RallyIQ

Game plan

Maria Sakkari v Xiyu Wang

Every number combines what Maria Sakkari does well with what Xiyu Wang allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Maria Sakkari wins, best of 3 66%90%: 40%–85% · best of 5: 69%
Serve points won 59.9% / 56.8% Maria / Xiyu · tour 56.4%
Strengths only, no similarity priors 66%serve 59.5% / 56.3%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Maria Sakkari's record against Xiyu Wang's tactical lookalikes and in their charted head-to-heads (lookalikes: +2.7 on serve, −3.8 on return vs expectation (502 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

CareerMariaXiyu
Direction choice+0.01 ±0.06
better than 54%
−0.20 ±0.07
better than 16%
Shot selection+0.36 ±0.08
better than 85%
+0.20 ±0.25
better than 65%
Execution−0.34 ±0.33
better than 42%
−0.96 ±0.91
better than 19%
Points left on the table2.52 ±0.08
lower than 63%
3.04 ±0.21
lower than 9%

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.

Maria Sakkari serving

Deuce court

1st serveNowMaria winsv XiyuMatchupOptimal
Wide41%64%62%59.9%±7.626% ▼
Body16%59%59%60.7%±8.117%
T42%73%67%72.1%±6.757% ▲

Optimal v Xiyu Wang: +0.5±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +6.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMaria winsv XiyuMatchupOptimal
Wide37%62%70%66.3%±7.852% ▲
Body15%61%54%59.0%±9.00% ▼
T48%69%63%67.5%±7.148%

Optimal v Xiyu Wang: +0.7±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.7 per 100 first serves in before the returner adjusts.

Xiyu Wang serving

Deuce court

1st serveNowXiyu winsv MariaMatchupOptimal
Wide31%64%63%60.9%±8.631%
Body32%61%57%60.7%±8.217% ▼
T37%65%69%66.3%±7.452% ▲

Optimal v Maria Sakkari: +0.6±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowXiyu winsv MariaMatchupOptimal
Wide48%66%66%66.4%±6.660% ▲
Body24%59%57%59.2%±9.29% ▼
T28%68%67%70.9%±8.031% ▲

Optimal v Maria Sakkari: +0.7±0.9 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.

Maria Sakkari returning

1st serve to the forehand

ReturnNowTourOwnv XiyuValue
FH through the middle44%+4.2−0.2−2.0+2.0±2.6
FH crosscourt20%+5.3−3.5−1.1+0.7±4.0
FH down the line14%+1.5+1.9−1.5+1.9±4.4
FH slice through the middle12%−6.7−1.9±0.0−8.7±2.4
FH slice crosscourt7%−6.6−2.2−0.2−9.0±2.7

Lean FH through the middle: +2.5±1.8 per 100 returns v the current mix (1015 returns charted)

1st serve to the backhand

ReturnNowTourOwnv XiyuValue
BH through the middle48%+6.0+0.1−1.7+4.4±2.2
BH crosscourt36%+7.7−1.4+2.1+8.3±3.1
BH down the line10%+2.2−4.6−2.1−4.5±4.6
BH slice through the middle4%−6.2−3.6−1.3−11.1±2.4
BH slice crosscourt3%−4.2−3.6−0.6−8.3±2.4

Lean BH crosscourt: +4.4±2.3 per 100 returns v the current mix (954 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv XiyuValue
FH through the middle58%−3.2−3.7+1.3−5.6±2.9
FH crosscourt32%+0.5−1.9+0.1−1.2±4.4
FH down the line10%−0.6−1.1−3.9−5.6±5.1

Lean FH crosscourt: +3.0±3.5 per 100 returns v the current mix (250 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv XiyuValue
BH crosscourt40%+1.5−0.7−1.3−0.4±3.3
BH through the middle38%−2.6−1.1+1.4−2.3±2.6
BH down the line14%−0.5+0.5−0.9−1.0±4.6
FH through the middle5%−2.7−1.9+1.3−3.3±2.6
FH inside-in2%+0.7±0.0+0.1+0.9±4.0

