  6. Fabio Fognini 2012–2025 plan v
  7. Aleksandar Kovacevic 2021–2026 plan v
  8. Alexei Popyrin 2019–2026 plan v

Closest from another era

  1. Roger Federer 1998–2021
  2. James Blake 2002–2011
  3. Mark Philippoussis 1995–2003

Charted matches