Game plan
Julia Goerges v Anhelina Kalinina
Every number combines what Julia Goerges does well with what Anhelina Kalinina 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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Julia Goerges's record against Anhelina Kalinina'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 | Julia | Anhelina |
|---|---|---|
| Direction choice | +0.23 ±0.09 better than 89% | +0.24 ±0.10 better than 90% |
| Shot selection | +0.79 ±0.14 better than 99% | −0.03 ±0.17 better than 44% |
| Execution | −0.84 ±0.54 better than 22% | +0.47 ±0.64 better than 78% |
| Points left on the table | 2.33 ±0.13 lower than 84% | 2.11 ±0.10 lower than 98% |
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.
Julia Goerges serving
Deuce court
| 1st serve | Now | Julia wins | v Anhelina | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 47% | 70% | 64% | 68.0%±6.8 | 62% ▲ |
| Body | 16% | 56% | 58% | 57.2%±9.4 | 1% ▼ |
| T | 37% | 72% | 62% | 67.4%±8.2 | 37% |
Optimal v Anhelina Kalinina: +1.1±1.0 per 100 first serves (faults included) over the current mix. Serving wide every time would read +2.0 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Julia wins | v Anhelina | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 38% | 72% | 64% | 70.5%±7.3 | 37% ▼ |
| Body | 14% | 54% | 51% | 48.2%±10.7 | 0% ▼ |
| T | 48% | 71% | 66% | 73.1%±6.9 | 63% ▲ |
Optimal v Anhelina Kalinina: +1.6±1.1 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.5 per 100 first serves in before the returner adjusts.
Anhelina Kalinina serving
Deuce court
| 1st serve | Now | Anhelina wins | v Julia | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 39% | 61% | 66% | 60.8%±8.2 | 39% |
| Body | 27% | 55% | 59% | 56.5%±8.7 | 12% ▼ |
| T | 34% | 64% | 71% | 67.6%±7.6 | 49% ▲ |
Optimal v Julia Goerges: +1.4±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +5.6 per 100 first serves in before the returner adjusts.
Ad court
| 1st serve | Now | Anhelina wins | v Julia | Matchup | Optimal |
|---|---|---|---|---|---|
| Wide | 50% | 63% | 70% | 67.6%±7.1 | 65% ▲ |
| Body | 25% | 51% | 53% | 47.9%±9.3 | 9% ▼ |
| T | 25% | 62% | 57% | 55.2%±9.5 | 26% |
Optimal v Julia Goerges: +0.8±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +8.0 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.
Julia Goerges returning
1st serve to the forehand
| Return | Now | Tour | Own | v Anhelina | Value |
|---|---|---|---|---|---|
| FH through the middle | 33% | +4.2 | −2.0 | +1.1 | +3.2±2.9 |
| FH down the line | 28% | +1.5 | +0.3 | +1.5 | +3.3±4.6 |
| FH crosscourt | 18% | +5.3 | +2.3 | +1.6 | +9.2±4.3 |
| FH slice through the middle | 15% | −6.7 | −0.9 | ±0.0 | −7.6±2.4 |
| FH slice crosscourt | 3% | −6.6 | +0.7 | +0.9 | −5.0±2.0 |
Lean FH crosscourt: +7.0±3.9 per 100 returns v the current mix (265 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Anhelina | Value |
|---|---|---|---|---|---|
| BH through the middle | 43% | +6.0 | −1.7 | +0.1 | +4.4±2.5 |
| BH crosscourt | 19% | +7.7 | −3.5 | −1.4 | +2.8±3.5 |
| BH down the line | 18% | +2.2 | −1.8 | −0.9 | −0.5±4.7 |
| BH slice through the middle | 11% | −6.2 | −1.9 | −1.2 | −9.4±2.5 |
| BH slice crosscourt | 7% | −4.2 | −4.0 | +0.4 | −7.8±2.6 |
Lean BH through the middle: +4.0±1.8 per 100 returns v the current mix (371 returns charted)
2nd serve to the forehand
| Return | Now | Tour | Own | v Anhelina | Value |
|---|---|---|---|---|---|
| FH crosscourt | 40% | +0.5 | −1.6 | −1.1 | −2.1±4.3 |
| FH through the middle | 32% | −3.2 | −1.3 | −0.6 | −5.1±2.9 |
| FH down the line | 28% | −0.6 | −1.1 | +1.2 | −0.5±4.9 |
Lean FH down the line: +2.1±4.0 per 100 returns v the current mix (57 returns charted, inside the 90% margin)
2nd serve to the backhand
| Return | Now | Tour | Own | v Anhelina | Value |
|---|---|---|---|---|---|
| BH through the middle | 33% | −2.6 | −3.0 | ±0.0 | −5.5±2.7 |
| BH crosscourt | 25% | +1.5 | +0.8 | −1.9 | +0.4±3.6 |
