ATP · Right-handed · 49 charted matches · 2000–2010
Fernando Gonzalez
Archetype: High-risk · Runs around the backhand
Against an average opponent
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
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 22,210 shots.
Shot expected value
The share of points Fernando Gonzalez 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 · 1,414 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH slice crosscourt | 26% | 47.0%±4.2 | 42.5% |
| BH crosscourt | 16% | 54.6%±5.3 | 47.6% |
| BH down the line | 12% | 43.0%±5.9 | 46.4% |
| BH through the middle | 12% | 35.2%±5.8 | 43.7% |
| FH inside-out | 11% | 51.4%±6.3 | 51.8% |
| BH slice through the middle | 10% | 43.1%±6.4 | 35.1% |
| FH inside-in | 6% | 55.5%±8.2 | 54.7% |
| BH slice down the line | 3% | 37.6%±9.9 | 37.1% |
Rally, shots 5–8: drive to your forehand side
position worth 44% to the average player · 765 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 48% | 40.7%±4.1 | 46.6% |
| FH down the line | 26% | 41.5%±5.5 | 44.7% |
| FH through the middle | 14% | 38.8%±7.1 | 41.5% |
| FH slice crosscourt | 4% | 30.5%±10.4 | 30.9% |
| FH slice through the middle | 4% | 24.3%±10.1 | 24.5% |
| FH down the line + approach | 2% | 66.3%±13.0 | 69.3% |
| FH slice down the line | 1% | 29.4%±13.5 | 25.6% |
Rally, shots 5–8: drive to your middle
position worth 51% to the average player · 748 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 31% | 52.4%±5.2 | 52.7% |
| FH down the line | 31% | 51.9%±5.2 | 51.5% |
| FH through the middle | 11% | 41.3%±7.9 | 47.0% |
| BH through the middle | 6% | 34.4%±9.7 | 46.8% |
| FH down the line + approach | 4% | 66.2%±10.7 | 70.5% |
| BH slice crosscourt | 4% | 42.5%±11.7 | 47.0% |
| BH crosscourt | 4% | 54.9%±11.9 | 49.1% |
| BH down the line | 4% | 50.3%±12.0 | 48.3% |
Return +1: drive to your backhand side
position worth 44% to the average player · 739 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH slice crosscourt | 32% | 42.4%±5.1 | 40.9% |
| BH crosscourt | 15% | 43.9%±7.1 | 46.9% |
| BH down the line | 15% | 48.7%±7.2 | 44.2% |
| BH slice through the middle | 13% | 38.9%±7.4 | 32.6% |
| BH through the middle | 13% | 47.9%±7.6 | 43.0% |
| FH inside-out | 6% | 53.0%±10.5 | 51.7% |
| FH inside-in | 3% | 43.8%±12.2 | 53.6% |
| BH slice down the line | 3% | 39.2%±12.7 | 33.3% |
Serve under pressure
Pressure predictability index +1 How much less varied Fernando Gonzalez's first-serve direction gets on break points. Positive means easier to read. Based on 387 break-point first serves.
Deuce court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 43% | 42% | 71% / 73% |
| Body | 11% | 7% | 64% / 63% |
| T | 47% | 52% | 81% / 75% |
2,370 normal · 91 break-point 1st serves
Ad court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 56% | 56% | 71% / 73% |
| Body | 5% | 5% | 63% / 63% |
| T | 39% | 39% | 73% / 72% |
1,931 normal · 296 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 serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 43% | 64.0%±2.4 n=1,052 | 40% ▼ |
| Body | 10% | 60.0%±4.8 n=255 | 0% ▼ |
| T | 47% | 67.1%±2.2 n=1,154 | 60% ▲ |
Off equilibrium (p = 0.033): serve T more. Gap 2.1 points per 100 first serves.
Optimal mix: +0.7 per 100 first serves.
Ad court
| 1st serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 56% | 60.8%±2.2 n=1,253 | 48% ▼ |
| Body | 5% | 64.6%±6.6 n=110 | 0% ▼ |
| T | 39% | 62.0%±2.7 n=864 | 52% ▲ |
Consistent with an optimal mix (p = 0.41).
