RallyIQ

ATP · Right-handed · 134 charted matches · 2005–2026

Gael Monfils

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 65.2% ±2.4 raw 63.1% · tour 63.4% · 11,617 points
Return points won 39.1% ±2.5 raw 37.0% · tour 36.6% · 11,379 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 −0.08 ±0.05 better than 35% of ATP · raw −0.08
Shot selection −0.10 ±0.07 better than 40% of ATP · raw −0.11
Execution +0.40 ±0.24 better than 82% of ATP · raw +0.36
Tactical adaptability +0.08 first serves toward what's working, set to set · 134 matches
Adaptation speed +0.07 same, every two to three service games · per 100 first serves
Long-rally execution −0.02 ±0.36 shot 9 on v own earlier rally shots · 9,390 shots · better than 75% of ATP
Points left on the table 2.57 per 100 shots vs best direction · lower than 52% 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 62,106 shots.

Shot expected value

The share of points Gael Monfils 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 · 4,529 shots

OptionUsedWin %Tour
BH crosscourt 39% 47.4%±1.9 47.6%
BH through the middle 26% 43.1%±2.4 43.7%
BH down the line 12% 46.6%±3.4 46.4%
FH inside-out 8% 52.1%±4.2 51.8%
BH slice crosscourt 4% 43.7%±5.7 42.5%
BH slice through the middle 3% 31.6%±6.1 35.1%
FH inside-in 3% 52.0%±6.8 54.7%
FH through the middle 3% 45.6%±7.0 45.2%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 3,284 shots

OptionUsedWin %Tour
BH crosscourt 43% 49.2%±2.2 48.0%
BH through the middle 24% 43.3%±2.9 43.8%
BH down the line 12% 41.9%±4.0 46.5%
BH slice crosscourt 6% 47.8%±5.7 42.1%
FH inside-out 6% 53.4%±5.7 52.6%
BH slice through the middle 4% 32.9%±6.5 35.1%
FH inside-in 2% 50.9%±8.6 54.3%
BH slice down the line 2% 30.6%±8.5 35.8%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 2,833 shots

OptionUsedWin %Tour
FH crosscourt 22% 52.0%±3.2 52.7%
FH down the line 20% 50.0%±3.4 51.5%
FH through the middle 20% 39.8%±3.3 47.0%
BH through the middle 14% 45.1%±4.0 46.8%
BH crosscourt 12% 53.6%±4.2 49.1%
BH down the line 4% 42.6%±6.7 48.3%
BH slice through the middle 1% 52.0%±11.9 44.8%
BH slice crosscourt 1% 48.8%±11.9 47.0%

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

position worth 44% to the average player · 2,656 shots

OptionUsedWin %Tour
FH crosscourt 42% 48.2%±2.5 46.6%
FH through the middle 26% 44.6%±3.1 41.5%
FH down the line 18% 44.6%±3.7 44.7%
FH slice through the middle 7% 30.0%±5.2 24.5%
FH slice down the line 3% 35.4%±8.4 25.6%
FH slice crosscourt 3% 35.8%±8.5 30.9%
BH inside-out 1% 47.3%±14.1 45.4%
FH drop shot down the line 0% 56.0%±14.4 49.6%

Serve under pressure

Pressure predictability index ±0 How much less varied Gael Monfils's first-serve direction gets on break points. Positive means easier to read. Based on 914 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 40% 41% 71% / 73%
Body 8% 11% 62% / 63%
T 52% 48% 77% / 75%

5,830 normal · 207 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 54% 49% 78% / 73%
Body 6% 4% 65% / 63%
T 40% 46% 67% / 72%

4,808 normal · 707 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
Wide40% 65.1%±1.6 n=2,420 53% ▲
Body8% 60.3%±3.5 n=492 0% ▼
T52% 62.8%±1.4 n=3,125 47% ▼

Consistent with an optimal mix (p = 0.05).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide53% 64.1%±1.4 n=2,948 67% ▲
Body5% 60.6%±4.4 n=302 0% ▼
T41% 61.0%±1.7 n=2,265 33% ▼

Off equilibrium (p = 0.043): serve wide more. Gap 1.5 points per 100 first serves.
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.49 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: +1.0±1.3 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. (5,249 repeats, 6,035 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 402 36% −1.3±3.8
1stAd courtT 1,422 30% +2.4±2.0
1stAd courtWide 1,506 29% +2.0±1.9
1stDeuce courtBody 442 36% −1.1±3.6
1stDeuce courtT 1,559 29% +4.4±1.9
1stDeuce courtWide 1,699 29% +2.0±1.8
2ndAd courtBody 791 48% −1.4±2.9
2ndAd courtT 352 51% +2.0±4.2
2ndAd courtWide 928 49% +0.2±2.7
2ndDeuce courtBody 988 46% −3.1±2.6
2ndDeuce courtT 853 50% −0.1±2.8
2ndDeuce courtWide 385 45% −3.2±4.0

