RallyIQ

Game plan

Monica Niculescu v Saisai Zheng

Every number combines what Monica Niculescu 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

Monica Niculescu wins, best of 3 45%90%: 14%–79% · best of 5: 43%
Serve points won 53.6% / 54.7% Monica / Saisai · tour 56.3%
Strengths only, no similarity priors 41%serve 53.5% / 55.1%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Monica Niculescu's record against Saisai Zheng's tactical lookalikes and in their charted head-to-heads (lookalikes: +1.5 on serve, +3.1 on return vs expectation (439 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

CareerMonicaSaisai
Direction choice−0.30 ±0.13
better than 6%
−0.36 ±0.16
better than 3%
Shot selection−2.97 ±0.45
better than 0%
−0.40 ±0.15
better than 17%
Execution+2.03 ±0.57
better than 98%
−0.20 ±0.75
better than 48%
Points left on the table3.44 ±0.15
lower than 2%
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.

Monica Niculescu serving

Deuce court

1st serveNowMonica winsv SaisaiMatchupOptimal
Wide41%58%65%56.2%±9.441%
Body38%52%51%45.3%±11.723% ▼
T21%63%68%63.4%±11.136% ▲

Optimal v Saisai Zheng: +1.3±1.2 per 100 first serves (faults included) over the current mix. Serving T every time would read +9.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMonica winsv SaisaiMatchupOptimal
Wide34%62%65%61.4%±10.542% ▲
Body30%55%63%62.6%±12.615% ▼
T36%57%65%57.6%±10.243% ▲

Optimal v Saisai Zheng: +0.1±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +2.2 per 100 first serves in before the returner adjusts.

Saisai Zheng serving

Deuce court

1st serveNowSaisai winsv MonicaMatchupOptimal
Wide43%62%62%58.1%±9.552% ▲
Body23%63%54%59.0%±12.38% ▼
T34%67%68%67.6%±10.140% ▲

Optimal v Monica Niculescu: +0.6±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +6.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSaisai winsv MonicaMatchupOptimal
Wide49%58%69%62.5%±10.049%
Body18%59%59%60.9%±12.73% ▼
T33%66%59%60.3%±11.448% ▲

Optimal v Monica Niculescu: +0.5±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.0 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.

Monica Niculescu returning

1st serve to the forehand

ReturnNowTourOwnv SaisaiValue
FH slice through the middle45%−6.7+4.0+0.7−2.0±2.0
FH slice crosscourt31%−6.6+4.4±0.0−2.2±1.9
FH slice down the line13%−10.5+7.4±0.0−3.1±2.4
FH through the middle9%+4.2−1.1−1.4+1.6±3.0
FH crosscourt3%+5.3+1.3−0.6+6.0±3.7

Lean FH through the middle: +3.2±3.0 per 100 returns v the current mix (262 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SaisaiValue
BH through the middle49%+6.0+1.9−0.4+7.6±2.8
BH crosscourt21%+7.7±0.0+0.5+8.3±3.7
BH down the line11%+2.2+2.7−4.0+0.9±4.5
BH slice through the middle9%−6.2±0.0−0.1−6.3±2.1
BH slice crosscourt5%−4.2−0.3+1.0−3.5±2.0

Lean BH crosscourt: +4.0±3.3 per 100 returns v the current mix (187 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SaisaiValue
FH slice through the middle39%−15.2+2.6±0.0−12.6±1.8
FH slice crosscourt35%−14.9+2.5±0.0−12.4±2.0
BH through the middle11%−1.0−0.1+2.9+1.8±2.2
FH slice down the line11%−14.1−0.5±0.0−14.6±2.0
FH crosscourt5%+0.5+0.7+0.1+1.3±3.6

Lean FH slice crosscourt: −1.9±1.5 per 100 returns v the current mix (103 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SaisaiValue
BH through the middle57%−2.6+1.9+2.9+2.2±2.8
BH crosscourt22%+1.5+1.7+0.7+3.9±3.4
BH down the line21%−0.5−0.3+1.2+0.3±4.2

Lean BH crosscourt: +1.7±3.2 per 100 returns v the current mix (72 returns charted, inside the 90% margin)

Saisai Zheng returning

1st serve to the forehand

ReturnNowTourOwnv MonicaValue
FH through the middle47%+4.2+1.1+2.9+8.2±2.9
FH slice through the middle19%−6.7+1.6+0.8−4.2±2.4
FH down the line17%+1.5+2.3+6.3+10.1±4.6
FH crosscourt7%+5.3+0.2+2.3+7.9±3.7
FH slice down the line5%−10.5−0.5±0.0−11.0±1.7

Lean FH down the line: +5.7±4.1 per 100 returns v the current mix (169 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MonicaValue
BH through the middle44%+6.0+1.0+0.4+7.4±2.8
BH down the line23%+2.2+1.9+3.2+7.3±4.6
BH crosscourt18%+7.7+0.9+2.2+10.9±3.5
BH slice through the middle9%−6.2+0.7+0.2−5.3±2.1
BH slice crosscourt7%−4.2+0.4+1.5−2.3±2.3

Lean BH crosscourt: +4.7±3.3 per 100 returns v the current mix (131 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv MonicaValue
BH through the middle48%−2.6−0.7−1.4−4.6±2.6
BH crosscourt32%+1.5−0.6−0.5+0.4±3.4
BH down the line19%−0.5−0.5+1.8+0.7±4.4

Lean BH down the line: +2.7±3.9 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.

Monica Niculescu

Favour

ShotEdgeOwnTheirs
BH to their backhand · return +1+3.5±3.6+3.4+0.1
BH to the middle · return +1+3.2±2.5+1.8+1.4
BH to their backhand · return+3.2±3.7+2.4+0.8
BH to the middle · return+2.2±2.4+0.7+1.5
BH to the middle · rally+1.0±2.0+1.2−0.2
BH to their backhand · serve +1+1.0±3.8+0.6+0.4

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−0.9±2.8+0.2−1.1
BH slice to the middle · rally−0.6±2.4+1.8−2.4
FH to their forehand · rally+0.3±3.6+2.2−2.0
BH to their forehand · rally+0.5±4.4+3.3−2.8
BH to their backhand · serve +1+1.0±3.8+0.6+0.4

Saisai Zheng

Favour

ShotEdgeOwnTheirs
FH to the middle · return+5.5±2.6+1.5+4.0
BH to their backhand · return+2.2±3.7−0.2+2.4
BH to the middle · return+1.9±2.6+0.2+1.7
BH to the middle · rally+1.6±2.1+1.3+0.3
BH to their backhand · rally+0.4±2.7+1.1−0.6
BH slice to their backhand · rally+0.4±2.9−0.4+0.8

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−4.2±4.0−2.1−2.1
FH to their forehand · rally−3.5±2.9−0.1−3.4
FH to the middle · serve +1−3.2±2.8+0.9−4.2
FH to their backhand · return +1−3.0±4.3−0.2−2.8
FH to their backhand · rally−2.8±3.2−0.6−2.2

Against Saisai Zheng-like opponents

Monica Niculescu vMatchesServe pts wonReturn pts won
All charted opponents–52.0%43.9%
Players most similar to Saisai Zheng3 53.6%47.8%

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