Game plan
Kate Makarova v Vera Zvonareva
Every number combines what Kate Makarova does well with what Vera Zvonareva 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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Kate Makarova's record against Vera Zvonareva's tactical lookalikes and in their charted head-to-heads (lookalikes: +5.1 on serve, +0.2 on return vs expectation (181 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 | Kate | Vera |
|---|---|---|
| Direction choice | −0.06 ±0.08 better than 43% | +0.01 ±0.13 better than 54% |
| Shot selection | −0.02 ±0.17 better than 44% | +0.03 ±0.15 better than 47% |
| Execution | −0.16 ±0.83 better than 54% | +0.99 ±0.45 better than 92% |
| Points left on the table | 2.73 ±0.18 lower than 29% | 2.43 ±0.24 lower than 71% |
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.
Kate Makarova serving
Deuce court
| 1st serve | Now | Kate wins | v Vera | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 26% | 67% | 64% | 65.3%±10.0 | 41% ▲ |
| Body | 24% | 55% | 52% | 49.9%±11.3 | 9% ▼ |
| T | 50% | 62% | 71% | 65.5%±9.5 | 50% |
Optimal v Vera Zvonareva: +0.9±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.8 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Kate wins | v Vera | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 28% | 57% | 69% | 60.7%±11.0 | 28% |
| Body | 35% | 51% | 56% | 50.8%±11.1 | 19% ▼ |
| T | 38% | 71% | 64% | 71.3%±8.7 | 53% ▲ |
Optimal v Vera Zvonareva: +1.4±1.2 per 100 first serves (faults included) over the current mix. Serving T every time would read +10.0 per 100 first serves in before the returner adjusts.
Vera Zvonareva serving
Deuce court
| 1st serve | Now | Vera wins | v Kate | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 28% | 64% | 70% | 68.3%±9.7 | 31% ▲ |
| Body | 22% | 54% | 60% | 56.2%±11.6 | 6% ▼ |
| T | 50% | 73% | 68% | 73.7%±8.0 | 63% ▲ |
Optimal v Kate Makarova: +1.0±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.3 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Vera wins | v Kate | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 43% | 61% | 70% | 65.3%±9.8 | 42% |
| Body | 24% | 56% | 50% | 50.1%±12.0 | 9% ▼ |
| T | 34% | 65% | 67% | 67.4%±9.3 | 49% ▲ |
Optimal v Kate Makarova: +1.1±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.0 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.
Kate Makarova returning
1st serve to the forehand
| Return | Now | Tour | Own | v Vera | Value |
|---|---|---|---|---|---|
| FH through the middle | 50% | +4.2 | −0.3 | +0.8 | +4.6±3.0 |
| FH crosscourt | 20% | +5.3 | −1.4 | +2.0 | +5.9±4.4 |
| FH down the line | 15% | +1.5 | −1.4 | +2.3 | +2.4±4.6 |
| FH slice through the middle | 6% | −6.7 | −0.5 | ±0.0 | −7.3±2.1 |
| FH slice crosscourt | 5% | −6.6 | −0.8 | ±0.0 | −7.5±1.4 |
Lean FH crosscourt: +2.6±3.9 per 100 returns v the current mix (181 returns charted, inside the 90% margin)
1st serve to the backhand
| Return | Now | Tour | Own | v Vera | Value |
|---|---|---|---|---|---|
| BH through the middle | 52% | +6.0 | +0.3 | +0.9 | +7.3±2.8 |
| BH crosscourt | 36% | +7.7 | −2.2 | +2.1 | +7.6±3.7 |
| BH down the line | 6% | +2.2 | +0.2 | +0.6 | +3.0±4.2 |
| BH slice through the middle | 6% | −6.2 | −1.6 | +0.2 | −7.6±2.1 |
Lean BH crosscourt: +1.4±2.8 per 100 returns v the current mix (179 returns charted, inside the 90% margin)
2nd serve to the forehand
| Return | Now | Tour | Own | v Vera | Value |
|---|---|---|---|---|---|
| FH through the middle | 52% | −3.2 | +1.4 | −1.0 | −2.8±3.1 |
| FH down the line | 26% | −0.6 | +0.5 | −1.1 | −1.2±5.0 |
| FH crosscourt | 23% | +0.5 | −0.4 | +0.9 | +1.1±4.2 |
Lean FH crosscourt: +2.6±3.9 per 100 returns v the current mix (93 returns charted, inside the 90% margin)
2nd serve to the backhand
| Return | Now | Tour | Own | v Vera | Value |
|---|---|---|---|---|---|
