RallyIQ

Game plan

Misaki Doi v Beatriz Haddad Maia

Every number combines what Misaki Doi does well with what Beatriz Haddad Maia allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Misaki Doi wins, best of 3 42%90%: 8%–85% · best of 5: 40%
Serve points won 56.8% / 58.4% Misaki / Beatriz · tour 58.1%
Strengths only, no similarity priors 42%serve 57.1% / 58.5%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Misaki Doi's record against Beatriz Haddad Maia's tactical lookalikes and in their charted head-to-heads (lookalikes: −3.0 on serve, +2.0 on return vs expectation (265 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

CareerMisakiBeatriz
Direction choice−0.10 ±0.11
better than 36%
−0.20 ±0.14
better than 16%
Shot selection+0.11 ±0.24
better than 56%
+0.38 ±0.13
better than 88%
Execution−0.93 ±0.51
better than 19%
+0.34 ±0.58
better than 74%
Points left on the table2.84 ±0.27
lower than 21%
2.98 ±0.22
lower than 12%

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.

Misaki Doi serving

Deuce court

1st serveNowMisaki winsv BeatrizMatchupOptimal
Wide23%69%66%69.5%±10.338% ▲
Body36%51%61%54.4%±10.121% ▼
T42%62%68%62.5%±9.641%

Optimal v Beatriz Haddad Maia: +0.9±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +8.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMisaki winsv BeatrizMatchupOptimal
Wide41%61%65%59.9%±10.141%
Body37%53%57%54.7%±10.622% ▼
T22%57%70%62.8%±10.737% ▲

Optimal v Beatriz Haddad Maia: +1.0±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.2 per 100 first serves in before the returner adjusts.

Beatriz Haddad Maia serving

Deuce court

1st serveNowBeatriz winsv MisakiMatchupOptimal
Wide31%62%65%60.6%±9.532%
Body34%55%60%57.5%±11.418% ▼
T35%60%66%58.5%±10.650% ▲

Optimal v Misaki Doi: +0.4±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowBeatriz winsv MisakiMatchupOptimal
Wide48%61%71%67.1%±9.948%
Body31%56%50%49.3%±11.616% ▼
T21%69%65%69.7%±10.036% ▲

Optimal v Misaki Doi: +1.1±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.6 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.

Misaki Doi returning

1st serve to the forehand

ReturnNowTourOwnv BeatrizValue
FH through the middle51%+4.2−3.5−0.4+0.2±3.0
FH crosscourt25%+5.3+2.5−7.3+0.4±4.2
FH slice through the middle17%−6.7+0.6−1.4−7.5±2.4
FH down the line7%+1.5−0.5+4.3+5.4±3.9

Lean FH crosscourt: +1.1±3.5 per 100 returns v the current mix (88 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv BeatrizValue
BH through the middle46%+6.0+0.5+2.5+9.0±2.6
BH crosscourt25%+7.7−0.9−1.4+5.4±3.7
BH down the line14%+2.2−1.3+4.2+5.0±4.3
BH slice through the middle12%−6.2+1.0−0.8−6.1±2.3
BH slice down the line3%−12.5+0.7−0.4−12.2±2.4

Lean BH through the middle: +3.9±1.8 per 100 returns v the current mix (174 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv BeatrizValue
BH crosscourt48%+1.5−2.1+5.3+4.8±3.6
BH through the middle46%−2.6−1.1+0.6−3.1±2.7
BH down the line7%−0.5−0.3−2.1−2.9±4.3

Lean BH crosscourt: +4.1±2.3 per 100 returns v the current mix (107 returns charted)

Beatriz Haddad Maia returning

1st serve to the forehand

ReturnNowTourOwnv MisakiValue
FH through the middle52%+4.2−1.8−0.4+1.9±3.0
FH down the line24%+1.5−4.0+0.4−2.1±4.7
FH crosscourt19%+5.3−0.4±0.0+4.9±4.2
FH slice through the middle5%−6.7+0.1+1.0−5.7±2.2

Lean FH crosscourt: +3.7±3.9 per 100 returns v the current mix (225 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv MisakiValue
BH through the middle48%+6.0−0.3+1.2+6.9±2.6
BH crosscourt23%+7.7−3.6−2.5+1.6±3.6
BH down the line17%+2.2−1.9+2.4+2.6±4.7
BH slice through the middle6%−6.2−2.2+1.0−7.4±2.3
BH slice crosscourt3%−4.2+0.8−0.3−3.8±2.0

Lean BH through the middle: +3.7±1.8 per 100 returns v the current mix (321 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MisakiValue
FH through the middle38%−3.2+2.2+0.1−0.8±3.1
FH crosscourt32%+0.5+0.1−2.5−1.8±4.4
FH down the line30%−0.6−4.0−0.1−4.7±5.0

Lean FH through the middle: +1.5±2.8 per 100 returns v the current mix (77 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MisakiValue
BH through the middle51%−2.6+2.2−0.4−0.8±2.8
BH crosscourt43%+1.5±0.0−2.5−1.0±3.4
BH down the line6%−0.5−0.4−2.7−3.6±4.3

Lean BH through the middle: +0.2±2.0 per 100 returns v the current mix (84 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 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.

Misaki Doi

Favour

ShotEdgeOwnTheirs
FH to their backhand · return+10.0±4.3+4.6+5.4
FH to their forehand · rally+3.8±5.0+0.7+3.1
BH to their forehand · serve +1+3.1±4.7−1.1+4.2
FH to their backhand · rally+2.9±5.0+1.0+1.9
BH to their forehand · return+2.6±5.6+0.4+2.2
BH to their forehand · rally+1.7±3.5−0.6+2.3

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−6.0±4.0−5.5−0.5
BH to the middle · rally−3.6±2.7−3.3−0.3
FH to the middle · rally−2.9±3.1−3.7+0.8
FH to their backhand · serve +1−1.3±5.4−1.5+0.2
FH to the middle · serve +1−1.3±3.3−2.6+1.3

Beatriz Haddad Maia

Favour

ShotEdgeOwnTheirs
FH to their backhand · return +1+4.4±3.9+1.9+2.5
BH to their forehand · return +1+4.2±5.6+1.4+2.8
BH to their forehand · rally+4.0±5.8+2.2+1.9
FH to their forehand · serve +1+4.0±4.6+1.3+2.7
FH to their forehand · rally+3.8±4.8+1.5+2.3
FH to the middle · serve +1+2.7±2.6+2.9−0.2

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−7.1±3.5−5.8−1.3
FH to their forehand · return−5.7±4.4−3.0−2.6
BH to their backhand · return−4.1±3.7−1.3−2.8
FH to the middle · return−3.0±4.0−2.8−0.2
BH to their forehand · return−1.6±4.2−1.0−0.7

Against Beatriz Haddad Maia-like opponents

Misaki Doi vMatchesServe pts wonReturn pts won
All charted opponents–52.5%43.5%
Players most similar to Beatriz Haddad Maia1 51.9%47.4%

Similar by tactical fingerprint: Suzan Lamens, Jasmine Paolini, Jil Teichmann, Sara Bejlek, Olga Danilovic, Xiyu Wang, Nao Hibino, Victoria Jimenez Kasintseva, Bernarda Pera, Anna Lena Friedsam. When two players have rarely met, their records against these lookalikes fill the gap.