Game plan
Qiang Wang v Paula Badosa
Every number combines what Qiang Wang does well with what Paula Badosa allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective
Forecast
Each player's serve and return strength is fitted against every opponent they were charted against, so a record built on weak opponents counts for less. At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers. The result is then nudged by Qiang Wang's record against Paula Badosa's tactical lookalikes and in their charted head-to-heads (lookalikes: −1.2 on serve, −5.4 on return vs expectation (111 points)). A game-by-game Markov chain turns point odds into match odds; the 90% range covers the uncertainty in the two strengths, not the nudges. Charted matches lean toward big events, so treat this as a scouting estimate, not a betting line.
Head to head, per 100 shots
| Career | Qiang | Paula |
|---|---|---|
| Direction choice | +0.04 ±0.17 better than 61% | −0.24 ±0.05 better than 13% |
| Shot selection | +0.37 ±0.16 better than 87% | +0.29 ±0.09 better than 77% |
| Execution | +0.03 ±0.80 better than 62% | +0.75 ±0.35 better than 86% |
| Points left on the table | 2.24 ±0.25 lower than 90% | 2.83 ±0.08 lower than 22% |
Each player's career against an average tour player in the same position, adjusted for opponent strength, with a 90% margin (shots clustered by match). Points left on the table is the gap to the best-value direction for the same stroke, so lower is better. Percentiles are within each player's own tour. A side is highlighted only when the gap is larger than the margin on the difference.
Serve plan
The share of points the server wins when a first serve lands in that direction (hover a rate for its 90% interval; ± is the 90% margin). "Matchup" combines the server's rate with how this returner handles that serve. "Optimal" is the mix that wins most against this returner once they start reading a habit, at the response measured across the tour, and only within the range servers' habits actually vary. The gain over the current mix is how exploitable that mix is.
Qiang Wang serving
Deuce court
| 1st serve | Now | Qiang wins | v Paula | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 36% | 61% | 67% | 61.9%±7.9 | 51% ▲ |
| Body | 24% | 59% | 54% | 56.0%±9.4 | 9% ▼ |
| T | 40% | 65% | 65% | 61.2%±8.3 | 40% |
Optimal v Paula Badosa: +0.4±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.7 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Qiang wins | v Paula | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 29% | 60% | 62% | 55.7%±9.5 | 44% ▲ |
| Body | 20% | 50% | 55% | 48.8%±10.6 | 19% |
| T | 52% | 52% | 62% | 48.8%±7.6 | 37% ▼ |
Optimal v Paula Badosa: +0.6±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.9 per 100 first serves in before the returner adjusts.
Paula Badosa serving
Deuce court
| 1st serve | Now | Paula wins | v Qiang | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 47% | 67% | 61% | 62.0%±7.2 | 48% |
| Body | 19% | 62% | 55% | 58.9%±9.7 | 4% ▼ |
| T | 33% | 73% | 71% | 76.6%±7.0 | 48% ▲ |
Optimal v Qiang Wang: +1.0±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +10.3 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Paula wins | v Qiang | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 26% | 67% | 64% | 65.6%±8.0 | 26% |
| Body | 16% | 53% | 63% | 59.8%±10.6 | 1% ▼ |
| T | 58% | 72% | 69% | 76.0%±6.3 | 73% ▲ |
Optimal v Qiang Wang: +1.5±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +5.3 per 100 first serves in before the returner adjusts.
Return plan
Value of each return, in points per 100 returns against an average return of the same serve (direction, court, surface): the tour's result with that return, the returner's own edge with it, and what this server gives up when it comes back to that side. Returns with no charted direction are left out, so values compare with each other rather than with zero. Depth isn't a choice here: missed returns have no depth. Serve quality isn't charted, so a block through the middle partly reflects the serve that forced it.
Qiang Wang returning
1st serve to the forehand
| Return | Now | Tour | Own | v Paula | Value |
|---|---|---|---|---|---|
| FH through the middle | 56% | +4.2 | +2.6 | +1.2 | +7.9±2.4 |
| FH down the line | 25% | +1.5 | +2.7 | −0.5 | +3.7±4.3 |
| FH crosscourt | 18% | +5.3 | −0.1 | −1.4 | +3.8±4.0 |
Lean FH through the middle: +1.8±1.7 per 100 returns v the current mix (208 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Paula | Value |
|---|---|---|---|---|---|
| BH crosscourt | 41% | +7.7 | +1.0 | −0.1 | +8.6±3.4 |
| BH through the middle | 39% | +6.0 | −0.9 | −0.9 | +4.3±2.5 |
| BH down the line | 9% | +2.2 | −1.3 | −2.7 | −1.9±4.1 |
