RallyIQ

Game plan

Caroline Wozniacki v Maya Joint

Every number combines what Caroline Wozniacki does well with what Maya Joint allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Caroline Wozniacki wins, best of 3 84%90%: 59%–96% · best of 5: 89%
Serve points won 59.1% / 51.7% Caroline / Maya · tour 56.3%
Strengths only, no similarity priors 81%serve 58.8% / 52.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Caroline Wozniacki's record against Maya Joint's tactical lookalikes and in their charted head-to-heads (lookalikes: +1.4 on serve, +2.4 on return vs expectation (795 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

CareerCarolineMaya
Direction choice+0.03 ±0.05
better than 59%
−0.21 ±0.12
better than 16%
Shot selection+0.06 ±0.06
better than 52%
+0.13 ±0.15
better than 59%
Execution+2.22 ±0.16
better than 100%
−0.78 ±0.58
better than 24%
Points left on the table2.40 ±0.07
lower than 76%
2.76 ±0.15
lower than 28%

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.

Structural compatibility

Expected edge per 100 rally shots from style alone: Caroline Wozniacki +2.27, Maya Joint +0.13. Each player's shot mix weighted by their own skill with each shot and by how much the other gives up against it. This is why some rankings gaps don't hold in a given matchup.

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.

Caroline Wozniacki serving

Deuce court

1st serveNowCaroline winsv MayaMatchupOptimal
Wide42%67%69%70.0%±5.757% ▲
Body25%62%55%59.7%±7.810% ▼
T33%71%70%72.7%±5.733%

Optimal v Maya Joint: +0.7±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowCaroline winsv MayaMatchupOptimal
Wide35%68%72%74.0%±5.550% ▲
Body24%59%54%56.9%±8.49% ▼
T41%63%68%67.2%±6.841%

Optimal v Maya Joint: +0.8±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +6.9 per 100 first serves in before the returner adjusts.

Maya Joint serving

Deuce court

1st serveNowMaya winsv CarolineMatchupOptimal
Wide38%62%60%55.7%±6.329% ▼
Body19%61%50%53.4%±8.213% ▼
T43%65%63%59.2%±6.458% ▲

Optimal v Caroline Wozniacki: +0.1±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMaya winsv CarolineMatchupOptimal
Wide45%62%60%56.0%±6.360% ▲
Body16%48%47%39.7%±8.51% ▼
T39%55%59%48.3%±6.739%

Optimal v Caroline Wozniacki: +1.1±0.9 per 100 first serves (faults included) over the current mix. Serving wide every time would read +5.6 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.

Caroline Wozniacki returning

1st serve to the forehand

ReturnNowTourOwnv MayaValue
FH through the middle52%+4.2+3.4+2.7+10.3±2.0
FH crosscourt21%+5.3+3.9+0.7+10.0±3.4
FH down the line16%+1.5+6.2+0.1+7.8±3.8
FH slice through the middle7%−6.7−1.5+0.8−7.4±2.0
FH slice crosscourt2%−6.6−1.7+0.6−7.8±2.3

Lean FH through the middle: +2.4±1.4 per 100 returns v the current mix (2852 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MayaValue
BH through the middle45%+6.0+2.8+1.1+9.9±1.9
BH crosscourt36%+7.7+4.0+2.4+14.1±2.8
BH slice through the middle9%−6.2−1.9−0.6−8.7±2.2
BH down the line5%+2.2+5.0+1.8+9.0±4.6
BH slice down the line3%−12.5−2.1+1.2−13.4±3.0

Lean BH crosscourt: +5.4±2.0 per 100 returns v the current mix (1809 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MayaValue
FH through the middle43%−3.2+3.7+0.8+1.3±2.6
FH down the line29%−0.6+2.5−1.0+1.0±4.5
FH crosscourt26%+0.5+3.0−0.4+3.2±3.9
BH inside-out1%+2.2+0.3−1.9+0.6±3.9
BH through the middle1%−1.0−0.3+0.3−0.9±2.0

Lean FH crosscourt: +1.7±3.3 per 100 returns v the current mix (983 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MayaValue
BH crosscourt54%+1.5+3.5+1.0+6.0±3.0
BH through the middle35%−2.6+4.1+0.3+1.9±2.3
BH down the line12%−0.5+2.0−1.9−0.5±5.1

