Game plan
Jessica Pegula v Anna Karolina Schmiedlova
Every number combines what Jessica Pegula does well with what Anna Karolina Schmiedlova 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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Jessica Pegula's record against Anna Karolina Schmiedlova's tactical lookalikes and in their charted head-to-heads (lookalikes: +3.7 on serve, +4.1 on return vs expectation (626 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 | Jessica | Anna |
|---|---|---|
| Direction choice | −0.15 ±0.04 better than 25% | −0.07 ±0.09 better than 40% |
| Shot selection | −0.24 ±0.07 better than 26% | +0.06 ±0.12 better than 53% |
| Execution | +0.29 ±0.30 better than 72% | +0.53 ±0.71 better than 80% |
| Points left on the table | 2.72 ±0.06 lower than 31% | 2.38 ±0.13 lower than 78% |
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.
Jessica Pegula serving
Deuce court
| 1st serve | Now | Jessica wins | v Anna | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 31% | 67% | 68% | 69.5%±7.4 | 46% ▲ |
| Body | 29% | 62% | 56% | 61.1%±8.5 | 14% ▼ |
| T | 40% | 74% | 73% | 78.1%±6.3 | 40% |
Optimal v Anna Karolina Schmiedlova: +0.4±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.6 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Jessica wins | v Anna | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 29% | 66% | 70% | 70.7%±9.0 | 44% ▲ |
| Body | 22% | 61% | 53% | 58.3%±8.5 | 7% ▼ |
| T | 49% | 63% | 61% | 59.3%±7.7 | 49% |
Optimal v Anna Karolina Schmiedlova: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +8.4 per 100 first serves in before the returner adjusts.
Anna Karolina Schmiedlova serving
Deuce court
| 1st serve | Now | Anna wins | v Jessica | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 36% | 67% | 65% | 66.3%±7.4 | 37% |
| Body | 27% | 53% | 55% | 50.0%±8.3 | 12% ▼ |
| T | 36% | 69% | 70% | 71.9%±7.2 | 51% ▲ |
Optimal v Jessica Pegula: +1.0±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +8.0 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Anna wins | v Jessica | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 24% | 61% | 64% | 59.1%±9.4 | 35% ▲ |
| Body | 26% | 56% | 54% | 53.4%±9.1 | 11% ▼ |
| T | 50% | 65% | 62% | 62.5%±7.6 | 54% ▲ |
Optimal v Jessica Pegula: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.2 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.
Jessica Pegula returning
1st serve to the forehand
| Return | Now | Tour | Own | v Anna | Value |
|---|---|---|---|---|---|
| FH through the middle | 49% | +4.2 | −1.8 | +1.4 | +3.8±2.4 |
| FH crosscourt | 19% | +5.3 | +1.4 | +2.9 | +9.7±3.9 |
| FH slice through the middle | 13% | −6.7 | +0.3 | +0.1 | −6.3±2.3 |
| FH down the line | 11% | +1.5 | +0.4 | −0.6 | +1.3±4.4 |
| FH slice crosscourt | 4% | −6.6 | −0.2 | −0.7 | −7.5±2.3 |
Lean FH crosscourt: +7.3±3.4 per 100 returns v the current mix (1257 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Anna | Value |
|---|---|---|---|---|---|
| BH through the middle | 42% | +6.0 | −3.0 | −0.7 | +2.3±2.3 |
| BH crosscourt | 24% | +7.7 | +0.5 | −0.4 | +7.8±3.1 |
| BH slice through the middle | 12% | −6.2 | −0.2 | +0.1 | −6.3±2.0 |
| BH down the line | 12% | +2.2 | −1.4 | +0.1 | +0.8±4.2 |
| BH slice crosscourt | 6% | −4.2 | −0.9 | ±0.0 | −5.1±2.1 |
Lean BH crosscourt: +6.5±2.6 per 100 returns v the current mix (1269 returns charted)
2nd serve to the forehand
| Return | Now | Tour | Own | v Anna | Value |
|---|---|---|---|---|---|
| FH through the middle | 46% | −3.2 | −1.4 | +1.8 | −2.8±2.9 |
| FH crosscourt | 27% | +0.5 | +0.2 | +0.4 | +1.1±4.4 |
| FH down the line | 23% | −0.6 | +2.7 | −2.3 | −0.2±5.1 |
| FH slice through the middle | 2% | −15.2 | −1.2 | ±0.0 | −16.4±1.3 |
| FH slice down the line | 2% | −14.1 | −1.7 | ±0.0 | −15.8±1.7 |
Lean FH crosscourt: +2.8±3.6 per 100 returns v the current mix (359 returns charted, inside the 90% margin)
2nd serve to the backhand
