RallyIQ

Game plan

Barbora Krejcikova v Naomi Osaka

Every number combines what Barbora Krejcikova 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

Barbora Krejcikova wins, best of 3 18%90%: 5%–43% · best of 5: 13%
Serve points won 57.3% / 64.3% Barbora / Naomi · tour 56.7%
Strengths only, no similarity priors 19%serve 57.3% / 64.1%

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. Both were charted enough in the last three seasons, so those carry the most weight. The result is then nudged by Barbora Krejcikova's record against Naomi Osaka's tactical lookalikes and in their charted head-to-heads (lookalikes: +0.1 on serve, −1.5 on return vs expectation (425 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

CareerBarboraNaomi
Direction choice+0.19 ±0.09
better than 84%
+0.15 ±0.06
better than 81%
Shot selection−0.47 ±0.17
better than 11%
+0.22 ±0.05
better than 70%
Execution−0.35 ±0.52
better than 40%
−0.20 ±0.34
better than 48%
Points left on the table2.49 ±0.13
lower than 66%
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.

Structural compatibility

Expected edge per 100 rally shots from style alone: Barbora Krejcikova −0.74, Naomi Osaka −2.47. 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.

Barbora Krejcikova serving

Deuce court

1st serveNowBarbora winsv NaomiMatchupOptimal
Wide41%70%70%74.0%±4.338% ▼
Body12%64%58%65.0%±7.40% ▼
T47%75%72%79.0%±4.162% ▲

Optimal v Naomi Osaka: +0.8±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowBarbora winsv NaomiMatchupOptimal
Wide51%67%68%70.2%±4.846% ▼
Body10%57%56%57.6%±8.90% ▼
T39%67%68%70.6%±5.054% ▲

Optimal v Naomi Osaka: +0.6±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.5 per 100 first serves in before the returner adjusts.

Naomi Osaka serving

Deuce court

1st serveNowNaomi winsv BarboraMatchupOptimal
Wide44%75%71%79.3%±3.859% ▲
Body13%62%58%62.4%±7.20% ▼
T43%75%67%74.4%±4.541% ▼

Optimal v Barbora Krejcikova: +1.3±0.8 per 100 first serves (faults included) over the current mix. Serving wide every time would read +4.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowNaomi winsv BarboraMatchupOptimal
Wide39%74%70%77.4%±4.654% ▲
Body11%60%56%60.1%±8.10% ▼
T50%70%62%68.1%±4.946% ▼

Optimal v Barbora Krejcikova: +1.0±0.8 per 100 first serves (faults included) over the current mix. Serving wide every time would read +6.6 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.

Barbora Krejcikova returning

1st serve to the forehand

ReturnNowTourOwnv NaomiValue
FH slice through the middle29%−6.7+3.4−0.5−3.7±2.1
FH through the middle24%+4.2−4.6−0.7−1.2±2.4
FH crosscourt17%+5.3−5.2−3.2−3.1±3.8
FH slice crosscourt15%−6.6+1.8±0.0−4.8±2.7
FH down the line11%+1.5−4.2−2.7−5.3±4.3

Lean FH through the middle: +2.3±2.1 per 100 returns v the current mix (564 returns charted)

1st serve to the backhand

ReturnNowTourOwnv NaomiValue
BH through the middle49%+6.0+0.1−2.7+3.4±2.0
BH crosscourt22%+7.7−0.4−0.9+6.4±3.2
BH down the line11%+2.2+0.7−4.3−1.5±4.3
BH slice through the middle10%−6.2−2.0+0.2−8.1±2.5
BH slice crosscourt4%−4.2+0.4−3.4−7.1±2.9

Lean BH crosscourt: +5.0±2.7 per 100 returns v the current mix (493 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv NaomiValue
FH through the middle47%−3.2−0.8+0.6−3.4±2.6
FH crosscourt36%+0.5−1.0−5.4−5.8±3.9
FH down the line17%−0.6−1.4+1.8−0.3±4.5