| BH slice crosscourt | 6% | −4.2 | +0.3 | −0.8 | −4.7±2.6 |
| BH slice through the middle | 6% | −6.2 | ±0.0 | −0.9 | −7.1±2.2 |
Lean BH crosscourt: +4.2±2.2 per 100 returns v the current mix (161 returns charted)
2nd serve to the backhand
| Return | Now | Tour | Own | v Paula | Value |
|---|---|---|---|---|---|
| BH crosscourt | 45% | +1.5 | +0.6 | −0.3 | +1.7±3.4 |
| BH through the middle | 38% | −2.6 | +1.6 | +2.0 | +1.0±2.4 |
| BH down the line | 16% | −0.5 | +1.2 | −1.7 | −1.1±4.7 |
Lean BH crosscourt: +0.8±2.2 per 100 returns v the current mix (104 returns charted, inside the 90% margin)
Paula Badosa returning
1st serve to the forehand
| Return | Now | Tour | Own | v Qiang | Value |
|---|---|---|---|---|---|
| FH through the middle | 45% | +4.2 | +0.5 | +0.1 | +4.8±2.5 |
| FH down the line | 21% | +1.5 | +1.4 | +1.6 | +4.5±4.4 |
| FH crosscourt | 15% | +5.3 | +0.1 | +4.1 | +9.5±4.2 |
| FH slice through the middle | 12% | −6.7 | −0.7 | −0.3 | −7.7±2.3 |
| FH slice crosscourt | 4% | −6.6 | +1.1 | −0.7 | −6.3±2.3 |
Lean FH crosscourt: +6.3±3.9 per 100 returns v the current mix (726 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Qiang | Value |
|---|---|---|---|---|---|
| BH through the middle | 49% | +6.0 | +1.3 | −1.0 | +6.3±2.4 |
| BH crosscourt | 24% | +7.7 | +1.9 | +3.4 | +13.0±3.4 |
| BH down the line | 16% | +2.2 | +4.0 | −0.3 | +5.9±4.3 |
| BH slice through the middle | 7% | −6.2 | −0.4 | +0.3 | −6.4±2.2 |
| BH slice crosscourt | 2% | −4.2 | +0.5 | −0.4 | −4.0±2.3 |
Lean BH crosscourt: +6.6±2.9 per 100 returns v the current mix (767 returns charted)
2nd serve to the forehand
| Return | Now | Tour | Own | v Qiang | Value |
|---|---|---|---|---|---|
| FH through the middle | 54% | −3.2 | +1.0 | −0.3 | −2.4±3.0 |
| FH crosscourt | 30% | +0.5 | −0.8 | +2.3 | +2.0±4.5 |
| FH down the line | 13% | −0.6 | −2.2 | +2.7 | −0.1±5.1 |
| FH slice through the middle | 3% | −15.2 | +0.6 | ±0.0 | −14.6±1.2 |
Lean FH crosscourt: +3.2±3.6 per 100 returns v the current mix (217 returns charted, inside the 90% margin)
2nd serve to the backhand
| Return | Now | Tour | Own | v Qiang | Value |
|---|---|---|---|---|---|
| BH through the middle | 45% | −2.6 | +2.0 | +1.0 | +0.4±2.5 |
| BH crosscourt | 38% | +1.5 | +3.3 | +1.9 | +6.7±3.4 |
| BH down the line | 8% | −0.5 | +0.7 | +6.5 | +6.6±5.2 |
| FH through the middle | 4% | −2.7 | −1.1 | −0.3 | −4.0±2.5 |
| FH inside-out | 3% | +1.4 | +0.8 | +2.7 | +4.8±3.9 |
Lean BH crosscourt: +3.4±2.4 per 100 returns v the current mix (450 returns charted)
Rally plan
Edge, in points per 100 shots: the hitter's skill with the shot (own) plus how much the receiver usually gives up against it (theirs), both measured against the tour average on hard. Each player's hard record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.
Qiang Wang
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to the middle · return | +4.9±2.7 | +4.1 | +0.9 |
| FH to their backhand · serve +1 | +4.3±4.6 | +1.4 | +2.8 |
| FH to their backhand · return | +2.9±5.4 | +4.1 | −1.2 |
| FH to the middle · serve +1 | +2.4±3.0 | +1.9 | +0.5 |
| BH to the middle · serve +1 | +1.2±3.2 | ±0.0 | +1.2 |
| FH to their forehand · rally | +0.7±2.4 | +0.2 | +0.6 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to their forehand · return | −4.8±5.3 | −2.1 | −2.7 |
| BH to their backhand · return +1 | −2.9±3.9 | −1.8 | −1.1 |
| BH to their forehand · rally | −2.8±4.5 | −4.5 | +1.8 |
| BH to the middle · rally | −0.9±2.1 | −1.3 | +0.4 |
| BH to their backhand · serve +1 | −0.7±4.1 | ±0.0 | −0.6 |
Paula Badosa
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their forehand · return | +10.7±5.5 | +3.9 | +6.8 |
| BH to their backhand · return | +9.2±4.2 | +3.9 | +5.3 |
| FH to their backhand · serve +1 | +7.4±4.5 | +3.2 | +4.2 |
| BH to their backhand · serve +1 | +5.6±4.2 | +0.7 | +4.8 |
| FH to their forehand · return | +5.1±5.0 | −0.8 | +5.9 |
| FH to their forehand · return +1 | +4.3±4.7 | +3.7 | +0.6 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their forehand · serve +1 | −1.1±5.9 | −2.5 | +1.3 |
| FH to the middle · return | −0.4±2.7 | −0.3 | −0.1 |
| FH to the middle · serve +1 | −0.2±3.4 | +0.6 | −0.8 |
| BH to the middle · return | +0.6±2.5 | +0.5 | +0.1 |
| FH to their forehand · rally | +0.7±2.6 | +0.3 | +0.3 |
Against Paula Badosa-like opponents
| Qiang Wang v | Matches | Serve pts won | Return pts won |
|---|---|---|---|
| All charted opponents | – | 50.4% | 40.5% |
| Players most similar to Paula Badosa | 1 | 50.0% | 32.7% |
Similar by tactical fingerprint: Coco Gauff, Marie Bouzkova, Kimberly Birrell, Jaqueline Cristian, Anna Bondar, Lin Zhu, Jennifer Brady, Carla Suarez Navarro, Louisa Chirico. When two players have rarely met, their records against these lookalikes fill the gap.