| Return | Now | Tour | Own | v Anna | Value |
|---|---|---|---|---|---|
| BH through the middle | 48% | −2.6 | −1.0 | +0.8 | −2.8±2.4 |
| BH crosscourt | 34% | +1.5 | −6.1 | +1.8 | −2.8±3.3 |
| BH down the line | 17% | −0.5 | −0.4 | +2.5 | +1.5±5.0 |
| BH slice through the middle | 2% | −11.7 | −0.9 | ±0.0 | −12.6±1.3 |
Lean BH down the line: +3.8±4.5 per 100 returns v the current mix (637 returns charted, inside the 90% margin)
Anna Karolina Schmiedlova returning
1st serve to the forehand
| Return | Now | Tour | Own | v Jessica | Value |
|---|---|---|---|---|---|
| FH through the middle | 48% | +4.2 | +1.9 | +0.4 | +6.5±2.4 |
| FH crosscourt | 19% | +5.3 | +1.2 | ±0.0 | +6.5±3.6 |
| FH down the line | 16% | +1.5 | −0.3 | −1.3 | ±0.0±4.0 |
| FH slice through the middle | 11% | −6.7 | −0.9 | +0.8 | −6.8±2.2 |
| BH inside-in | 3% | +7.3 | +0.7 | −1.5 | +6.4±2.3 |
Lean FH crosscourt: +3.0±3.2 per 100 returns v the current mix (161 returns charted, inside the 90% margin)
1st serve to the backhand
| Return | Now | Tour | Own | v Jessica | Value |
|---|---|---|---|---|---|
| BH through the middle | 54% | +6.0 | +0.9 | −0.2 | +6.7±2.3 |
| BH crosscourt | 26% | +7.7 | −2.9 | −1.5 | +3.2±3.0 |
| BH down the line | 11% | +2.2 | −1.7 | −3.2 | −2.7±3.5 |
| BH slice through the middle | 9% | −6.2 | −0.6 | −1.1 | −8.0±2.1 |
Lean BH through the middle: +3.3±1.4 per 100 returns v the current mix (100 returns charted)
2nd serve to the backhand
| Return | Now | Tour | Own | v Jessica | Value |
|---|---|---|---|---|---|
| BH crosscourt | 48% | +1.5 | +0.2 | −0.5 | +1.1±2.9 |
| BH through the middle | 43% | −2.6 | −0.6 | +0.1 | −3.1±2.2 |
| BH down the line | 8% | −0.5 | −1.4 | −0.8 | −2.7±3.5 |
Lean BH crosscourt: +2.2±1.8 per 100 returns v the current mix (60 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 clay. Each player's clay record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.
Jessica Pegula
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to their forehand · return | +5.9±5.5 | −0.7 | +6.6 |
| BH to their backhand · rally | +5.3±3.3 | +1.0 | +4.2 |
| FH to their forehand · rally | +3.3±3.6 | +2.9 | +0.3 |
| FH to their backhand · rally | +3.2±4.3 | −0.2 | +3.4 |
| FH to their forehand · return +1 | +2.9±5.0 | +0.3 | +2.6 |
| BH to the middle · rally | +2.1±2.7 | +0.2 | +2.0 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to their forehand · serve +1 | −4.7±5.0 | +0.6 | −5.4 |
| BH to their forehand · rally | −4.1±5.2 | −0.9 | −3.2 |
| BH to the middle · return | −4.0±3.0 | −3.8 | −0.3 |
| FH to their backhand · return | −3.2±5.5 | +0.9 | −4.1 |
| FH to the middle · serve +1 | −2.5±3.4 | −2.6 | +0.1 |
Anna Karolina Schmiedlova
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to the middle · rally | +4.5±2.7 | +3.8 | +0.7 |
| FH to their forehand · return +1 | +3.8±5.0 | +3.7 | +0.1 |
| BH to the middle · return +1 | +2.3±3.2 | +1.4 | +0.9 |
| BH to the middle · rally | +1.9±2.7 | +2.9 | −1.1 |
| FH to their forehand · rally | +1.8±3.6 | +0.4 | +1.4 |
| BH to their backhand · rally | +0.3±3.2 | +0.9 | −0.6 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their backhand · serve +1 | −3.9±4.3 | −0.4 | −3.5 |
| BH to their backhand · return +1 | −3.7±4.3 | −2.6 | −1.1 |
| BH to their forehand · rally | −2.8±5.4 | −0.6 | −2.3 |
| BH to their backhand · return | −2.2±3.9 | +1.8 | −4.0 |
| FH to their forehand · serve +1 | −1.4±5.0 | −0.3 | −1.0 |
Against Anna Karolina Schmiedlova-like opponents
| Jessica Pegula v | Matches | Serve pts won | Return pts won |
|---|---|---|---|
| All charted opponents | – | 58.5% | 43.9% |
| Players most similar to Anna Karolina Schmiedlova | 4 | 59.8% | 47.5% |
Similar by tactical fingerprint: Elina Svitolina, Kimberly Birrell, Varvara Gracheva, Elisabetta Cocciaretto, Ana Bogdan, Caroline Wozniacki, Qiang Wang, Carla Suarez Navarro, Marion Bartoli. When two players have rarely met, their records against these lookalikes fill the gap.