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.7% · won 66% · −0.8±4.4 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 2.0% · won 64% · −3.4±5.0 vs own baseline
  3. T serve (ad court) → FH down the line used 2.6% · won 58% · −9.4±4.6 vs own baseline
  4. Wide serve (deuce court) → BH crosscourt used 2.3% · won 55% · −12.0±5.0 vs own baseline
  5. T serve (deuce court) → FH down the line used 3.0% · won 56% · −11.1±4.3 vs own baseline

Return

  1. vs T serve (deuce court) → BH through the middle, mid used 4.4% · won 48% · +10.1±3.8 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, deep used 2.4% · won 51% · +13.2±5.1 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, mid used 4.4% · won 47% · +8.7±3.8 vs own baseline
  4. vs T serve (ad court) → FH through the middle, mid used 2.4% · won 49% · +10.6±5.1 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, short used 2.7% · won 48% · +9.5±4.8 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH inside-out used 1.1% · won 57% · +11.2±5.7 vs own baseline
  2. FH crosscourt → BH crosscourt used 3.0% · won 52% · +5.7±3.6 vs own baseline
  3. FH down the line → FH crosscourt used 1.2% · won 55% · +8.8±5.4 vs own baseline
  4. FH crosscourt → FH down the line used 3.1% · won 52% · +5.2±3.5 vs own baseline
  5. BH crosscourt → FH crosscourt used 3.6% · won 51% · +4.3±3.3 vs own baseline

Discovered sequences

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

  1. Wide serve → BH through the middle return, mid → FH crosscourt used 0.2% · won 65% · +17.3±8.2 vs own baseline · +12.9 vs tour on the same sequence Disrupted by Novak Djokovic (4/6), Jannik Sinner (5/7)
  2. FH crosscourt → FH slice through the middle → FH down the line used 0.1% · won 67% · +18.7±9.5 vs own baseline · +15.5 vs tour on the same sequence
  3. FH down the line → BH slice crosscourt → FH inside-out used 0.3% · won 58% · +10.5±7.1 vs own baseline · +6.1 vs tour on the same sequence Disrupted by Milos Raonic (4/7), Roger Federer (13/23)
  4. FH crosscourt → FH through the middle → BH crosscourt used 0.5% · won 56% · +8.1±5.8 vs own baseline · +7.0 vs tour on the same sequence Disrupted by Novak Djokovic (6/22), Diego Schwartzman (5/13)
  5. BH crosscourt → BH slice crosscourt → FH inside-out used 0.3% · won 59% · +11.3±7.8 vs own baseline · +8.7 vs tour on the same sequence Disrupted by Roger Federer (4/6), Damir Dzumhur (6/8)
  6. FH crosscourt → FH through the middle → FH down the line used 0.6% · won 55% · +7.1±5.4 vs own baseline · +2.9 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

BH slice to their forehand · rally+3.9279
BH to their forehand · rally+2.51,847
FH slice to their forehand · rally+2.3185
BH volley to their forehand · rally+2.2143
FH slice to the middle · rally+2.1473

Most exposed to

BH to their forehand · return +1−1.7447
BH to the middle · serve +1−1.6525
FH to their forehand · return +1−1.3775
BH to their backhand · return−1.21,029
FH to the middle · return−1.02,221

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +1.79, Miomir Kecmanovic +1.78, Nishesh Basavareddy +1.51, Casper Ruud +1.49, Roberto Bautista Agut +1.49

Favourable matchups

Miomir Kecmanovic +1.79, Pedro Martinez +1.72, Fabian Marozsan +1.71, Roberto Carballes Baena +1.59, Roberto Bautista Agut +1.58

Active players who are best at the shot in the top weakness: Rafael Nadal, Adrian Mannarino, Yoshihito Nishioka, Learner Tien, Casper Ruud

Tactical fingerprint

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

Through the middle29%
T serves · deuce52%
Avg rally length4.4
Wide serves · ad53%
Run-around forehands22%
T serves · ad41%
1st serve in62%
Deep returns28%
Forehand share53%
Drop shots / shot1.4%
Chipped returns14%
Serve & volley4%
BH down the line17%
Wide serves · deuce40%
Unforced errors / shot8.6%
Backhand slice12%
FH down the line27%
Point-ending shots19.7%
Points at net7%

Plays most like

  1. Taylor Fritz 2016–2026 plan v
  2. Miomir Kecmanovic 2019–2026 plan v
  3. Marcos Giron 2018–2026 plan v
  4. Jannik Sinner 2013–2026 plan v
  5. Andreas Seppi 2008–2021 plan v
  6. Mackenzie Mcdonald 2015–2025 plan v
  7. Arthur Cazaux 2020–2025 plan v
  8. Daniel Elahi Galan 2020–2025 plan v

Closest from another era

  1. Michael Chang 1989–1998
  2. Magnus Norman 2000–2001
  3. Marcelo Rios 1995–2001

Charted matches