Lean BH crosscourt: +2.2±1.7 per 100 returns v the current mix (834 returns charted)

Maya Joint returning

1st serve to the forehand

ReturnNowTourOwnv CarolineValue
FH through the middle49%+4.2−1.2+0.9+3.9±2.2
FH crosscourt27%+5.3−1.1+1.4+5.6±3.4
FH down the line11%+1.5−1.3+3.6+3.8±3.7
FH slice through the middle9%−6.7+0.1+0.3−6.3±2.2
FH slice crosscourt3%−6.6−0.3−1.1−8.0±2.4

Lean FH crosscourt: +2.9±2.8 per 100 returns v the current mix (241 returns charted)

1st serve to the backhand

ReturnNowTourOwnv CarolineValue
BH through the middle54%+6.0−2.3±0.0+3.7±2.0
BH crosscourt28%+7.7−4.3+1.2+4.7±2.9
BH down the line9%+2.2−1.4−1.1−0.4±3.6
BH slice through the middle7%−6.2−0.8−1.3−8.3±2.1
BH slice crosscourt3%−4.2−1.4−0.1−5.7±2.5

Lean BH crosscourt: +2.1±2.4 per 100 returns v the current mix (259 returns charted, inside the 90% margin)

2nd serve to the forehand

ReturnNowTourOwnv CarolineValue
FH through the middle50%−3.2+0.1+1.8−1.2±2.4
FH crosscourt38%+0.5−1.9+0.8−0.5±3.3
FH down the line13%−0.6−0.6+1.5+0.4±3.3

Lean FH crosscourt: +0.2±2.4 per 100 returns v the current mix (48 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv CarolineValue
BH through the middle47%−2.6+0.3+1.8−0.5±2.3
BH crosscourt34%+1.5+3.8+0.3+5.5±3.0
BH down the line19%−0.5−1.4+2.9+1.0±4.3

Lean BH crosscourt: +3.7±2.4 per 100 returns v the current mix (121 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.

Caroline Wozniacki

Favour

ShotEdgeOwnTheirs
FH to the middle · return+6.9±1.8+4.2+2.7
BH to their backhand · return+5.7±2.3+3.4+2.3
FH to their forehand · return+4.9±3.3+4.1+0.8
BH to their backhand · return +1+4.2±2.7+3.2+1.0
BH to their backhand · rally+4.0±2.1+2.7+1.2
BH to the middle · return+3.8±1.6+2.6+1.1

Avoid

ShotEdgeOwnTheirs
FH to their forehand · return +1−1.7±2.9+1.4−3.1
FH to the middle · serve +1−1.6±2.0+1.4−3.1
BH to their forehand · return +1−1.4±3.9+3.3−4.7
FH to their forehand · rally−0.8±2.1+1.7−2.5
BH to the middle · serve +1+0.7±1.9+2.1−1.4

Maya Joint

Favour

ShotEdgeOwnTheirs
FH to their backhand · serve +1+4.2±3.1+1.2+3.0
FH to their backhand · return+3.5±3.5+0.7+2.8
FH to their forehand · serve +1+3.5±2.9+2.4+1.1
FH to their forehand · return +1+1.6±3.0+1.7−0.1
FH to their backhand · rally+1.4±2.4±0.0+1.4
FH to the middle · return+1.3±1.8−0.1+1.4

Avoid

ShotEdgeOwnTheirs
FH to their backhand · return +1−1.7±3.3−2.9+1.2
BH to their backhand · return−1.5±2.6−2.4+0.9
FH to their forehand · return−1.4±3.3−2.7+1.2
BH to the middle · rally−1.3±1.5−2.8+1.5
BH to their backhand · serve +1−1.3±2.6−2.0+0.7

Against Maya Joint-like opponents

Caroline Wozniacki vMatchesServe pts wonReturn pts won
All charted opponents–59.8%48.8%
Players most similar to Maya Joint6 59.2%47.9%

Similar by tactical fingerprint: Jasmine Paolini, Shuai Zhang, Robin Montgomery, Yue Yuan, Bernarda Pera, Rebecca Marino, Irina Camelia Begu, Anett Kontaveit, Garbine Muguruza, Andrea Petkovic. When two players have rarely met, their records against these lookalikes fill the gap.