Optimal mix: +0.2 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: −1.1±2.3 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. (1,847 repeats, 2,743 switches.)
Return by serve direction
Return points won against each serve direction, compared with the tour average.
| Serve | Court | Direction | Points | Won | vs tour | |
|---|---|---|---|---|---|---|
| 1st | Ad court | Body | 124 | 34% | −3.2±6.3 | |
| 1st | Ad court | T | 532 | 25% | −2.9±3.0 | |
| 1st | Ad court | Wide | 751 | 27% | −0.6±2.6 | |
| 1st | Deuce court | Body | 192 | 32% | −4.7±5.1 | |
| 1st | Deuce court | T | 733 | 30% | +4.5±2.7 | |
| 1st | Deuce court | Wide | 587 | 24% | −2.8±2.8 | |
| 2nd | Ad court | Body | 114 | 52% | +2.6±6.8 | |
| 2nd | Ad court | T | 188 | 46% | −3.0±5.6 | |
| 2nd | Ad court | Wide | 505 | 49% | +1.1±3.6 | |
| 2nd | Deuce court | Body | 233 | 49% | −0.1±5.1 | |
| 2nd | Deuce court | T | 413 | 49% | −0.7±3.9 | |
| 2nd | Deuce court | Wide | 225 | 50% | +2.3±5.2 |
Signature patterns
Recurring sequences that win more than Fernando Gonzalez's own baseline, ranked by edge weighted by how often they're used.
Serve → +1
- Wide serve (ad court) → FH inside-in used 2.4% · won 66% · −1.4±6.8 vs own baseline
- T serve (deuce court) → FH down the line used 3.3% · won 66% · −1.3±5.9 vs own baseline
- Wide serve (ad court) → FH crosscourt used 3.0% · won 63% · −4.4±6.3 vs own baseline
- Wide serve (ad court) → FH inside-out used 2.1% · won 62% · −5.8±7.3 vs own baseline
- T serve (deuce court) → FH crosscourt used 2.5% · won 60% · −7.3±6.9 vs own baseline
Return
- vs wide serve (ad court) → BH slice crosscourt, mid used 3.1% · won 49% · +11.7±6.9 vs own baseline
- vs wide serve (deuce court) → FH crosscourt, mid used 2.1% · won 48% · +11.2±8.0 vs own baseline
- vs wide serve (ad court) → BH crosscourt, mid used 2.6% · won 46% · +8.6±7.4 vs own baseline
- vs T serve (deuce court) → BH through the middle, mid used 2.1% · won 46% · +9.2±8.1 vs own baseline
- vs T serve (deuce court) → BH slice through the middle, deep used 2.1% · won 43% · +6.4±7.9 vs own baseline
Rally, consecutive own shots
- BH crosscourt → BH crosscourt used 1.8% · won 58% · +12.9±8.7 vs own baseline
- BH crosscourt → BH down the line used 1.9% · won 55% · +9.7±8.5 vs own baseline
- FH down the line → FH inside-out used 2.3% · won 53% · +7.7±8.0 vs own baseline
- FH inside-out → FH inside-in used 1.1% · won 56% · +10.3±10.2 vs own baseline
- FH down the line → FH down the line used 1.8% · won 52% · +7.1±8.8 vs own baseline
Discovered sequences
Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Fernando Gonzalez wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.
