WTA · Right-handed · 8 charted matches · 2013–2019
Johanna Larsson
Archetype: Ad-court slider · Avoids the wide serve
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 2,626 shots.
Shot expected value
The share of points Johanna Larsson 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 · 184 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH crosscourt | 34% | 38.0%±8.8 | 47.6% |
| BH through the middle | 30% | 32.9%±8.9 | 43.3% |
| BH slice through the middle | 10% | 25.3%±11.5 | 34.4% |
| BH slice crosscourt | 10% | 42.3%±13.2 | 40.4% |
Rally, shots 5–8: drive to your middle
position worth 50% to the average player · 175 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 29% | 45.1%±9.8 | 52.7% |
| FH through the middle | 26% | 33.6%±9.6 | 45.8% |
| BH through the middle | 21% | 42.5%±10.8 | 46.2% |
| FH down the line | 13% | 46.3%±12.7 | 52.2% |
| BH crosscourt | 8% | 35.8%±13.5 | 50.9% |
Rally, shots 5–8: drive to your forehand side
position worth 43% to the average player · 151 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 54% | 34.7%±7.8 | 46.7% |
| FH through the middle | 30% | 32.2%±9.5 | 41.3% |
| FH down the line | 10% | 48.5%±13.9 | 44.9% |
Long rally, 9+: drive to your backhand side
position worth 44% to the average player · 120 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH crosscourt | 31% | 36.1%±10.5 | 47.9% |
| BH through the middle | 26% | 28.5%±10.4 | 42.7% |
| BH down the line | 13% | 45.4%±13.7 | 46.7% |
| BH slice through the middle | 13% | 29.7%±12.5 | 33.4% |
| BH slice crosscourt | 13% | 36.4%±13.4 | 38.7% |
Serve under pressure
Pressure predictability index −4 How much less varied Johanna Larsson's first-serve direction gets on break points. Positive means easier to read. Based on 73 break-point first serves.
Deuce court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 46% | 25% ▼ | 59% / 66% |
| Body | 17% | 19% | 54% / 57% |
| T | 37% | 56% ▲ | 60% / 68% |
215 normal · 16 break-point 1st serves
Ad court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 53% | 47% | 54% / 66% |
| Body | 15% | 21% | 53% / 56% |
| T | 33% | 32% | 60% / 64% |
160 normal · 57 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 | 44% | 53.9%±7.1 n=102 | 59% ▲ |
| Body | 17% | 47.5%±9.8 n=40 | 2% ▼ |
| T | 39% | 46.6%±7.5 n=89 | 39% |
Consistent with an optimal mix (p = 0.34).
Optimal mix: +0.6 per 100 first serves.
Ad court
| 1st serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 51% | 49.0%±6.9 n=111 | 61% ▲ |
| Body | 17% | 44.8%±10.1 n=36 | 1% ▼ |
| T | 32% | 49.8%±8.2 n=70 | 38% ▲ |
Consistent with an optimal mix (p = 0.66).
Optimal mix: +0.5 per 100 first serves.
Exploitability 0.54 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: +0.8±8.7 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. (166 repeats, 266 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 | 30 | 42% | −1.9±10.5 | |
| 1st | Ad court | T | 55 | 30% | −5.3±8.2 | |
| 1st | Ad court | Wide | 60 | 35% | +0.4±8.3 | |
| 1st | Deuce court | Body | 22 | 32% | −10.3±10.7 | |
| 1st | Deuce court | T | 60 | 31% | −1.4±8.0 | |
| 1st | Deuce court | Wide | 66 | 28% | −5.7±7.6 | |
| 2nd | Ad court | Body | 29 | 47% | −8.4±10.7 | |
| 2nd | Ad court | T | 14 | 53% | −1.6±12.4 | |
| 2nd | Ad court | Wide | 32 | 57% | +3.0±10.4 | |
| 2nd | Deuce court | Body | 39 | 47% | −7.6±9.9 | |
| 2nd | Deuce court | T | 28 | 46% | −9.8±10.8 | |
| 2nd | Deuce court | Wide | 24 | 54% | +0.2±11.2 |
Signature patterns
Recurring sequences that win more than Johanna Larsson's own baseline, ranked by edge weighted by how often they're used.
