RallyIQ

Game plan

Petra Kvitova v Mona Barthel

Every number combines what Petra Kvitova does well with what Mona Barthel allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Petra Kvitova wins, best of 3 83%90%: 57%–96% · best of 5: 89%
Serve points won 61.0% / 53.7% Petra / Mona · tour 56.3%
Strengths only, no similarity priors 84%serve 61.1% / 53.7%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Petra Kvitova's record against Mona Barthel's tactical lookalikes and in their charted head-to-heads (lookalikes: −3.0 on serve, −3.7 on return vs expectation (276 points); head-to-head: +6.2 on serve, +9.9 on return vs expectation (100 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

CareerPetraMona
Direction choice+0.13 ±0.04
better than 77%
+0.20 ±0.18
better than 84%
Shot selection+0.33 ±0.07
better than 82%
+0.21 ±0.31
better than 68%
Execution−0.96 ±0.32
better than 18%
−0.27 ±1.34
better than 45%

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.

Petra Kvitova serving

Deuce court

1st serveNowPetra winsv MonaMatchupOptimal
Wide42%72%62%68.6%±7.851% ▲
Body12%57%55%55.0%±10.30% ▼
T46%66%73%71.3%±7.949% ▲

Optimal v Mona Barthel: +0.7±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowPetra winsv MonaMatchupOptimal
Wide54%71%66%71.1%±7.269% ▲
Body8%54%51%49.5%±12.10% ▼
T38%73%59%68.4%±7.731% ▼

Optimal v Mona Barthel: +1.2±0.8 per 100 first serves (faults included) over the current mix. Serving wide every time would read +2.9 per 100 first serves in before the returner adjusts.

Mona Barthel serving

Deuce court

1st serveNowMona winsv PetraMatchupOptimal
Wide38%71%66%70.4%±7.753% ▲
Body17%53%57%53.3%±10.72% ▼
T45%67%68%67.1%±8.445%

Optimal v Petra Kvitova: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMona winsv PetraMatchupOptimal
Wide47%57%67%58.2%±8.645% ▼
Body12%51%58%52.6%±12.10% ▼
T40%65%64%65.0%±8.355% ▲

Optimal v Petra Kvitova: +0.6±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.8 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.

Petra Kvitova returning

1st serve to the forehand

ReturnNowTourOwnv MonaValue
FH through the middle49%+4.2−1.4−1.0+1.8±2.5
FH crosscourt25%+5.3−0.7−0.4+4.3±3.5
FH down the line19%+1.5−5.1+2.9−0.7±4.1
FH slice through the middle4%−6.7−0.1+1.2−5.6±2.2
FH slice crosscourt1%−6.6−0.6±0.0−7.3±1.7

Lean FH crosscourt: +2.7±3.0 per 100 returns v the current mix (1275 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv MonaValue
BH through the middle47%+6.0−1.9+1.7+5.8±2.3
BH crosscourt26%+7.7−2.2+0.9+6.4±3.0
BH down the line13%+2.2±0.0+0.3+2.4±4.2
BH slice through the middle7%−6.2+0.2−0.3−6.3±2.1
BH slice crosscourt3%−4.2−4.5+0.4−8.3±2.6

Lean BH crosscourt: +2.6±2.5 per 100 returns v the current mix (1499 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MonaValue
FH crosscourt43%+0.5−0.4+1.3+1.4±3.6
FH through the middle37%−3.2−4.5−0.8−8.5±2.9
FH down the line20%−0.6−1.3+2.0+0.1±5.2

Lean FH crosscourt: +3.9±2.5 per 100 returns v the current mix (419 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv MonaValue
BH through the middle44%−2.6+0.5−0.5−2.6±2.4
BH crosscourt41%+1.5+1.2−0.8+1.9±2.8
BH down the line15%−0.5+1.0+1.6+2.0±5.0
BH slice through the middle1%−11.7−0.7±0.0−12.4±1.0

Lean BH down the line: +2.2±4.6 per 100 returns v the current mix (593 returns charted, inside the 90% margin)

Mona Barthel returning

1st serve to the forehand

ReturnNowTourOwnv PetraValue
FH through the middle45%+4.2+0.6−1.9+2.9±2.5
FH down the line26%+1.5+3.3−5.1−0.3±4.2
FH crosscourt21%+5.3−1.9−0.2+3.3±3.6
FH slice through the middle8%−6.7−0.6−2.0−9.4±2.1

Lean FH crosscourt: +2.2±3.3 per 100 returns v the current mix (121 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv PetraValue
BH through the middle42%+6.0+0.6+0.8+7.5±2.3
BH crosscourt33%+7.7−0.9+2.7+9.5±3.0
BH down the line13%+2.2−0.9−0.5+0.8±3.7
BH slice crosscourt7%−4.2+0.4+0.2−3.6±2.5
BH slice through the middle5%−6.2+0.1−2.8−8.9±1.8

Lean BH crosscourt: +3.8±2.3 per 100 returns v the current mix (116 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv PetraValue
BH crosscourt49%+1.5+0.5−2.8−0.8±3.1
BH through the middle38%−2.6−2.1−2.3−7.0±2.1
BH down the line12%−0.5+0.9−3.7−3.3±3.9

Lean BH crosscourt: +2.7±1.8 per 100 returns v the current mix (65 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.

Petra Kvitova

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+1.6±3.3±0.0+1.7
BH to their forehand · rally+1.3±3.7−1.9+3.3
FH to their backhand · rally+0.9±3.1−1.7+2.6
BH to the middle · return+0.7±2.1−1.0+1.7
FH to their forehand · return+0.4±3.6−2.2+2.6
BH to their backhand · rally−0.1±2.9−3.1+2.9

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−4.8±2.2−3.2−1.6
FH to their forehand · rally−4.7±2.7−4.7−0.1
BH to the middle · rally−4.7±2.1−2.9−1.8
FH to the middle · serve +1−2.5±2.3−1.9−0.6
BH to their backhand · rally−0.1±2.9−3.1+2.9

Mona Barthel

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+2.5±3.4+2.5±0.0
FH to the middle · return+0.7±2.3+2.4−1.6
BH to their forehand · rally+0.7±3.6+1.9−1.2
FH to their forehand · rally+0.4±2.9+2.4−2.0
FH to the middle · rally+0.1±2.1+0.9−0.8
BH to the middle · return−1.4±2.0−0.1−1.2

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−7.3±3.5−5.3−2.0
BH to their backhand · serve +1−5.1±3.3−0.1−4.9
BH to their backhand · rally−4.0±2.9+1.6−5.6
FH to their backhand · rally−3.2±3.1−2.7−0.5
BH to their backhand · return−2.9±3.0−0.8−2.1

Against Mona Barthel-like opponents

Petra Kvitova vMatchesServe pts wonReturn pts won
All charted opponents–60.7%42.9%
Players most similar to Mona Barthel2 56.1%40.5%
Mona Barthel (charted head-to-head)1 67.3%56.3%

Similar by tactical fingerprint: Karolina Pliskova, Leylah Fernandez, Elise Mertens, Ekaterina Alexandrova, Sorana Cirstea, Victoria Azarenka, Veronika Kudermetova, Vera Zvonareva, Daniela Hantuchova, Nadia Petrova. When two players have rarely met, their records against these lookalikes fill the gap.

Charted head-to-head