RallyIQ

ATP · Left-handed · 14 charted matches · 2005–2017

Gilles Muller

Archetype: Serve-and-volleyer · Net rusher

Against an average opponent

Serve points won 68.4% ±2.9 raw 66.9% · tour 63.4% · 1,264 points
Return points won 34.2% ±3.1 raw 26.9% · tour 36.6% · 1,116 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 +0.24 ±0.16 better than 96% of ATP · raw +0.24
Shot selection +0.37 ±0.36 better than 85% of ATP · raw +0.35
Execution −0.84 ±0.63 better than 31% of ATP · raw −1.14
Tactical adaptability +0.08 first serves toward what's working, set to set · 13 matches
Adaptation speed +0.07 same, every two to three service games · per 100 first serves
Points left on the table 3.21 per 100 shots vs best direction · lower than 12% 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 4,957 shots.

Shot expected value

The share of points Gilles Muller 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 · 181 shots

OptionUsedWin %Tour
BH crosscourt 26% 44.1%±10.0 47.6%
BH slice crosscourt 18% 37.5%±11.0 42.5%
BH down the line 17% 49.6%±11.5 46.4%
BH through the middle 15% 35.6%±11.5 43.7%
BH slice down the line 14% 32.0%±11.4 37.1%
BH slice through the middle 10% 23.2%±11.1 35.1%

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

position worth 44% to the average player · 149 shots

OptionUsedWin %Tour
FH crosscourt 45% 36.0%±8.5 46.6%
FH down the line 30% 44.5%±10.1 44.7%
FH through the middle 10% 40.8%±13.7 41.5%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 128 shots

OptionUsedWin %Tour
FH crosscourt 31% 49.2%±10.6 52.7%
FH down the line 20% 42.0%±12.0 51.5%
BH crosscourt 13% 49.5%±13.7 49.1%
BH slice down the line 9% 44.1%±14.4 45.6%
BH through the middle 9% 56.0%±14.7 46.8%

Return +1: drive to your backhand side

position worth 44% to the average player · 107 shots

OptionUsedWin %Tour
BH crosscourt 28% 36.8%±11.2 46.9%
BH slice down the line 22% 24.2%±10.6 33.3%
BH slice through the middle 15% 26.4%±12.1 32.6%
BH slice crosscourt 14% 43.4%±13.8 40.9%
BH through the middle 12% 44.3%±14.2 43.0%

Serve under pressure

Pressure predictability index −7 How much less varied Gilles Muller's first-serve direction gets on break points. Positive means easier to read. Based on 120 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 41% 33% 77% / 73%
Body 4% 4% 62% / 63%
T 55% 63% 76% / 75%

636 normal · 24 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 50% 43% 81% / 73%
Body 8% 15% 72% / 63%
T 42% 43% 78% / 72%

507 normal · 96 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% 63.0%±4.6 n=270 52% ▲
Body4% 64.3%±10.5 n=26 0% ▼
T55% 64.3%±4.0 n=364 48% ▼

Consistent with an optimal mix (p = 0.68).
Optimal mix: +0.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide49% 72.3%±4.1 n=294 62% ▲
Body9% 65.5%±8.4 n=56 0% ▼
T42% 69.5%±4.5 n=253 38% ▼

Consistent with an optimal mix (p = 0.28).
Optimal mix: +0.8 per 100 first serves.

Exploitability 0.47 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: +3.0±3.2 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. (618 repeats, 617 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 31 38% +0.9±10.2
1stAd courtT 139 20% −8.3±5.0
1stAd courtWide 169 21% −6.0±4.8
1stDeuce courtBody 39 30% −6.3±9.1
1stDeuce courtT 151 20% −5.4±4.9
1stDeuce courtWide 190 24% −3.5±4.7
2ndAd courtBody 67 42% −7.3±8.2
2ndAd courtT 66 39% −9.9±8.2
2ndAd courtWide 58 43% −5.7±8.7
2ndDeuce courtBody 82 44% −4.6±7.7
2ndDeuce courtT 65 34% −16.1±8.0
2ndDeuce courtWide 56 44% −4.6±8.8

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → BH volley crosscourt used 2.9% · won 78% · +0.1±9.4 vs own baseline
  2. T serve (deuce court) → FH crosscourt + approach used 2.9% · won 71% · −7.5±10.3 vs own baseline
  3. Wide serve (deuce court) → FH volley crosscourt used 2.8% · won 70% · −8.0±10.4 vs own baseline
  4. T serve (deuce court) → FH down the line used 3.3% · won 65% · −13.1±10.4 vs own baseline
  5. Body serve (deuce court) → FH crosscourt used 2.8% · won 62% · −15.7±11.0 vs own baseline

Return

  1. vs wide serve (ad court) → FH crosscourt, mid used 5.4% · won 44% · +14.7±11.3 vs own baseline
  2. vs T serve (ad court) → BH through the middle, mid used 6.1% · won 23% · −5.9±9.5 vs own baseline
  3. vs wide serve (ad court) → FH crosscourt used 4.9% · won 17% · −11.6±9.1 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → BH slice down the line used 9.5% · won 44% · +0.9±11.7 vs own baseline
  2. FH crosscourt → FH down the line used 18.0% · won 42% · −0.3±9.5 vs own baseline
  3. FH crosscourt → FH crosscourt used 14.7% · won 36% · −6.9±10.0 vs own baseline

Discovered sequences

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

  1. FH crosscourt → BH crosscourt → FH down the line used 1.2% · won 47% · +0.5±12.1 vs own baseline · −1.2 vs tour on the same sequence Disrupted by Andre Agassi (4/6)
  2. FH crosscourt → BH through the middle → FH crosscourt used 0.9% · won 38% · −8.4±12.5 vs own baseline · −27.8 vs tour on the same sequence
  3. FH crosscourt → BH crosscourt → FH crosscourt used 1.0% · won 36% · −11.0±11.9 vs own baseline · −27.4 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

T 1st serve · ad court+3.0253
Wide 1st serve · ad court+2.3294
Wide 1st serve · deuce court+0.8270
BH to the middle · return−0.1159
T 1st serve · deuce court−0.1364

Most exposed to

Wide 1st serve · ad court−2.8276
FH to their backhand · rally−2.1197
FH to their backhand · serve +1−1.8142
FH to their forehand · serve +1−1.8136
FH to their forehand · rally−0.8133

Active players who are best at the shot in the top weakness: Giovanni Mpetshi Perricard, Reilly Opelka, Nicolas Jarry, Nick Kyrgios, Maxime Cressy

Tactical fingerprint

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

Point-ending shots34.2%
Points at net20%
T serves · deuce55%
Backhand slice42%
BH down the line29%
Serve & volley32%
Unforced errors / shot12.8%
FH down the line35%
Chipped returns24%
Forehand share57%
T serves · ad42%
Deep returns30%
Drop shots / shot1.8%
1st serve in62%
Wide serves · ad49%
Wide serves · deuce41%
Run-around forehands10%
Avg rally length3.1
Through the middle15%

Plays most like

  1. Mark Philippoussis 1995–2003 plan v
  2. Jo Wilfried Tsonga 2007–2022 plan v
  3. Pierre Hugues Herbert 2014–2025 plan v
  4. Tim Henman 1995–2006 plan v
  5. Kevin King 2019–2019 plan v
  6. Todd Martin 1992–2001 plan v
  7. Sam Querrey 2010–2022 plan v
  8. Boris Becker 1985–1999 plan v

Closest from another era

  1. Boris Becker 1985–1999
  2. Pete Sampras 1990–2002
  3. Petr Korda 1991–1999

Charted matches