| BH crosscourt | 55% | +1.5 | −0.8 | +2.5 | +3.2±3.5 |
| BH through the middle | 45% | −2.6 | −0.3 | +0.2 | −2.7±2.7 |
Lean BH crosscourt: +2.7±2.0 per 100 returns v the current mix (51 returns charted)
Vera Zvonareva returning
1st serve to the forehand
| Return | Now | Tour | Own | v Kate | Value |
|---|---|---|---|---|---|
| FH through the middle | 43% | +4.2 | +0.8 | −1.0 | +4.0±2.9 |
| FH down the line | 26% | +1.5 | +5.0 | −2.6 | +4.0±4.7 |
| FH crosscourt | 17% | +5.3 | +0.3 | +4.9 | +10.5±4.4 |
| FH slice through the middle | 11% | −6.7 | +1.8 | −1.6 | −6.5±2.1 |
| FH slice crosscourt | 3% | −6.6 | −0.7 | ±0.0 | −7.3±1.2 |
Lean FH crosscourt: +7.0±4.0 per 100 returns v the current mix (209 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Kate | Value |
|---|---|---|---|---|---|
| BH through the middle | 54% | +6.0 | +1.0 | +0.7 | +7.8±2.7 |
| BH crosscourt | 21% | +7.7 | +1.1 | +0.7 | +9.5±3.5 |
| BH down the line | 15% | +2.2 | −1.0 | −0.8 | +0.3±4.4 |
| BH slice through the middle | 10% | −6.2 | +0.6 | −0.6 | −6.2±2.3 |
Lean BH crosscourt: +4.0±3.2 per 100 returns v the current mix (106 returns charted)
2nd serve to the forehand
| Return | Now | Tour | Own | v Kate | Value |
|---|---|---|---|---|---|
| FH down the line | 42% | −0.6 | +1.3 | −2.9 | −2.2±5.1 |
| FH through the middle | 30% | −3.2 | +1.4 | −1.0 | −2.8±2.9 |
| FH crosscourt | 28% | +0.5 | +1.8 | +2.8 | +5.1±4.0 |
Lean FH crosscourt: +5.4±3.7 per 100 returns v the current mix (53 returns charted)
2nd serve to the backhand
| Return | Now | Tour | Own | v Kate | Value |
|---|---|---|---|---|---|
| BH through the middle | 47% | −2.6 | +0.3 | −1.7 | −4.0±2.7 |
| BH crosscourt | 39% | +1.5 | +1.2 | −2.5 | +0.2±3.6 |
| BH down the line | 14% | −0.5 | −0.6 | +1.0 | −0.1±4.7 |
Lean BH crosscourt: +2.0±2.7 per 100 returns v the current mix (83 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.
Kate Makarova
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their backhand · serve +1 | +8.8±5.3 | +2.6 | +6.2 |
| FH to the middle · rally | +5.2±3.2 | +1.9 | +3.3 |
| FH to their backhand · return | +4.3±5.7 | +2.2 | +2.1 |
| FH to their forehand · rally | +2.7±4.9 | −1.3 | +3.9 |
| BH to their forehand · return | +2.1±6.4 | −1.1 | +3.3 |
| FH to the middle · return | +2.1±4.2 | +0.1 | +1.9 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their forehand · rally | −3.2±6.1 | +0.4 | −3.6 |
| FH to their backhand · serve +1 | −2.8±5.8 | −1.7 | −1.1 |
| FH to their forehand · serve +1 | −2.1±5.8 | −6.3 | +4.2 |
| BH to the middle · serve +1 | −1.0±3.3 | −0.4 | −0.6 |
| BH to the middle · rally | −0.8±2.9 | −1.4 | +0.7 |
Vera Zvonareva
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to their backhand · return | +11.6±6.4 | +3.5 | +8.2 |
| FH to their forehand · rally | +5.7±4.9 | +4.5 | +1.3 |
| BH to their backhand · serve +1 | +4.9±5.5 | +4.1 | +0.8 |
| BH to their backhand · return | +4.8±4.6 | +1.9 | +2.9 |
| FH to the middle · return | +3.6±4.0 | +3.7 | −0.1 |
| BH to their backhand · rally | +3.2±4.8 | +1.6 | +1.6 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their forehand · return +1 | −3.1±6.8 | −2.4 | −0.7 |
| BH to the middle · rally | −1.7±2.8 | −0.7 | −1.1 |
| FH to their forehand · return | −1.6±6.2 | +3.3 | −4.9 |
| BH to the middle · return | −0.7±3.7 | −0.2 | −0.5 |
| BH to their forehand · serve +1 | −0.5±6.8 | −2.0 | +1.5 |
Against Vera Zvonareva-like opponents
| Kate Makarova v | Matches | Serve pts won | Return pts won |
|---|---|---|---|
| All charted opponents | – | 54.8% | 39.6% |
| Players most similar to Vera Zvonareva | 1 | 58.7% | 41.6% |
Similar by tactical fingerprint: Magdalena Frech, Jaqueline Cristian, Victoria Azarenka, Linda Fruhvirtova, Simona Halep, Mona Barthel, Jelena Jankovic, Nadia Petrova, Dinara Safina. When two players have rarely met, their records against these lookalikes fill the gap.