RallyIQ

Game plan

Karolina Muchova v Mayar Sherif

Every number combines what Karolina Muchova does well with what Mayar Sherif allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Karolina Muchova wins, best of 3 99%90%: 93%–100% · best of 5: 100%
Serve points won 69.7% / 52.6% Karolina / Mayar · tour 56.4%
Strengths only, no similarity priors 98%serve 70.2% / 53.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Karolina Muchova's record against Mayar Sherif's tactical lookalikes and in their charted head-to-heads (lookalikes: −4.2 on serve, +5.2 on return vs expectation (431 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

CareerKarolinaMayar
Direction choice−0.01 ±0.05
better than 52%
+0.12 ±0.14
better than 76%
Shot selection−0.17 ±0.09
better than 30%
+0.77 ±0.25
better than 99%
Execution+0.22 ±0.28
better than 70%
−0.22 ±0.71
better than 47%
Points left on the table2.88 ±0.08
lower than 18%
2.53 ±0.18
lower than 63%

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.

Karolina Muchova serving

Deuce court

1st serveNowKarolina winsv MayarMatchupOptimal
Wide40%68%67%69.8%±6.440%
Body22%58%63%63.9%±8.17% ▼
T38%74%67%73.6%±7.053% ▲

Optimal v Mayar Sherif: +1.4±0.9 per 100 first serves (faults included) over the current mix. Serving T every time would read +3.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowKarolina winsv MayarMatchupOptimal
Wide48%68%64%66.7%±6.463% ▲
Body14%57%55%55.5%±10.20% ▼
T39%67%66%69.2%±8.237% ▼

Optimal v Mayar Sherif: +0.9±1.0 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.

Mayar Sherif serving

Deuce court

1st serveNowMayar winsv KarolinaMatchupOptimal
Wide46%65%65%63.7%±6.561% ▲
Body22%54%58%54.4%±8.86% ▼
T32%63%69%63.9%±7.733%

Optimal v Karolina Muchova: +0.8±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMayar winsv KarolinaMatchupOptimal
Wide55%57%66%57.7%±6.554% ▼
Body13%50%54%47.9%±10.60% ▼
T31%66%64%65.1%±8.046% ▲

Optimal v Karolina Muchova: +1.0±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +6.4 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.

Karolina Muchova returning

1st serve to the forehand

ReturnNowTourOwnv MayarValue
FH through the middle41%+4.2+1.1+0.8+6.1±2.5
FH slice through the middle18%−6.7+3.0−1.6−5.3±2.2
FH crosscourt15%+5.3−0.7+1.5+6.1±4.0
FH down the line14%+1.5−2.9+2.5+1.1±4.4
FH slice crosscourt9%−6.6+2.2+0.2−4.2±2.2

Lean FH crosscourt: +4.2±3.7 per 100 returns v the current mix (1182 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MayarValue
BH through the middle46%+6.0−0.4+0.4+6.0±2.2
BH crosscourt20%+7.7+0.9+5.1+13.8±3.2
BH slice through the middle14%−6.2+0.2−0.5−6.6±2.0
BH down the line12%+2.2−1.2−3.3−2.3±4.4
BH slice crosscourt5%−4.2−0.8±0.0−5.0±2.1

Lean BH crosscourt: +10.1±2.8 per 100 returns v the current mix (1188 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MayarValue
FH through the middle43%−3.2−1.4+1.3−3.3±3.0
FH crosscourt28%+0.5−0.4+2.4+2.6±4.3
FH down the line21%−0.6−1.9−1.7−4.2±5.2
FH slice through the middle5%−15.2+0.1±0.0−15.1±1.5
FH slice crosscourt3%−14.9+1.3±0.0−13.6±1.3

Lean FH crosscourt: +5.3±3.5 per 100 returns v the current mix (247 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv MayarValue
BH through the middle40%−2.6+1.0+0.2−1.4±2.5
BH crosscourt31%+1.5−0.4−0.4+0.7±3.4
BH down the line20%−0.5−0.3+2.3+1.5±4.8
FH inside-in5%+0.7−1.9+2.4+1.3±4.5
FH through the middle3%−2.7+1.7+1.3+0.3±2.5

