WTA · Right-handed · 5 charted matches · 2016–2021
Richel Hogenkamp
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 2,491 shots.
Shot expected value
The share of points Richel Hogenkamp 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 · 201 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH crosscourt | 29% | 41.2%±9.1 | 47.6% |
| BH slice crosscourt | 20% | 38.5%±10.3 | 40.4% |
| BH slice through the middle | 19% | 38.8%±10.4 | 34.4% |
| BH through the middle | 15% | 39.3%±11.4 | 43.3% |
| BH down the line | 11% | 50.8%±12.7 | 46.8% |
Rally, shots 5–8: drive to your middle
position worth 50% to the average player · 119 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 20% | 51.2%±12.4 | 52.7% |
| FH down the line | 19% | 47.5%±12.5 | 52.2% |
| BH crosscourt | 16% | 51.8%±13.2 | 50.9% |
| BH slice through the middle | 13% | 49.9%±13.7 | 44.8% |
| FH through the middle | 13% | 49.0%±13.9 | 45.8% |
| BH slice crosscourt | 10% | 43.4%±14.4 | 49.5% |
Rally, shots 5–8: drive to your forehand side
position worth 43% to the average player · 104 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 41% | 51.3%±10.4 | 46.7% |
| FH through the middle | 27% | 44.3%±11.8 | 41.3% |
| FH down the line | 22% | 41.8%±12.4 | 44.9% |
Long rally, 9+: drive to your backhand side
position worth 44% to the average player · 75 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH slice crosscourt | 25% | 35.2%±12.6 | 38.7% |
| BH slice through the middle | 24% | 46.6%±13.3 | 33.4% |
| BH crosscourt | 23% | 47.5%±13.5 | 47.9% |
| BH down the line | 15% | 39.8%±14.5 | 46.7% |
| BH through the middle | 13% | 51.8%±15.0 | 42.7% |
Serve under pressure
Pressure predictability index +5 How much less varied Richel Hogenkamp's first-serve direction gets on break points. Positive means easier to read. Based on 51 break-point first serves.
Deuce court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 56% | 46% ▼ | 59% / 66% |
| Body | 13% | 8% | 61% / 57% |
| T | 31% | 46% ▲ | 63% / 68% |
210 normal · 13 break-point 1st serves
Ad court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 53% | 53% | 65% / 66% |
| Body | 17% | 11% | 57% / 56% |
| T | 30% | 37% | 57% / 64% |
169 normal · 38 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 | 55% | 50.6%±6.6 n=123 | 65% ▲ |
| Body | 13% | 57.2%±10.7 n=28 | 3% ▼ |
| T | 32% | 45.7%±8.1 n=72 | 32% |
Consistent with an optimal mix (p = 0.16).
Optimal mix: ±0.0 per 100 first serves.
Ad court
| 1st serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 53% | 59.1%±6.8 n=110 | 68% ▲ |
| Body | 16% | 52.5%±10.3 n=33 | 1% ▼ |
| T | 31% | 56.9%±8.4 n=64 | 31% |
Consistent with an optimal mix (p = 0.52).
Optimal mix: +0.7 per 100 first serves.
Exploitability 0.36 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: −4.6±6.4 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. (134 repeats, 286 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 | 32 | 45% | +1.5±10.4 | |
| 1st | Ad court | T | 50 | 41% | +5.3±9.0 | |
| 1st | Ad court | Wide | 63 | 33% | −1.8±8.0 | |
| 1st | Deuce court | Body | 27 | 36% | −6.1±10.5 | |
| 1st | Deuce court | T | 46 | 31% | −1.0±8.7 | |
| 1st | Deuce court | Wide | 72 | 29% | −5.4±7.4 | |
| 2nd | Ad court | Body | 33 | 58% | +2.9±10.2 | |
| 2nd | Ad court | T | 9 | 50% | −5.0±13.2 | |
| 2nd | Ad court | Wide | 38 | 55% | +1.0±9.9 | |
| 2nd | Deuce court | Body | 38 | 49% | −5.4±10.0 | |
| 2nd | Deuce court | T | 20 | 64% | +7.6±11.2 | |
| 2nd | Deuce court | Wide | 35 | 63% | +9.5±9.8 |
Signature patterns
Recurring sequences that win more than Richel Hogenkamp's own baseline, ranked by edge weighted by how often they're used.
Serve → +1
- Wide serve (deuce court) → FH down the line used 10.7% · won 58% · −0.7±11.5 vs own baseline
Return
- Not enough data
Rally, consecutive own shots
- Not enough data
Discovered sequences
Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Richel Hogenkamp wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.
- FH crosscourt → FH crosscourt → FH crosscourt used 1.9% · won 43% · −3.8±11.8 vs own baseline · −9.1 vs tour on the same sequence Disrupted by Svetlana Kuznetsova (4/8), Valeria Bhunu (4/6)
- BH crosscourt → BH crosscourt → BH crosscourt used 1.8% · won 43% · −4.1±12.0 vs own baseline · −10.5 vs tour on the same sequence Disrupted by Svetlana Kuznetsova (6/18)
- FH down the line → BH crosscourt → BH crosscourt used 1.6% · won 43% · −4.5±12.3 vs own baseline · −11.5 vs tour on the same sequence Disrupted by Svetlana Kuznetsova (4/12)
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 1st serve · deuce court | +0.4 | 123 |
| FH to their forehand · rally | −1.3 | 129 |
Most exposed to
| BH to their backhand · rally | −0.5 | 171 |
| FH to their backhand · rally | +1.5 | 142 |
| FH to their forehand · rally | +1.6 | 160 |
Active players who are best at the shot in the top weakness: Maja Chwalinska, Sara Sorribes Tormo, Yulia Putintseva, Elsa Jacquemot, Caroline Wozniacki
Charted matches
- Richel Hogenkamp v Valeria Bhunu W ITF Johannesburg F · Hard · 19 Sep 2021
- Donna Vekic v Richel Hogenkamp L US Open R128 · Hard · 27 Aug 2019
- Bianca Andreescu v Richel Hogenkamp L Fed Cup World Group II RR · Clay · 9 Feb 2019
- Kristina Mladenovic v Richel Hogenkamp L Fed Cup World Group SF RR · Clay · 16 Apr 2016
- Richel Hogenkamp v Svetlana Kuznetsova W Fed Cup World Group R1 RR · Hard · 7 Feb 2016