WTA · Right-handed · 23 charted matches · 2009–2020
Julia Goerges
Archetype: Runs around the backhand · Forehand-dominant
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 7,047 shots.
Shot expected value
The share of points Julia Goerges 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 45% to the average player · 395 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH crosscourt | 38% | 45.9%±6.3 | 47.6% |
| BH through the middle | 24% | 40.4%±7.6 | 43.3% |
| BH down the line | 21% | 44.9%±8.1 | 46.8% |
| BH slice crosscourt | 4% | 38.1%±13.1 | 40.4% |
| FH inside-out | 3% | 50.0%±14.3 | 52.5% |
| FH inside-in | 3% | 53.5%±14.5 | 55.6% |
| BH slice through the middle | 3% | 38.3%±14.4 | 34.4% |
Rally, shots 5–8: drive to your forehand side
position worth 43% to the average player · 300 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 52% | 46.5%±6.2 | 46.7% |
| FH down the line | 26% | 52.5%±8.3 | 44.9% |
| FH through the middle | 10% | 42.5%±11.5 | 41.3% |
| FH slice through the middle | 5% | 23.1%±11.9 | 29.2% |
| FH down the line + approach | 4% | 64.8%±14.1 | 65.4% |
Rally, shots 5–8: drive to your middle
position worth 50% to the average player · 292 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 30% | 58.5%±7.8 | 52.7% |
| FH down the line | 27% | 50.5%±8.3 | 52.2% |
| BH through the middle | 12% | 52.3%±11.2 | 46.2% |
| FH through the middle | 9% | 45.0%±11.9 | 45.8% |
| BH crosscourt | 7% | 38.9%±12.8 | 50.9% |
| BH down the line | 6% | 47.4%±13.3 | 50.0% |
| FH down the line + approach | 5% | 63.9%±13.6 | 68.6% |
Return +1: drive to your backhand side
position worth 44% to the average player · 263 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH crosscourt | 30% | 54.7%±8.3 | 47.8% |
| BH through the middle | 29% | 46.5%±8.4 | 43.0% |
| BH down the line | 22% | 42.6%±9.2 | 46.2% |
| BH slice through the middle | 6% | 36.9%±13.0 | 33.2% |
| BH slice crosscourt | 5% | 40.9%±13.9 | 39.6% |
| FH inside-in | 4% | 47.1%±15.0 | 55.6% |
| BH down the line + approach | 4% | 69.7%±13.8 | 64.5% |
Serve under pressure
Pressure predictability index ±0 How much less varied Julia Goerges's first-serve direction gets on break points. Positive means easier to read. Based on 161 break-point first serves.
Deuce court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 47% | 38% ▼ | 70% / 66% |
| Body | 16% | 22% | 56% / 57% |
| T | 36% | 41% | 72% / 68% |
809 normal · 37 break-point 1st serves
Ad court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 39% | 38% | 72% / 66% |
| Body | 14% | 13% | 54% / 56% |
| T | 47% | 49% | 71% / 64% |
661 normal · 124 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. A direction loses 0.19 points per 100 serves for every 10 points of habitual usage, measured from WTA 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 | 47% | 64.2%±3.8 n=398 | 62% ▲ |
| Body | 16% | 54.8%±6.3 n=138 | 1% ▼ |
| T | 37% | 62.3%±4.3 n=310 | 37% |
Consistent with an optimal mix (p = 0.06).
Optimal mix: +1.1 per 100 first serves.
Ad court
| 1st serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 38% | 66.0%±4.3 n=302 | 54% ▲ |
| Body | 14% | 55.3%±6.9 n=110 | 0% ▼ |
| T | 48% | 62.3%±4.0 n=373 | 46% ▼ |
Off equilibrium (p = 0.037): serve wide more. Gap 3.3 points per 100 first serves.
Optimal mix: +1.2 per 100 first serves.
