RallyIQ

ATP · Right-handed · 42 charted matches · 2018–2026

Marton Fucsovics

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 64.2% ±2.5 raw 60.4% · tour 63.4% · 3,708 points
Return points won 40.8% ±2.6 raw 38.2% · tour 36.6% · 3,827 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 ±0.08 better than 36% of ATP · raw −0.08
Shot selection −0.45 ±0.12 better than 13% of ATP · raw −0.46
Execution −0.38 ±0.31 better than 49% of ATP · raw −0.48
Tactical adaptability −0.06 first serves toward what's working, set to set · 42 matches
Adaptation speed +0.06 same, every two to three service games · per 100 first serves
Long-rally execution +0.02 ±0.41 shot 9 on v own earlier rally shots · 3,355 shots · better than 76% of ATP
Points left on the table 2.57 per 100 shots vs best direction · lower than 53% 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 21,697 shots.

Shot expected value

The share of points Marton Fucsovics 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 · 1,644 shots

OptionUsedWin %Tour
BH crosscourt 23% 48.5%±4.1 47.6%
BH through the middle 22% 40.3%±4.1 43.7%
BH slice crosscourt 18% 44.5%±4.6 42.5%
BH slice through the middle 10% 38.1%±5.9 35.1%
BH down the line 9% 42.2%±6.3 46.4%
FH inside-in 5% 57.7%±7.8 54.7%
FH inside-out 5% 43.1%±8.0 51.8%
BH slice down the line 5% 41.8%±8.2 37.1%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 1,133 shots

OptionUsedWin %Tour
BH slice crosscourt 26% 41.6%±4.6 42.1%
BH crosscourt 21% 44.9%±5.1 48.0%
BH through the middle 19% 44.6%±5.3 43.8%
BH slice through the middle 11% 34.7%±6.4 35.1%
BH down the line 8% 44.1%±8.0 46.5%
BH slice down the line 6% 40.2%±8.7 35.8%
FH inside-out 4% 55.7%±10.4 52.6%
FH inside-in 3% 49.8%±10.8 54.3%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 1,083 shots

OptionUsedWin %Tour
FH crosscourt 25% 49.7%±4.8 52.7%
FH down the line 21% 47.7%±5.2 51.5%
FH through the middle 17% 47.5%±5.7 47.0%
BH through the middle 13% 45.7%±6.6 46.8%
BH crosscourt 7% 44.9%±8.6 49.1%
BH down the line 5% 33.3%±9.2 48.3%
BH slice through the middle 4% 36.3%±9.7 44.8%
BH slice crosscourt 3% 48.8%±11.6 47.0%

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

position worth 44% to the average player · 957 shots

OptionUsedWin %Tour
FH crosscourt 38% 46.0%±4.2 46.6%
FH through the middle 27% 41.0%±4.8 41.5%
FH down the line 22% 44.0%±5.3 44.7%
FH slice through the middle 6% 25.5%±7.9 24.5%
FH slice down the line 2% 23.6%±10.6 25.6%
FH down the line + approach 2% 81.7%±10.2 69.3%
FH slice crosscourt 2% 23.5%±11.2 30.9%

Serve under pressure

Pressure predictability index −4 How much less varied Marton Fucsovics's first-serve direction gets on break points. Positive means easier to read. Based on 332 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 39% 33% 69% / 73%
Body 13% 24% ▲ 68% / 63%
T 47% 43% 69% / 75%

1,846 normal · 72 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 54% 53% 68% / 73%
Body 13% 16% 63% / 63%
T 34% 32% 71% / 72%

1,514 normal · 260 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
Wide39% 60.6%±2.9 n=751 52% ▲
Body14% 60.3%±4.7 n=263 1% ▼
T47% 60.2%±2.6 n=904 47%

Consistent with an optimal mix (p = 0.99).
Optimal mix: +0.3 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide54% 60.5%±2.6 n=951 54%
Body13% 57.9%±5.0 n=233 0% ▼
T33% 61.3%±3.2 n=590 46% ▲

Consistent with an optimal mix (p = 0.58).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.33 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: −0.1±2.6 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. (1,483 repeats, 2,125 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 94 44% +7.4±7.3
1stAd courtT 462 27% −0.7±3.3
1stAd courtWide 555 31% +3.9±3.1
1stDeuce courtBody 141 44% +7.2±6.2
1stDeuce courtT 502 28% +3.4±3.2
1stDeuce courtWide 582 26% −1.2±2.9
2ndAd courtBody 259 51% +1.4±4.8
2ndAd courtT 107 57% +7.5±7.0
2ndAd courtWide 349 47% −1.8±4.2
2ndDeuce courtBody 307 54% +4.9±4.5
2ndDeuce courtT 315 53% +3.0±4.4
2ndDeuce courtWide 134 46% −2.1±6.4

