RallyIQ

Game plan

Jelena Dokic v Naomi Osaka

Every number combines what Jelena Dokic does well with what Naomi Osaka allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jelena Dokic wins, best of 3 12%90%: 3%–35% · best of 5: 7%
Serve points won 54.8% / 63.8% Jelena / Naomi · tour 56.3%
Strengths only, no similarity priors 12%serve 54.7% / 63.6%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Jelena Dokic's record against Naomi Osaka's tactical lookalikes and in their charted head-to-heads (lookalikes: +0.9 on serve, −1.9 on return vs expectation (226 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

CareerJelenaNaomi
Direction choice+0.52 ±0.09
better than 99%
+0.15 ±0.06
better than 81%
Shot selection+0.15 ±0.13
better than 60%
+0.22 ±0.05
better than 70%
Execution−1.44 ±0.86
better than 12%
−0.20 ±0.34
better than 48%
Points left on the table1.89 ±0.16
lower than 99%
2.33 ±0.09
lower than 84%

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.

Jelena Dokic serving

Deuce court

1st serveNowJelena winsv NaomiMatchupOptimal
Wide45%66%70%70.4%±7.051% ▲
Body14%52%58%52.4%±11.00% ▼
T41%64%72%68.9%±7.649% ▲

Optimal v Naomi Osaka: +0.5±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJelena winsv NaomiMatchupOptimal
Wide41%67%68%69.4%±7.937% ▼
Body8%55%56%55.4%±12.80% ▼
T51%62%68%66.0%±7.663% ▲

Optimal v Naomi Osaka: +0.5±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.8 per 100 first serves in before the returner adjusts.

Naomi Osaka serving

Deuce court

1st serveNowNaomi winsv JelenaMatchupOptimal
Wide44%75%74%81.8%±5.359% ▲
Body13%62%65%68.7%±11.00% ▼
T43%75%73%79.2%±6.041% ▼

Optimal v Jelena Dokic: +0.9±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowNaomi winsv JelenaMatchupOptimal
Wide39%74%68%75.6%±7.154% ▲
Body11%60%57%61.2%±12.20% ▼
T50%70%67%72.2%±7.046% ▼

Optimal v Jelena Dokic: +0.9±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.3 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.

Jelena Dokic returning

1st serve to the forehand

ReturnNowTourOwnv NaomiValue
FH through the middle50%+4.2−0.5−0.7+3.0±2.5
FH crosscourt31%+5.3+0.1−3.2+2.3±3.9
FH down the line19%+1.5−2.6−2.7−3.7±4.2

Lean FH through the middle: +1.5±1.9 per 100 returns v the current mix (148 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv NaomiValue
BH through the middle37%+6.0−2.2−2.7+1.1±2.4
BH crosscourt34%+7.7−0.7−0.9+6.1±3.3
BH down the line20%+2.2−0.7−4.3−2.9±4.2
BH slice crosscourt5%−4.2+0.5−3.4−7.1±2.5
BH slice through the middle4%−6.2−0.9+0.2−6.9±2.0

Lean BH crosscourt: +4.9±2.5 per 100 returns v the current mix (121 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv NaomiValue
FH crosscourt62%+0.5+2.4−5.4−2.5±3.9
FH through the middle21%−3.2+0.6+0.6−2.0±2.5
FH down the line17%−0.6−2.5+1.8−1.3±4.3

Lean FH down the line: +0.9±4.4 per 100 returns v the current mix (103 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv NaomiValue
BH crosscourt57%+1.5−0.8+0.8+1.5±3.1
BH through the middle25%−2.6+0.2+0.9−1.6±2.1
BH down the line18%−0.5+1.1+3.1+3.7±4.4

Lean BH crosscourt: +0.4±1.7 per 100 returns v the current mix (76 returns charted, inside the 90% margin)

Naomi Osaka returning

1st serve to the forehand

ReturnNowTourOwnv JelenaValue
FH through the middle51%+4.2−1.4−1.9+0.9±2.5
FH down the line28%+1.5−1.5+4.6+4.7±4.1
FH crosscourt17%+5.3−1.9−2.5+0.9±4.0
FH slice through the middle3%−6.7−1.1−0.6−8.5±2.1
FH slice crosscourt1%−6.6−2.6±0.0−9.2±1.6

Lean FH down the line: +3.2±3.3 per 100 returns v the current mix (1120 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JelenaValue
BH through the middle51%+6.0−0.9−0.6+4.5±2.4
BH crosscourt28%+7.7+2.3−0.7+9.3±3.2
BH down the line13%+2.2+0.1+2.2+4.4±4.4
BH slice through the middle4%−6.2−2.4−0.2−8.8±2.1
BH slice crosscourt2%−4.2−2.2±0.0−6.4±1.9

Lean BH crosscourt: +4.5±2.7 per 100 returns v the current mix (938 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JelenaValue
FH through the middle41%−3.2−1.4+1.3−3.2±2.9
FH crosscourt32%+0.5+2.3+0.5+3.3±4.3
FH down the line25%−0.6+0.8−3.8−3.6±4.9
FH slice through the middle2%−15.2+0.6±0.0−14.6±1.2

Lean FH crosscourt: +4.8±3.4 per 100 returns v the current mix (315 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JelenaValue
BH crosscourt46%+1.5+0.2−1.4+0.3±3.2
BH through the middle41%−2.6−1.3−1.9−5.8±2.5
BH down the line13%−0.5+1.4+0.6+1.4±5.1

Lean BH down the line: +3.5±4.8 per 100 returns v the current mix (558 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.

Jelena Dokic

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+3.7±3.3+0.9+2.8
FH to their forehand · return +1+2.8±3.4+1.4+1.3
FH to their backhand · serve +1+0.6±3.6−0.8+1.4
FH to their forehand · rally+0.1±2.5−0.8+0.8
BH to their backhand · serve +1−0.2±3.0+1.0−1.1
BH to their forehand · rally−0.3±3.9−0.4+0.1

Avoid

ShotEdgeOwnTheirs
BH to the middle · return−3.8±2.2−2.0−1.8
FH to their forehand · return−2.8±3.5+2.3−5.1
BH to their backhand · rally−2.8±2.4−2.9+0.1
FH to the middle · return−1.4±2.3−0.5−0.9
BH to their backhand · return +1−1.2±3.1−1.4+0.2

Naomi Osaka

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+3.1±3.4−1.0+4.0
BH to their forehand · return+2.1±4.0+0.1+2.0
FH to their backhand · return+0.2±3.7−1.3+1.5
BH to their backhand · serve +1−0.4±3.0−0.1−0.4
FH to their forehand · return +1−0.9±3.4−0.8−0.1
FH to the middle · rally−1.6±2.2−1.4−0.2

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−3.5±3.7−2.4−1.0
FH to their backhand · serve +1−3.3±3.6−2.4−0.9
BH to the middle · rally−3.1±2.0−1.1−1.9
BH to the middle · return−2.6±2.0−1.0−1.5
FH to their forehand · return−2.2±3.7−0.8−1.4

Against Naomi Osaka-like opponents

Jelena Dokic vMatchesServe pts wonReturn pts won
All charted opponents–53.4%39.9%
Players most similar to Naomi Osaka2 52.0%36.3%

Similar by tactical fingerprint: Karolina Pliskova, Ekaterina Alexandrova, Serena Williams, Shuai Zhang, Viktoria Hruncakova, Elena Gabriela Ruse, Veronika Kudermetova, Anett Kontaveit, Maria Sharapova, Lindsay Davenport. When two players have rarely met, their records against these lookalikes fill the gap.