Exploitability 1.13 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of WTA servers. Tested on matches they weren't fitted on, WTA mixes picked this way win 0.42 per 100 first serves on average.
Repeating the previous direction to the same court: +3.4±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. (523 repeats, 1,062 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 | 138 | 47% | +2.6±6.3 | |
| 1st | Ad court | T | 152 | 43% | +7.1±6.0 | |
| 1st | Ad court | Wide | 208 | 30% | −4.1±4.9 | |
| 1st | Deuce court | Body | 147 | 41% | −1.5±6.1 | |
| 1st | Deuce court | T | 230 | 29% | −3.4±4.6 | |
| 1st | Deuce court | Wide | 177 | 34% | −0.1±5.4 | |
| 2nd | Ad court | Body | 148 | 68% | +13.2±5.7 | |
| 2nd | Ad court | T | 44 | 62% | +6.5±9.3 | |
| 2nd | Ad court | Wide | 114 | 45% | −8.4±6.8 | |
| 2nd | Deuce court | Body | 163 | 48% | −6.6±5.9 | |
| 2nd | Deuce court | T | 106 | 51% | −4.7±7.1 | |
| 2nd | Deuce court | Wide | 45 | 50% | −4.3±9.5 |
Signature patterns
Recurring sequences that win more than Julia Goerges's own baseline, ranked by edge weighted by how often they're used.
Serve → +1
- Wide serve (deuce court) → FH down the line + approach used 2.1% · won 73% · +7.4±9.7 vs own baseline
- T serve (deuce court) → FH crosscourt used 3.7% · won 65% · −0.8±8.8 vs own baseline
- Body serve (deuce court) → FH crosscourt used 2.1% · won 63% · −3.1±10.5 vs own baseline
- T serve (ad court) → FH crosscourt used 3.0% · won 62% · −3.9±9.6 vs own baseline
- Wide serve (ad court) → FH crosscourt used 2.8% · won 62% · −4.1±9.8 vs own baseline
Return
- vs body serve (ad court) → FH down the line, mid used 2.6% · won 59% · +17.0±10.7 vs own baseline
- vs wide serve (ad court) → BH through the middle, deep used 3.2% · won 56% · +14.5±10.3 vs own baseline
- vs wide serve (deuce court) → FH crosscourt, mid used 2.1% · won 53% · +11.1±11.4 vs own baseline
- vs T serve (ad court) → FH through the middle, mid used 2.0% · won 50% · +8.2±11.6 vs own baseline
- vs T serve (deuce court) → BH down the line, deep used 2.1% · won 47% · +5.3±11.4 vs own baseline
Rally, consecutive own shots
- FH crosscourt → FH down the line used 9.6% · won 55% · +4.1±8.1 vs own baseline
- FH crosscourt → FH crosscourt used 6.3% · won 56% · +4.9±9.4 vs own baseline
- BH crosscourt → FH down the line used 4.2% · won 55% · +3.8±10.7 vs own baseline
- BH through the middle → FH down the line used 3.0% · won 53% · +2.6±11.6 vs own baseline
- BH through the middle → BH crosscourt used 6.0% · won 52% · +0.9±9.6 vs own baseline
Discovered sequences
Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Julia Goerges wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.