Lean FH down the line: +3.5±4.2 per 100 returns v the current mix (142 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv NaomiValue
BH through the middle47%−2.6−0.8+0.9−2.5±2.1
BH crosscourt38%+1.5−1.3+0.8+1.0±2.9
BH down the line12%−0.5+0.6+3.1+3.1±4.8
FH through the middle2%−2.7−1.4+0.6−3.5±1.6

Lean BH down the line: +3.6±4.5 per 100 returns v the current mix (281 returns charted, inside the 90% margin)

Naomi Osaka returning

1st serve to the forehand

ReturnNowTourOwnv BarboraValue
FH through the middle51%+4.2−1.4+0.2+2.9±2.1
FH down the line28%+1.5−1.5−3.1−3.0±3.9
FH crosscourt17%+5.3−1.9+1.1+4.5±3.9
FH slice through the middle3%−6.7−1.1+0.8−7.0±2.5
FH slice crosscourt1%−6.6−2.6+0.7−8.5±2.3

Lean FH crosscourt: +3.5±3.5 per 100 returns v the current mix (1120 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv BarboraValue
BH through the middle51%+6.0−0.9+0.4+5.6±1.9
BH crosscourt28%+7.7+2.3−1.9+8.1±2.9
BH down the line13%+2.2+0.1+1.4+3.6±4.3
BH slice through the middle4%−6.2−2.4−1.3−9.9±2.5
BH slice crosscourt2%−4.2−2.2−2.8−9.2±2.9

Lean BH crosscourt: +3.3±2.3 per 100 returns v the current mix (938 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv BarboraValue
FH through the middle41%−3.2−1.4−0.9−5.5±2.8
FH crosscourt32%+0.5+2.3+0.9+3.7±4.4
FH down the line25%−0.6+0.8+1.2+1.4±5.2
FH slice through the middle2%−15.2+0.6−1.3−15.9±1.7

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

2nd serve to the backhand

ReturnNowTourOwnv BarboraValue
BH crosscourt46%+1.5+0.2−2.1−0.4±3.0
BH through the middle41%−2.6−1.3−0.6−4.5±2.1
BH down the line13%−0.5+1.4−0.4+0.4±5.1

Lean BH down the line: +2.4±4.7 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 on hard. Each player's hard record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Barbora Krejcikova

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+7.5±3.7+5.1+2.5
BH to their forehand · serve +1+4.2±5.7+2.3+1.9
FH slice to their forehand · return+3.7±4.0+2.7+1.0
FH slice to the middle · return+2.5±2.9+2.6−0.1
FH to the middle · serve +1+2.0±2.8+1.3+0.7
BH slice to their backhand · return +1+1.4±4.2+1.8−0.3

Avoid

ShotEdgeOwnTheirs
FH to their forehand · return−11.6±4.3−5.2−6.4
FH to the middle · return−6.2±2.4−5.0−1.3
FH to the middle · rally−5.9±2.3−4.1−1.8
BH to the middle · return +1−5.3±2.8−5.4+0.1
BH to their backhand · return +1−5.2±3.9−5.6+0.4

Naomi Osaka

Favour

ShotEdgeOwnTheirs
BH to their forehand · return +1+3.8±5.8+1.8+2.0
BH to their forehand · return+0.3±4.8+0.2+0.1
BH to their backhand · return +1−0.2±3.6±0.0−0.3
BH to the middle · return−0.8±1.9−0.7−0.1
FH to the middle · serve +1−0.8±2.6±0.0−0.8
FH to their backhand · return−0.9±4.6−1.1+0.2

Avoid

ShotEdgeOwnTheirs
FH to their backhand · return +1−11.2±5.0−4.4−6.7
FH to their backhand · serve +1−6.2±4.0−4.0−2.2
FH to their backhand · rally−5.6±3.4−3.2−2.4
FH slice to the middle · rally−5.1±3.9−1.9−3.2
BH to their backhand · rally−4.4±2.6−0.3−4.2

Against Naomi Osaka-like opponents

Barbora Krejcikova vMatchesServe pts wonReturn pts won
All charted opponents–60.6%40.5%
Players most similar to Naomi Osaka2 60.8%39.4%

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.