Game plan
Yafan Wang v Emma Navarro
Every number combines what Yafan Wang does well with what Emma Navarro 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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Yafan Wang's record against Emma Navarro's tactical lookalikes and in their charted head-to-heads. 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 | Yafan | Emma |
|---|---|---|
| Direction choice | −0.09 ±0.14 better than 37% | −0.07 ±0.08 better than 40% |
| Shot selection | +0.23 ±0.17 better than 71% | −0.14 ±0.13 better than 33% |
| Execution | −0.19 ±0.49 better than 50% | +0.65 ±0.53 better than 84% |
| Points left on the table | 2.70 ±0.16 lower than 33% | 2.56 ±0.11 lower than 58% |
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.
Structural compatibility
Expected edge per 100 rally shots from style alone: Yafan Wang +1.10, Emma Navarro +1.60. Each player's shot mix weighted by their own skill with each shot and by how much the other gives up against it. This is why some rankings gaps don't hold in a given matchup.
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.
Yafan Wang serving
Deuce court
| 1st serve | Now | Yafan wins | v Emma | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 54% | 60% | 60% | 53.9%±7.7 | 39% ▼ |
| Body | 21% | 64% | 58% | 65.1%±9.4 | 21% |
| T | 25% | 68% | 69% | 68.5%±9.9 | 40% ▲ |
Optimal v Emma Navarro: +0.4±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +8.6 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Yafan wins | v Emma | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 44% | 63% | 62% | 59.2%±8.5 | 43% |
| Body | 21% | 47% | 64% | 55.1%±10.8 | 6% ▼ |
| T | 36% | 63% | 70% | 69.1%±8.0 | 51% ▲ |
Optimal v Emma Navarro: +0.6±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.2 per 100 first serves in before the returner adjusts.
Emma Navarro serving
Deuce court
| 1st serve | Now | Emma wins | v Yafan | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 46% | 61% | 68% | 63.7%±7.7 | 40% ▼ |
| Body | 25% | 60% | 62% | 63.8%±9.7 | 15% ▼ |
| T | 29% | 65% | 77% | 75.2%±7.8 | 45% ▲ |
Optimal v Yafan Wang: +0.4±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +8.1 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Emma wins | v Yafan | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 41% | 64% | 67% | 64.7%±8.1 | 56% ▲ |
| Body | 21% | 58% | 56% | 57.7%±10.9 | 6% ▼ |
| T | 38% | 60% | 68% | 63.7%±8.8 | 38% |
Optimal v Yafan Wang: +0.8±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.9 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.
Yafan Wang returning
1st serve to the forehand
| Return | Now | Tour | Own | v Emma | Value |
|---|---|---|---|---|---|
| FH through the middle | 49% | +4.2 | +2.4 | +0.9 | +7.5±2.7 |
| FH crosscourt | 17% | +5.3 | +1.8 | +3.8 | +10.9±4.1 |
| FH down the line | 14% | +1.5 | +0.7 | +1.3 | +3.6±4.4 |
| FH slice through the middle | 12% | −6.7 | −2.1 | −0.3 | −9.1±2.5 |
| FH slice crosscourt | 4% | −6.6 | +0.1 | −0.3 | −6.8±2.1 |
Lean FH crosscourt: +6.6±3.8 per 100 returns v the current mix (187 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Emma | Value |
|---|---|---|---|---|---|
| BH through the middle | 47% | +6.0 | ±0.0 | ±0.0 | +6.0±2.5 |
| BH crosscourt | 27% | +7.7 | +1.5 | +0.7 | +9.9±3.5 |
| BH down the line | 12% | +2.2 | −0.9 | +2.2 | +3.5±4.4 |
| BH slice through the middle | 9% | −6.2 | −0.3 | +1.5 | −5.0±2.4 |
| BH slice crosscourt | 4% | −4.2 | +0.7 | −0.9 | −4.3±2.3 |
Lean BH crosscourt: +4.6±2.9 per 100 returns v the current mix (182 returns charted)
2nd serve to the forehand
| Return | Now | Tour | Own | v Emma | Value |
|---|---|---|---|---|---|
| FH through the middle | 41% | −3.2 | −0.1 | +1.2 | −2.1±2.8 |
| FH crosscourt | 37% | +0.5 | +1.2 | +3.4 | +5.1±4.1 |
| FH down the line | 22% | −0.6 | −2.0 | +1.8 | −0.8±4.6 |
Lean FH crosscourt: +4.3±3.0 per 100 returns v the current mix (46 returns charted)
2nd serve to the backhand
| Return | Now | Tour | Own | v Emma | Value |
|---|---|---|---|---|---|