| BH down the line | 22% | −0.5 | −3.7 | +5.1 | +0.8±5.3 |
| FH inside-out | 8% | +1.4 | −2.8 | +1.2 | −0.2±4.0 |
| FH inside-in | 6% | +0.7 | +1.2 | −1.1 | +0.9±4.2 |
Lean BH down the line: +2.6±4.3 per 100 returns v the current mix (183 returns charted, inside the 90% margin)
Anhelina Kalinina returning
1st serve to the forehand
| Return | Now | Tour | Own | v Julia | Value |
|---|---|---|---|---|---|
| FH through the middle | 38% | +4.2 | −2.3 | −0.8 | +1.1±2.8 |
| FH crosscourt | 26% | +5.3 | +3.1 | +1.9 | +10.3±4.3 |
| FH slice through the middle | 16% | −6.7 | +0.5 | −0.6 | −6.7±2.6 |
| FH down the line | 11% | +1.5 | −1.3 | +2.5 | +2.7±4.7 |
| FH slice crosscourt | 7% | −6.6 | +1.3 | +0.8 | −4.6±2.5 |
Lean FH crosscourt: +8.6±3.4 per 100 returns v the current mix (312 returns charted)
1st serve to the backhand
| Return | Now | Tour | Own | v Julia | Value |
|---|---|---|---|---|---|
| BH through the middle | 48% | +6.0 | +1.3 | −1.9 | +5.5±2.6 |
| BH crosscourt | 44% | +7.7 | −0.2 | +1.5 | +8.9±3.5 |
| BH down the line | 9% | +2.2 | +3.6 | −0.4 | +5.3±4.5 |
Lean BH crosscourt: +2.0±2.4 per 100 returns v the current mix (270 returns charted, inside the 90% margin)
2nd serve to the forehand
| Return | Now | Tour | Own | v Julia | Value |
|---|---|---|---|---|---|
| FH crosscourt | 48% | +0.5 | +0.4 | +1.9 | +2.8±4.5 |
| FH through the middle | 35% | −3.2 | +3.0 | +0.5 | +0.4±3.0 |
| FH down the line | 17% | −0.6 | +0.1 | +0.6 | +0.1±4.8 |
Lean FH crosscourt: +1.3±2.7 per 100 returns v the current mix (81 returns charted, inside the 90% margin)
2nd serve to the backhand
| Return | Now | Tour | Own | v Julia | Value |
|---|---|---|---|---|---|
| BH crosscourt | 58% | +1.5 | −1.0 | −1.0 | −0.6±3.4 |
| BH through the middle | 37% | −2.6 | +1.4 | −3.4 | −4.6±2.7 |
| BH down the line | 6% | −0.5 | +0.8 | −1.9 | −1.6±4.4 |
Lean BH crosscourt: +1.5±1.8 per 100 returns v the current mix (120 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.
Julia Goerges
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to their backhand · rally | +7.1±5.2 | +1.2 | +5.9 |
| FH to their forehand · serve +1 | +4.9±5.3 | −0.2 | +5.1 |
| BH to their backhand · serve +1 | +4.6±4.4 | +2.9 | +1.7 |
| BH to their backhand · return +1 | +4.2±3.5 | +2.5 | +1.8 |
| FH to their backhand · serve +1 | +3.2±5.5 | +2.1 | +1.0 |
| FH to their forehand · return +1 | +2.6±4.7 | +1.8 | +0.8 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to the middle · return | −8.1±4.0 | −6.4 | −1.7 |
| BH to the middle · return | −3.4±3.6 | −4.6 | +1.3 |
| BH to their forehand · return | −3.0±6.2 | −4.6 | +1.6 |
| BH to their backhand · return | −2.8±4.1 | −1.0 | −1.7 |
| BH to their forehand · return +1 | −2.2±5.7 | −1.8 | −0.4 |
Anhelina Kalinina
Favour
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| FH to their forehand · return | +6.5±5.2 | +3.4 | +3.1 |
| FH to their backhand · return | +4.5±5.2 | −0.5 | +5.0 |
| BH to the middle · return +1 | +3.7±2.5 | +2.7 | +1.1 |
| FH to their forehand · return +1 | +2.8±5.5 | +0.1 | +2.6 |
| BH to the middle · serve +1 | +2.7±3.5 | +0.9 | +1.7 |
| FH to their forehand · rally | +2.2±5.0 | +0.3 | +1.9 |
Avoid
| Shot | Edge | Own | Theirs |
|---|---|---|---|
| BH to their forehand · serve +1 | −11.6±5.6 | −2.9 | −8.7 |
| BH to their backhand · serve +1 | −8.2±4.9 | −5.1 | −3.2 |
| FH to their backhand · serve +1 | −5.7±5.1 | −0.3 | −5.4 |
| BH to the middle · return | −4.7±3.7 | +1.3 | −6.0 |
| BH to their backhand · return | −4.2±4.7 | −3.4 | −0.8 |
Against Anhelina Kalinina-like opponents
| Julia Goerges v | Matches | Serve pts won | Return pts won |
|---|---|---|---|
| All charted opponents | – | 62.2% | 42.5% |
Similar by tactical fingerprint: Anna Blinkova, Linda Klimovicova, Magda Linette, Sara Bejlek, Varvara Gracheva, Yue Yuan, Anastasija Sevastova, Su Wei Hsieh, Anett Kontaveit, Elena Vesnina. When two players have rarely met, their records against these lookalikes fill the gap.