RallyIQ

Game plan

Alina Korneeva v Saisai Zheng

Every number combines what Alina Korneeva does well with what Saisai Zheng allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Alina Korneeva wins, best of 3 77%90%: 32%–97% · best of 5: 82%
Serve points won 57.9% / 52.4% Alina / Saisai · tour 58.1%
Strengths only, no similarity priors 79%serve 58.6% / 52.5%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Alina Korneeva's record against Saisai Zheng's tactical lookalikes and in their charted head-to-heads (lookalikes: −15.0 on serve, +4.4 on return vs expectation (116 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

CareerAlinaSaisai
Direction choice−0.01 ±0.10
better than 51%
−0.36 ±0.16
better than 3%
Shot selection+0.25 ±0.25
better than 73%
−0.40 ±0.15
better than 17%
Execution+0.66 ±0.76
better than 84%
−0.20 ±0.75
better than 48%
Points left on the table2.48 ±0.14
lower than 67%
3.22 ±0.21
lower than 4%

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.

Alina Korneeva serving

Deuce court

1st serveNowAlina winsv SaisaiMatchupOptimal
Wide36%66%65%64.8%±9.844% ▲
Body36%54%51%47.6%±12.421% ▼
T29%66%68%66.5%±11.135% ▲

Optimal v Saisai Zheng: +1.0±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAlina winsv SaisaiMatchupOptimal
Wide48%59%65%58.6%±10.349%
Body26%62%63%68.9%±12.310% ▼
T26%70%65%70.1%±10.541% ▲

Optimal v Saisai Zheng: +0.4±1.3 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.9 per 100 first serves in before the returner adjusts.

Saisai Zheng serving

Deuce court

1st serveNowSaisai winsv AlinaMatchupOptimal
Wide43%62%60%56.2%±10.052% ▲
Body23%63%52%57.7%±11.78% ▼
T34%67%64%63.2%±11.840% ▲

Optimal v Alina Korneeva: +0.3±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSaisai winsv AlinaMatchupOptimal
Wide49%58%60%52.6%±10.933% ▼
Body18%59%51%53.2%±12.719%
T33%66%51%52.2%±12.348% ▲

Optimal v Alina Korneeva: +0.3±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +0.6 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.

Alina Korneeva returning

1st serve to the forehand

ReturnNowTourOwnv SaisaiValue
FH through the middle42%+4.2+2.6−1.4+5.3±3.1
FH crosscourt33%+5.3+1.8−0.6+6.6±4.3
FH slice through the middle10%−6.7+0.8+0.7−5.2±2.0
FH down the line9%+1.5+2.4−2.0+1.9±4.3
FH slice crosscourt6%−6.6+0.7±0.0−6.0±1.6

Lean FH crosscourt: +3.0±3.2 per 100 returns v the current mix (206 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv SaisaiValue
BH through the middle61%+6.0+2.3−0.4+8.0±2.9
BH crosscourt24%+7.7+1.9+0.5+10.1±3.6
BH down the line12%+2.2+0.5−4.0−1.3±4.3
BH slice through the middle4%−6.2−0.8−0.1−7.1±1.7

Lean BH crosscourt: +3.3±3.3 per 100 returns v the current mix (127 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SaisaiValue
FH crosscourt46%+0.5+0.3+0.1+0.9±4.3
FH through the middle30%−3.2+0.3+0.5−2.3±2.8
FH down the line24%−0.6+3.7±0.0+3.1±4.3

Lean FH crosscourt: +0.5±2.7 per 100 returns v the current mix (50 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SaisaiValue
BH crosscourt44%+1.5−0.8+0.7+1.4±3.5
BH through the middle37%−2.6+0.2+2.9+0.5±2.7
BH down the line19%−0.5−4.1+1.2−3.5±3.9

Lean BH crosscourt: +1.3±2.3 per 100 returns v the current mix (52 returns charted, inside the 90% margin)

Saisai Zheng returning

1st serve to the forehand

ReturnNowTourOwnv AlinaValue
FH through the middle47%+4.2+1.1+0.2+5.5±3.1
FH slice through the middle19%−6.7+1.6+0.1−5.0±2.3
FH down the line17%+1.5+2.3+0.7+4.5±4.6
FH crosscourt7%+5.3+0.2+1.2+6.7±3.9
FH slice down the line5%−10.5−0.5±0.0−11.0±1.7

Lean FH through the middle: +3.5±1.9 per 100 returns v the current mix (169 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AlinaValue
BH through the middle44%+6.0+1.0+1.6+8.5±2.8
BH down the line23%+2.2+1.9+2.0+6.1±4.6
BH crosscourt18%+7.7+0.9−0.2+8.4±3.6
BH slice through the middle9%−6.2+0.7±0.0−5.5±1.9
BH slice crosscourt7%−4.2+0.4±0.0−3.8±1.6

Lean BH through the middle: +2.7±2.0 per 100 returns v the current mix (131 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv AlinaValue
BH through the middle48%−2.6−0.7+1.5−1.7±2.8
BH crosscourt32%+1.5−0.6+2.5+3.4±3.5
BH down the line19%−0.5−0.5−1.8−2.9±4.7

Lean BH crosscourt: +3.7±2.9 per 100 returns v the current mix (77 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 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.

Alina Korneeva

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+3.1±4.3+3.6−0.5
FH to their forehand · serve +1+3.0±4.8−0.3+3.2
BH to the middle · return+2.9±3.1+1.1+1.8
BH to their backhand · return+2.8±4.4+0.5+2.4
FH to their backhand · serve +1+2.7±5.1+2.3+0.4
BH to the middle · return +1+2.3±2.6+0.9+1.4

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−3.8±4.5−1.1−2.8
BH to their backhand · serve +1−3.8±3.8−4.2+0.4
FH to their backhand · rally−2.0±4.5+1.8−3.8
BH to their backhand · rally−1.4±3.6−1.0−0.4
BH to the middle · rally−0.3±2.1±0.0−0.2

Saisai Zheng

Favour

ShotEdgeOwnTheirs
BH to the middle · return+2.8±2.5+0.2+2.6
FH to the middle · return +1+2.3±2.8+0.2+2.1
FH to the middle · rally+2.2±2.9−1.0+3.2
BH to their forehand · rally+2.2±4.5+0.3+1.8
FH to the middle · return+2.1±2.7+1.5+0.6
BH to their backhand · rally+2.0±3.8+2.2−0.2

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−3.7±5.1−2.0−1.7
FH to their backhand · rally−2.3±4.5−0.8−1.4
FH to their backhand · return +1−1.7±4.3−0.2−1.5
BH slice to their backhand · rally−0.6±3.6−0.5−0.1
BH to their forehand · return−0.2±5.5−0.9+0.7

Against Saisai Zheng-like opponents

Alina Korneeva vMatchesServe pts wonReturn pts won
All charted opponents–54.6%50.6%
Players most similar to Saisai Zheng1 38.2%47.9%

Similar by tactical fingerprint: Coco Gauff, Marie Bouzkova, Viktorija Golubic, Emma Navarro, Yafan Wang, Petra Martic, Alize Cornet, Anna Lena Friedsam, Agnieszka Radwanska. When two players have rarely met, their records against these lookalikes fill the gap.