Serve → +1
- Not enough data
Return
- Not enough data
Rally, consecutive own shots
- FH crosscourt → FH crosscourt used 8.4% · won 33% · +3.3±9.4 vs own baseline
- BH through the middle → FH crosscourt used 8.2% · won 32% · +2.2±9.4 vs own baseline
- FH through the middle → BH through the middle used 4.7% · won 32% · +1.9±10.9 vs own baseline
- FH crosscourt → BH through the middle used 6.5% · won 31% · +1.0±10.0 vs own baseline
- BH through the middle → FH through the middle used 6.1% · won 29% · −1.5±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 Johanna Larsson 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 1.3% · won 44% · +8.6±12.5 vs own baseline · +7.9 vs tour on the same sequence
- FH crosscourt → FH through the middle → BH through the middle used 1.2% · won 42% · +7.3±12.6 vs own baseline · +6.1 vs tour on the same sequence Disrupted by Mona Barthel (3/6), Kurumi Nara (3/6)
- BH crosscourt → BH through the middle → FH crosscourt used 1.1% · won 41% · +5.9±12.7 vs own baseline · −3.9 vs tour on the same sequence Disrupted by Kurumi Nara (2/6)
- BH crosscourt → BH crosscourt → BH through the middle used 1.3% · won 38% · +3.1±12.1 vs own baseline · −1.8 vs tour on the same sequence Disrupted by Kurumi Nara (2/8)
- FH crosscourt → FH crosscourt → FH crosscourt used 2.4% · won 37% · +1.9±10.3 vs own baseline · −10.0 vs tour on the same sequence Disrupted by Kurumi Nara (2/6), Agnieszka Radwanska (3/6)
- FH crosscourt → FH through the middle → FH through the middle used 1.2% · won 37% · +2.5±12.3 vs own baseline · −4.6 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 to the middle · rally | −0.3 | 143 |
| FH to their forehand · rally | −0.9 | 220 |
| BH to their backhand · rally | −1.4 | 143 |
| FH to the middle · rally | −1.8 | 153 |
Most exposed to
| FH to their forehand · rally | −2.9 | 203 |
| FH to their backhand · rally | +0.1 | 157 |
| FH to the middle · rally | +0.6 | 130 |
| BH to their backhand · rally | +0.8 | 185 |
Active players who are best at the shot in the top weakness: Linda Fruhvirtova, Maja Chwalinska, Sara Sorribes Tormo, Linda Klimovicova, Nadia Podoroska
Tactical fingerprint
Each bar shows how far a style trait is from the WTA average, in standard deviations.
| Through the middle | 38% | |
| Avg rally length | 4.8 | |
| Wide serves · ad | 51% | |
| Run-around forehands | 14% | |
| Wide serves · deuce | 44% | |
| Backhand slice | 22% | |
| 1st serve in | 63% | |
| T serves · deuce | 39% | |
| Points at net | 8% | |
| Chipped returns | 12% | |
| Forehand share | 54% | |
| Serve & volley | 1% | |
| Unforced errors / shot | 9.8% | |
| Drop shots / shot | 1.1% | |
| T serves · ad | 32% | |
| Deep returns | 29% | |
| BH down the line | 15% | |
| Point-ending shots | 17.0% | |
| FH down the line | 19% |
Plays most like
- Elina Svitolina 2013–2026 plan v
- Jil Teichmann 2017–2026 plan v
- Suzan Lamens 2021–2026 plan v
- Ana Bogdan 2019–2024 plan v
- Anna Lena Friedsam 2014–2023 plan v
- Arantxa Rus 2019–2026 plan v
- Andrea Petkovic 2010–2022 plan v
- Lucia Bronzetti 2021–2025 plan v
Closest from another era
- Jennifer Capriati 1990–2002
- Arantxa Sanchez Vicario 1988–2001
- Monica Seles 1990–2003
Charted matches
- Johanna Larsson v Kiki Bertens L s Hertogenbosch R32 · Grass · 11 Jun 2019
- Caroline Wozniacki v Johanna Larsson L Australian Open R64 · Hard · 16 Jan 2019
- Alize Cornet v Johanna Larsson L Hobart SF · Hard · 15 Jan 2016
- Jelena Ostapenko v Johanna Larsson L Auckland R32 · Hard · 4 Jan 2016
- Mona Barthel v Johanna Larsson W Bastad F · Clay · 19 Jul 2015
- Agnieszka Radwanska v Johanna Larsson L Australian Open R64 · Hard · 21 Jan 2015
- Kurumi Nara v Johanna Larsson L Hobart R16 · Hard · 13 Jan 2015
- Serena Williams v Johanna Larsson L Bastad F · Clay · 15 Jul 2013