| BH through the middle | 56% | −2.6 | +0.2 | −1.3 | −3.7±2.6 |
| BH crosscourt | 34% | +1.5 | +1.6 | +2.1 | +5.1±3.5 |
| BH down the line | 10% | −0.5 | −2.3 | +5.3 | +2.5±4.6 |
Lean BH crosscourt: +5.2±2.8 per 100 returns v the current mix (98 returns charted)
Emma Navarro returning
1st serve to the forehand
| Return | Now | Tour | Own | v Yafan | Value |
|---|---|---|---|---|---|
| FH through the middle | 43% | +4.2 | +1.2 | +1.3 | +6.7±2.7 |
| FH crosscourt | 29% | +5.3 | +2.7 | +0.3 | +8.3±4.2 |
| FH down the line | 18% | +1.5 | +0.5 | −0.4 | +1.6±4.7 |
| FH slice through the middle | 7% | −6.7 | −0.9 | −0.3 | −8.0±2.4 |
| FH slice down the line | 2% | −10.5 | −0.6 | ±0.0 | −11.1±1.7 |
Lean FH crosscourt: +3.5±3.3 per 100 returns v the current mix (421 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Yafan | Value |
|---|---|---|---|---|---|
| BH through the middle | 47% | +6.0 | +2.5 | +2.4 | +11.0±2.6 |
| BH crosscourt | 28% | +7.7 | +0.4 | +0.8 | +8.9±3.6 |
| BH down the line | 10% | +2.2 | +1.5 | +2.4 | +6.0±4.6 |
| BH slice through the middle | 9% | −6.2 | +3.9 | +0.5 | −1.8±2.4 |
| BH slice crosscourt | 4% | −4.2 | −0.5 | +1.0 | −3.7±2.4 |
Lean BH through the middle: +3.2±1.8 per 100 returns v the current mix (370 returns charted)
2nd serve to the forehand
| Return | Now | Tour | Own | v Yafan | Value |
|---|---|---|---|---|---|
| FH through the middle | 49% | −3.2 | +2.9 | +2.2 | +1.9±3.1 |
| FH crosscourt | 28% | +0.5 | +1.3 | +1.2 | +3.1±4.4 |
| FH down the line | 24% | −0.6 | −1.0 | +1.7 | +0.2±5.1 |
Lean FH crosscourt: +1.3±3.7 per 100 returns v the current mix (119 returns charted, inside the 90% margin)
2nd serve to the backhand
| Return | Now | Tour | Own | v Yafan | Value |
|---|---|---|---|---|---|
| BH crosscourt | 47% | +1.5 | −1.1 | −1.1 | −0.7±3.6 |
| BH through the middle | 40% | −2.6 | +0.5 | +0.7 | −1.3±2.8 |
| BH down the line | 13% | −0.5 | +3.5 | −1.0 | +2.0±5.0 |
Lean BH down the line: +2.6±4.8 per 100 returns v the current mix (174 returns charted, inside the 90% margin)
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 grass. Each player's grass record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.
Yafan Wang
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to the middle · serve +1 | +4.7±3.2 | +3.8 | +1.0 |
| BH to their backhand · return | +4.1±4.2 | +0.7 | +3.4 |
| FH to their forehand · return | +4.1±5.2 | +1.1 | +3.0 |
| FH to the middle · return | +3.4±3.1 | +1.7 | +1.7 |
| BH to the middle · return +1 | +3.3±3.2 | +1.3 | +2.0 |
| FH to their backhand · rally | +3.2±4.0 | +2.9 | +0.3 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their forehand · rally | −6.0±5.0 | −3.0 | −3.0 |
| BH to the middle · return | −2.6±2.8 | −0.3 | −2.3 |
| BH to their backhand · return +1 | −0.6±4.4 | +0.8 | −1.4 |
| FH to their forehand · return +1 | −0.4±4.7 | −3.2 | +2.7 |
| FH to their forehand · rally | −0.4±3.3 | +0.2 | −0.5 |
Emma Navarro
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to the middle · return | +4.3±2.7 | +2.2 | +2.2 |
| FH to their forehand · serve +1 | +3.8±4.5 | +2.6 | +1.2 |
| FH to the middle · return | +3.4±3.1 | +1.6 | +1.8 |
| BH to their backhand · return +1 | +3.0±4.3 | +2.5 | +0.5 |
| FH to the middle · rally | +2.7±2.6 | +2.4 | +0.4 |
| BH slice to the middle · rally | +2.5±2.9 | +1.0 | +1.4 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their backhand · serve +1 | −2.6±4.4 | −3.2 | +0.7 |
| FH to their backhand · return +1 | −2.4±5.3 | −0.3 | −2.2 |
| FH to their backhand · return | −1.9±5.4 | −2.7 | +0.7 |
| BH slice to their backhand · rally | −1.8±3.6 | −2.0 | +0.2 |
| BH to their backhand · return | −1.4±4.2 | −1.0 | −0.4 |
Against Emma Navarro-like opponents
| Yafan Wang v | Matches | Serve pts won | Return pts won |
|---|---|---|---|
| All charted opponents | – | 53.0% | 39.0% |
Similar by tactical fingerprint: Coco Gauff, Iva Jovic, Anastasia Potapova, Anna Blinkova, Kimberly Birrell, Emma Raducanu, Nao Hibino, Lin Zhu, R. When two players have rarely met, their records against these lookalikes fill the gap.