- BH crosscourt → BH crosscourt → BH crosscourt used 0.4% · won 65% · +17.0±9.4 vs own baseline · +26.6 vs tour on the same sequence Disrupted by Roger Federer (9/13)
- Wide serve → FH through the middle return, mid → FH down the line used 0.4% · won 65% · +17.0±9.6 vs own baseline · +19.7 vs tour on the same sequence Disrupted by Guillermo Coria (4/6)
- FH down the line → BH slice crosscourt → FH inside-in used 0.3% · won 64% · +15.6±10.4 vs own baseline · +16.1 vs tour on the same sequence Disrupted by Taylor Dent (5/8)
- Wide serve → BH crosscourt return, mid → FH inside-in used 0.5% · won 61% · +12.9±9.4 vs own baseline · +7.7 vs tour on the same sequence Disrupted by Andy Roddick (4/6), Roger Federer (6/6)
- FH down the line → BH slice crosscourt → FH inside-out used 0.7% · won 57% · +8.9±8.5 vs own baseline · +5.7 vs tour on the same sequence Disrupted by James Blake (5/9), Andy Roddick (4/6)
- Wide serve → BH crosscourt return, mid → FH inside-out used 0.3% · won 62% · +13.4±11.1 vs own baseline · +19.2 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 the middle · return | +4.2 | 498 |
| BH slice to their backhand · rally | +2.7 | 653 |
| BH slice to their backhand · return | +2.5 | 457 |
| BH slice to the middle · rally | +2.4 | 259 |
| BH to their backhand · return +1 | +2.2 | 228 |
Most exposed to
| T 2nd serve · ad court | −3.2 | 188 |
| BH to their forehand · return +1 | −2.7 | 170 |
| BH to their forehand · rally | −2.4 | 409 |
| BH to their forehand · serve +1 | −2.3 | 159 |
| BH slice to the middle · return | −1.9 | 321 |
Active players who are best at the shot in the top weakness: Giovanni Mpetshi Perricard, Roberto Bautista Agut, Taylor Fritz, Andrey Rublev, Sebastian Korda
Tactical fingerprint
Each bar shows how far a style trait is from the ATP average, in standard deviations.
| Chipped returns | 35% | |
| BH down the line | 31% | |
| Run-around forehands | 35% | |
| Backhand slice | 42% | |
| Forehand share | 58% | |
| FH down the line | 35% | |
| Wide serves · ad | 56% | |
| Point-ending shots | 27.8% | |
| Drop shots / shot | 2.1% | |
| T serves · deuce | 47% | |
| Unforced errors / shot | 10.3% | |
| 1st serve in | 61% | |
| T serves · ad | 39% | |
| Wide serves · deuce | 43% | |
| Deep returns | 26% | |
| Points at net | 10% | |
| Serve & volley | 2% | |
| Avg rally length | 3.7 | |
| Through the middle | 18% |
Plays most like
- Jo Wilfried Tsonga 2007–2022 plan v
- Steve Johnson 2015–2022 plan v
- Roger Federer 1998–2021 plan v
- Joao Fonseca 2024–2026 plan v
- Dominic Thiem 2011–2024 plan v
- Jeremy Chardy 2013–2023 plan v
- Alexei Popyrin 2019–2026 plan v
- Lorenzo Musetti 2019–2026 plan v
Closest from another era
- Joao Fonseca 2024–2026
- Alexei Popyrin 2019–2026
- Lorenzo Musetti 2019–2026
Charted matches
- Andy Roddick v Fernando Gonzalez L Australian Open R16 · Hard · 24 Jan 2010
- Juan Martin Del Potro v Fernando Gonzalez Paris Masters R16 · Hard · 13 Nov 2009
- Fernando Gonzalez v Nikolay Davydenko L Shanghai Masters R16 · Hard · 11 Oct 2009
- Marat Safin v Fernando Gonzalez L Beijing R32 · Hard · 8 Oct 2009
- Jo Wilfried Tsonga v Fernando Gonzalez W US Open R16 · Hard · 8 Sep 2009
- Fernando Gonzalez v Nicolas Massu W US Open R128 · Hard · 1 Sep 2009
- Fernando Gonzalez v Juan Martin Del Potro L Washington SF · Hard · 8 Aug 2009
- Fernando Gonzalez v Andy Murray W Roland Garros QF · Clay · 2 Jun 2009
- Victor Hanescu v Fernando Gonzalez W Roland Garros R16 · Clay · 31 May 2009
- Fernando Gonzalez v Rafael Nadal L Rome Masters SF · Clay · 2 May 2009
- Richard Gasquet v Fernando Gonzalez W Australian Open R32 · Hard · 24 Jan 2009
- Rafael Nadal v Fernando Gonzalez L Olympics F · Hard · 17 Aug 2008