Lean BH down the line: +1.5±4.1 per 100 returns v the current mix (582 returns charted, inside the 90% margin)

Mayar Sherif returning

1st serve to the forehand

ReturnNowTourOwnv KarolinaValue
FH through the middle39%+4.2+2.0−0.1+6.0±2.6
FH crosscourt33%+5.3+1.5−1.4+5.5±3.9
FH down the line13%+1.5+1.0−0.7+1.8±3.9
FH slice crosscourt7%−6.6+0.6−2.5−8.5±2.5
FH slice through the middle7%−6.7−0.3−1.7−8.7±2.1

Lean FH through the middle: +2.9±2.1 per 100 returns v the current mix (150 returns charted)

1st serve to the backhand

ReturnNowTourOwnv KarolinaValue
BH through the middle54%+6.0+0.9+0.1+7.0±2.2
BH crosscourt33%+7.7+2.2+0.3+10.2±3.0
BH down the line8%+2.2−2.0+0.2+0.4±3.8
BH slice through the middle5%−6.2−0.9−1.1−8.2±2.1

Lean BH crosscourt: +3.5±2.4 per 100 returns v the current mix (173 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv KarolinaValue
FH through the middle48%−3.2+0.1+0.5−2.6±2.5
FH crosscourt41%+0.5+0.2−3.9−3.2±3.7
FH down the line11%−0.6+1.7−1.0+0.1±3.7

Lean FH through the middle: −0.1±2.0 per 100 returns v the current mix (44 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv KarolinaValue
BH through the middle45%−2.6−0.5−0.7−3.8±2.3
BH crosscourt26%+1.5−2.0−1.3−1.9±2.9
FH inside-out15%+1.4−0.9−1.0−0.6±3.5
FH through the middle8%−2.7−0.5+0.5−2.6±1.7
BH down the line6%−0.5+0.6−2.0−1.9±3.9

Lean BH crosscourt: +0.7±2.5 per 100 returns v the current mix (78 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.

Karolina Muchova

Favour

ShotEdgeOwnTheirs
FH to their backhand · serve +1+7.3±4.7+3.2+4.1
BH to their backhand · rally+3.9±3.5+2.0+2.0
FH to the middle · return+3.9±3.2+0.8+3.1
BH to their backhand · return +1+3.5±4.4+1.4+2.2
BH to their backhand · return+2.8±4.0−0.6+3.4
FH to their backhand · return +1+2.6±5.0+1.7+0.9

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return−2.5±5.5−1.5−0.9
BH to the middle · rally−0.6±2.6−0.7+0.1
FH to their forehand · serve +1±0.0±4.6+0.2−0.1
BH to the middle · serve +1+0.3±3.1+0.4−0.1
FH to their backhand · rally+0.3±4.1−1.6+1.9

Mayar Sherif

Favour

ShotEdgeOwnTheirs
BH to their backhand · serve +1+3.0±4.3+2.5+0.5
BH to their backhand · return +1+1.9±4.0+1.9−0.1
FH to the middle · return+1.3±3.2+1.8−0.5
BH to the middle · serve +1+1.0±3.1−0.2+1.2
FH to the middle · rally+1.0±2.8+1.9−0.9
FH to their forehand · serve +1+0.6±4.5+3.0−2.4

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−6.8±5.2−3.9−2.9
FH to their backhand · return +1−6.1±4.9−4.1−2.1
FH to their forehand · return−5.7±5.1−2.7−2.9
FH to their forehand · rally−3.9±3.6−1.8−2.1
BH to the middle · rally−3.0±2.6−1.5−1.6

Against Mayar Sherif-like opponents

Karolina Muchova vMatchesServe pts wonReturn pts won
All charted opponents–61.6%42.9%
Players most similar to Mayar Sherif3 57.7%47.8%

Similar by tactical fingerprint: Cristina Bucsa, Xin Yu Wang, Tamara Zidansek, Bianca Andreescu, Anhelina Kalinina, Petra Martic, Daria Saville, Kiki Bertens, Svetlana Kuznetsova. When two players have rarely met, their records against these lookalikes fill the gap.