- FH crosscourt → FH crosscourt → FH down the line used 1.4% · won 59% · +9.1±10.0 vs own baseline · +17.3 vs tour on the same sequence Disrupted by Agnieszka Radwanska (3/7), Caroline Wozniacki (8/12)
- BH crosscourt → BH through the middle → FH crosscourt used 1.0% · won 58% · +7.4±11.2 vs own baseline · +10.4 vs tour on the same sequence
- FH crosscourt → FH through the middle → FH crosscourt used 0.9% · won 57% · +6.9±11.5 vs own baseline · +8.7 vs tour on the same sequence Disrupted by Caroline Wozniacki (3/6)
- BH crosscourt → BH through the middle → FH down the line used 0.7% · won 58% · +7.9±12.3 vs own baseline · +15.1 vs tour on the same sequence
- BH through the middle → FH down the line → BH crosscourt used 1.0% · won 52% · +1.7±11.1 vs own baseline · +7.4 vs tour on the same sequence Disrupted by Kiki Bertens (4/8), Lesia Tsurenko (4/6)
- FH down the line → BH crosscourt → BH crosscourt used 0.5% · won 51% · +1.2±13.0 vs own baseline · +4.9 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
| Wide 2nd serve · ad court | +2.7 | 151 |
| FH to their backhand · serve +1 | +2.2 | 265 |
| T 1st serve · ad court | +1.3 | 352 |
| FH to their forehand · serve +1 | +1.2 | 240 |
| BH to their backhand · serve +1 | +1.1 | 142 |
Most exposed to
| FH to their forehand · return | −2.4 | 141 |
| FH to their backhand · return | −2.0 | 122 |
| FH to their forehand · rally | −1.1 | 236 |
| BH to the middle · rally | −0.9 | 153 |
| Body 2nd serve · deuce court | −0.6 | 146 |
Active players who are best at the shot in the top weakness: Caroline Wozniacki, Su Wei Hsieh, Anhelina Kalinina, Ashlyn Krueger, Katie Boulter
Tactical fingerprint
Each bar shows how far a style trait is from the WTA average, in standard deviations.
| Point-ending shots | 37.6% | |
| Unforced errors / shot | 15.4% | |
| FH down the line | 38% | |
| BH down the line | 28% | |
| Run-around forehands | 15% | |
| Forehand share | 58% | |
| T serves · ad | 48% | |
| Points at net | 11% | |
| Wide serves · deuce | 47% | |
| Drop shots / shot | 2.1% | |
| Deep returns | 35% | |
| T serves · deuce | 37% | |
| Chipped returns | 10% | |
| Serve & volley | 0% | |
| Wide serves · ad | 38% | |
| Backhand slice | 8% | |
| 1st serve in | 58% | |
| Avg rally length | 3.3 | |
| Through the middle | 21% |
Plays most like
- Madison Keys 2014–2026 plan v
- Daniela Hantuchova 2002–2015 plan v
- Alycia Parks 2021–2026 plan v
- Dayana Yastremska 2013–2026 plan v
- Sabine Lisicki 2009–2022 plan v
- Anastasia Pavlyuchenkova 2014–2026 plan v
- Ana Ivanovic 2007–2016 plan v
- Amanda Anisimova 2017–2026 plan v
Closest from another era
- Mary Pierce 1994–2005
- Monica Seles 1990–2003
- Jennifer Capriati 1990–2002
Charted matches
- Julia Goerges v Laura Siegemund L Roland Garros R64 · Clay · 1 Oct 2020
- Alison Riske Amritraj v Julia Goerges W Roland Garros R128 · Clay · 29 Sep 2020
- Caroline Wozniacki v Julia Goerges L Auckland QF · Hard · 10 Jan 2020
- Julia Goerges v Kiki Bertens W US Open R32 · Hard · 31 Aug 2019
- Francesca Di Lorenzo v Julia Goerges W US Open R64 · Hard · 29 Aug 2019
- Serena Williams v Julia Goerges L Wimbledon R32 · Grass · 6 Jul 2019
- Vera Zvonareva v Julia Goerges L St Petersburg R16 · Hard · 30 Jan 2019
- Eugenie Bouchard v Julia Goerges W Auckland QF · Hard · 3 Jan 2019
- Kiki Bertens v Julia Goerges W Wimbledon QF · Grass · 10 Jul 2018
- Naomi Osaka v Julia Goerges Charleston R16 · Clay · 5 Apr 2018
- Julia Goerges v Lesia Tsurenko W Moscow QF · Hard · 19 Oct 2017
- Julia Goerges v Polina Monova W Moscow R32 · Hard · 17 Oct 2017