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH crosscourt used 3.2% · won 62% · −1.1±6.8 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 3.0% · won 62% · −1.3±7.0 vs own baseline
  3. Body serve (deuce court) → FH crosscourt used 2.4% · won 62% · −1.5±7.6 vs own baseline
  4. Wide serve (ad court) → FH down the line used 2.4% · won 60% · −3.3±7.7 vs own baseline
  5. Wide serve (deuce court) → FH crosscourt used 2.1% · won 60% · −3.9±8.1 vs own baseline

Return

  1. vs T serve (deuce court) → BH through the middle, deep used 2.9% · won 56% · +16.6±7.5 vs own baseline
  2. vs T serve (ad court) → FH through the middle, deep used 2.4% · won 52% · +13.1±8.1 vs own baseline
  3. vs wide serve (ad court) → BH through the middle, deep used 2.8% · won 48% · +9.3±7.7 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, deep used 2.1% · won 49% · +10.0±8.5 vs own baseline
  5. vs wide serve (ad court) → BH through the middle, mid used 3.5% · won 45% · +6.2±6.9 vs own baseline

Rally, consecutive own shots

  1. FH through the middle → FH crosscourt used 2.5% · won 50% · +5.8±6.4 vs own baseline
  2. FH down the line → FH crosscourt used 1.4% · won 52% · +7.3±7.9 vs own baseline
  3. BH slice crosscourt → FH crosscourt used 1.8% · won 50% · +5.8±7.2 vs own baseline
  4. BH crosscourt → FH crosscourt used 1.5% · won 51% · +6.3±7.7 vs own baseline
  5. FH down the line → BH crosscourt used 1.4% · won 51% · +6.4±8.0 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH crosscourt → FH down the line + approach used 0.2% · won 64% · +17.9±12.0 vs own baseline · +18.2 vs tour on the same sequence
  2. T serve → BH through the middle return, mid → FH crosscourt used 0.2% · won 58% · +12.2±11.0 vs own baseline · +14.4 vs tour on the same sequence Disrupted by Daniil Medvedev (6/7)
  3. BH crosscourt → BH through the middle → FH crosscourt used 0.4% · won 55% · +8.9±9.8 vs own baseline · +6.9 vs tour on the same sequence Disrupted by Roger Federer (4/6), Stan Wawrinka (5/7)
  4. BH through the middle → BH through the middle → FH down the line used 0.4% · won 55% · +8.4±10.0 vs own baseline · +10.1 vs tour on the same sequence Disrupted by Daniil Medvedev (2/6)
  5. FH down the line → BH crosscourt → FH inside-in used 0.3% · won 54% · +7.7±10.1 vs own baseline · +3.5 vs tour on the same sequence Disrupted by Daniil Medvedev (4/8)
  6. Body serve → BH crosscourt return, mid → BH crosscourt used 0.2% · won 57% · +10.6±12.2 vs own baseline · +20.8 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

Wide 2nd serve · deuce court+1.9239
BH to the middle · return+1.8870
FH to the middle · serve +1+1.6321
BH to the middle · serve +1+1.5262
FH to the middle · return+1.5754

Most exposed to

FH to their forehand · return−2.1222
BH to their backhand · serve +1−0.8504
FH to the middle · rally−0.8898
BH to the middle · return−0.7851
Wide 2nd serve · ad court−0.6349

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Miomir Kecmanovic +0.68, Rafael Nadal +0.49, Nishesh Basavareddy +0.48, Casper Ruud +0.45, Pedro Martinez +0.41

Favourable matchups

Miomir Kecmanovic +1.24, Fabian Marozsan +1.17, Roberto Carballes Baena +1.12, Jenson Brooksby +1.07, Roberto Bautista Agut +1.05

Active players who are best at the shot in the top weakness: Tomas Machac, Andrey Rublev, Alexei Popyrin, Daniil Medvedev, Novak Djokovic

Tactical fingerprint

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

Backhand slice40%
Through the middle30%
Avg rally length4.6
Deep returns33%
Run-around forehands26%
Wide serves · ad54%
T serves · deuce47%
Forehand share54%
Chipped returns16%
Drop shots / shot1.4%
BH down the line19%
Serve & volley3%
Points at net10%
Unforced errors / shot9.2%
FH down the line29%
Wide serves · deuce39%
Point-ending shots19.8%
1st serve in58%
T serves · ad33%

Plays most like

  1. Marcos Giron 2018–2026 plan v
  2. Robin Haase 2012–2024 plan v
  3. Gael Monfils 2005–2026 plan v
  4. Dominic Thiem 2011–2024 plan v
  5. Guillermo Garcia Lopez 2015–2019 plan v
  6. Lorenzo Musetti 2019–2026 plan v
  7. Philipp Kohlschreiber 2008–2019 plan v
  8. Radu Albot 2016–2024 plan v

Closest from another era

  1. Nicolas Massu 2000–2009
  2. Gaston Gaudio 2002–2005
  3. Sebastien Grosjean 1999–2005

Charted matches