Lean BH crosscourt: +0.9±2.3 per 100 returns v the current mix (509 returns charted, inside the 90% margin)

Xiyu Wang returning

1st serve to the forehand

ReturnNowTourOwnv MariaValue
FH through the middle66%+4.2+0.1−1.1+3.1±2.4
FH crosscourt13%+5.3+0.4−1.8+4.0±3.7
FH down the line13%+1.5+2.7−3.5+0.7±4.0
FH slice through the middle7%−6.7−0.1−0.6−7.4±2.2

Lean FH crosscourt: +1.8±3.6 per 100 returns v the current mix (178 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv MariaValue
BH through the middle52%+6.0+1.7−1.4+6.3±2.3
BH crosscourt27%+7.7+1.3−0.2+8.8±3.3
BH down the line13%+2.2−0.1+2.1+4.2±3.8
BH slice through the middle4%−6.2−0.6−0.4−7.3±2.2
BH slice crosscourt3%−4.2+0.3−1.5−5.4±2.5

Lean BH crosscourt: +3.1±2.7 per 100 returns v the current mix (201 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MariaValue
FH through the middle63%−3.2−0.9−0.1−4.2±2.6
FH down the line26%−0.6+0.1−1.0−1.4±4.2
FH crosscourt12%+0.5+0.4+1.4+2.2±3.6

Lean FH through the middle: −1.4±1.5 per 100 returns v the current mix (43 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MariaValue
BH through the middle48%−2.6−1.3+0.1−3.8±2.2
BH crosscourt34%+1.5−2.6+0.4−0.7±3.1
BH down the line17%−0.5+0.4+0.6+0.5±3.7

Lean BH crosscourt: +1.3±2.4 per 100 returns v the current mix (58 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 hard. Each player's hard record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Maria Sakkari

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+7.7±4.5+3.1+4.6
BH to their forehand · serve +1+2.8±6.3−0.2+3.1
FH to the middle · return +1+2.8±3.2+0.7+2.1
BH to the middle · return +1+2.6±3.1−1.0+3.6
FH to the middle · serve +1+0.8±3.0−0.1+1.0
BH to their forehand · rally+0.7±5.2−1.1+1.8

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−5.8±3.9−0.3−5.5
FH to their forehand · return−5.4±5.4−0.7−4.6
FH to their backhand · serve +1−5.0±4.3−1.8−3.2
BH to the middle · serve +1−4.8±3.1−1.2−3.6
BH to their forehand · return−4.1±5.3−4.0−0.1

Xiyu Wang

Favour

ShotEdgeOwnTheirs
FH to their forehand · return +1+4.9±4.9+5.2−0.3
BH to their forehand · serve +1+4.5±5.8+1.9+2.6
BH to their forehand · return+2.7±5.0+2.2+0.6
FH to the middle · serve +1+0.7±3.0±0.0+0.7
BH to the middle · return +1+0.4±3.1−0.5+0.8
BH to the middle · serve +1+0.3±3.3+0.7−0.5

Avoid

ShotEdgeOwnTheirs
FH to their backhand · return +1−7.0±5.2−5.9−1.1
BH to their forehand · return +1−6.1±6.0−4.3−1.7
FH to their backhand · serve +1−5.8±4.7−4.9−0.9
BH to their forehand · rally−4.1±4.7−0.2−3.9
FH to the middle · rally−3.3±2.7−2.9−0.4

Against Xiyu Wang-like opponents

Maria Sakkari vMatchesServe pts wonReturn pts won
All charted opponents–57.7%41.6%
Players most similar to Xiyu Wang3 59.5%37.8%

Similar by tactical fingerprint: Alexandra Eala, Diana Shnaider, Marta Kostyuk, Jasmine Paolini, Robin Montgomery, Olga Danilovic, Olivia Gadecki, Bernarda Pera, Anett Kontaveit, Eugenie Bouchard. When two players have rarely met, their records against these lookalikes fill the gap.