RallyIQ

Game plan

Viktorija Golubic v Saisai Zheng

Every number combines what Viktorija Golubic 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

Viktorija Golubic wins, best of 3 46%90%: 13%–82% · best of 5: 45%
Serve points won 54.5% / 55.2% Viktorija / Saisai · tour 55.0%
Strengths only, no similarity priors 46%serve 54.5% / 55.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Viktorija Golubic's record against Saisai Zheng'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

CareerViktorijaSaisai
Direction choice−0.29 ±0.09
better than 8%
−0.36 ±0.16
better than 3%
Shot selection−0.97 ±0.19
better than 3%
−0.40 ±0.15
better than 17%
Execution+0.87 ±0.49
better than 88%
−0.20 ±0.75
better than 48%
Points left on the table2.93 ±0.14
lower than 14%
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.

Viktorija Golubic serving

Deuce court

1st serveNowViktorija winsv SaisaiMatchupOptimal
Wide36%54%65%52.2%±9.521% ▼
Body34%65%51%58.9%±11.549% ▲
T30%55%68%55.7%±11.030%

Optimal v Saisai Zheng: +0.4±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +3.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowViktorija winsv SaisaiMatchupOptimal
Wide35%57%65%56.1%±10.035%
Body30%54%63%61.6%±12.415% ▼
T35%60%65%60.3%±9.850% ▲

Optimal v Saisai Zheng: +0.4±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +2.4 per 100 first serves in before the returner adjusts.

Saisai Zheng serving

Deuce court

1st serveNowSaisai winsv ViktorijaMatchupOptimal
Wide43%62%65%61.4%±9.758% ▲
Body23%63%57%62.6%±10.58% ▼
T34%67%62%61.2%±10.334%

Optimal v Viktorija Golubic: +0.4±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +1.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSaisai winsv ViktorijaMatchupOptimal
Wide49%58%73%66.7%±9.249%
Body18%59%55%57.6%±12.53% ▼
T33%66%67%68.2%±9.948% ▲

Optimal v Viktorija Golubic: +0.8±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.7 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.

Viktorija Golubic returning

1st serve to the forehand

ReturnNowTourOwnv SaisaiValue
FH through the middle53%+4.2+2.0−1.4+4.7±2.9
FH crosscourt16%+5.3−1.5−0.6+3.3±4.4
FH down the line15%+1.5−0.3−2.0−0.7±4.6
FH slice through the middle9%−6.7+0.9+0.7−5.1±2.1
FH slice crosscourt5%−6.6−0.6±0.0−7.2±1.6

Lean FH through the middle: +2.9±1.7 per 100 returns v the current mix (280 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SaisaiValue
BH through the middle32%+6.0+0.1−0.4+5.8±2.8
BH slice through the middle31%−6.2+2.1−0.1−4.2±2.2
BH crosscourt15%+7.7+0.7+0.5+8.9±3.7
BH slice crosscourt10%−4.2+0.9+1.0−2.3±2.4
BH down the line8%+2.2−1.9−4.0−3.7±4.5

Lean BH crosscourt: +8.0±3.3 per 100 returns v the current mix (267 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SaisaiValue
FH through the middle67%−3.2+2.4+0.5−0.2±3.0
FH crosscourt33%+0.5−0.4+0.1+0.3±4.2

Lean FH crosscourt: +0.3±3.4 per 100 returns v the current mix (48 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SaisaiValue
BH through the middle56%−2.6+2.0+2.9+2.3±2.8
BH crosscourt25%+1.5+1.6+0.7+3.8±3.6
BH down the line19%−0.5−1.8+1.2−1.2±4.5

Lean BH crosscourt: +1.8±3.2 per 100 returns v the current mix (135 returns charted, inside the 90% margin)

Saisai Zheng returning

1st serve to the forehand

ReturnNowTourOwnv ViktorijaValue
FH through the middle47%+4.2+1.1+1.0+6.3±2.8
FH slice through the middle19%−6.7+1.6−1.0−6.0±2.3
FH down the line17%+1.5+2.3+1.8+5.7±4.6
FH crosscourt7%+5.3+0.2−2.4+3.1±3.8
FH slice down the line5%−10.5−0.5±0.0−11.0±1.7

Lean FH through the middle: +4.3±1.8 per 100 returns v the current mix (169 returns charted)

1st serve to the backhand

ReturnNowTourOwnv ViktorijaValue
BH through the middle44%+6.0+1.0+1.9+8.9±2.6
BH down the line23%+2.2+1.9+6.0+10.1±4.5
BH crosscourt18%+7.7+0.9+1.5+10.2±3.4
BH slice through the middle9%−6.2+0.7−0.9−6.5±1.8
BH slice crosscourt7%−4.2+0.4±0.0−3.8±1.6

Lean BH crosscourt: +3.0±3.2 per 100 returns v the current mix (131 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv ViktorijaValue
BH through the middle48%−2.6−0.7+0.1−3.2±2.7
BH crosscourt32%+1.5−0.6−0.7+0.2±3.6
BH down the line19%−0.5−0.5+0.5−0.6±4.9

Lean BH crosscourt: +1.8±2.9 per 100 returns v the current mix (77 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 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.

Viktorija Golubic

Favour

ShotEdgeOwnTheirs
FH to their backhand · serve +1+3.5±4.8+1.4+2.1
BH to the middle · return+3.4±3.0+1.9+1.5
FH to the middle · return+2.9±3.2+3.6−0.7
BH to their backhand · serve +1+2.8±4.6+2.4+0.4
BH to the middle · return +1+2.5±3.1+1.1+1.4
FH to their forehand · serve +1+2.3±4.8+0.3+2.0

Avoid

ShotEdgeOwnTheirs
FH to their forehand · return−2.0±5.4−1.5−0.5
BH to the middle · rally−1.3±2.6−1.0−0.2
FH to their forehand · rally−1.2±3.9+0.7−2.0
BH slice to their backhand · rally−1.1±3.3−2.7+1.6
BH to their backhand · return−0.7±4.2−1.5+0.8

Saisai Zheng

Favour

ShotEdgeOwnTheirs
BH to their forehand · return+5.4±5.4−0.3+5.7
FH to the middle · return+3.5±3.2+1.5+2.0
BH to the middle · rally+2.1±2.5+1.3+0.8
BH to the middle · return+2.1±3.0+0.2+1.9
FH to the middle · rally+2.0±2.7+1.3+0.7
BH to their backhand · serve +1+1.9±4.3+0.6+1.3

Avoid

ShotEdgeOwnTheirs
FH to their backhand · return +1−4.3±4.9−0.2−4.1
FH to their backhand · serve +1−1.1±4.7−2.1+1.1
FH to their forehand · rally−0.8±4.0−0.1−0.6
BH to their forehand · rally−0.7±5.1+0.3−1.0
FH to their backhand · rally−0.7±4.0−0.6−0.1

Against Saisai Zheng-like opponents

Viktorija Golubic vMatchesServe pts wonReturn pts won
All charted opponents–53.3%41.3%

Similar by tactical fingerprint: Coco Gauff, Alina Korneeva, Marie Bouzkova, 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.