RallyIQ

Game plan

Jessica Pegula v Dominika Cibulkova

Every number combines what Jessica Pegula does well with what Dominika Cibulkova allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jessica Pegula wins, best of 3 90%90%: 69%–98% · best of 5: 94%
Serve points won 60.3% / 50.7% Jessica / Dominika · tour 55.0%
Strengths only, no similarity priors 88%serve 60.2% / 51.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Jessica Pegula's record against Dominika Cibulkova's tactical lookalikes and in their charted head-to-heads (lookalikes: +1.4 on serve, +6.0 on return vs expectation (321 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

CareerJessicaDominika
Direction choice−0.15 ±0.04
better than 25%
−0.17 ±0.12
better than 22%
Shot selection−0.24 ±0.07
better than 26%
+0.17 ±0.10
better than 62%
Execution+0.29 ±0.30
better than 72%
−0.60 ±0.39
better than 29%
Points left on the table2.72 ±0.06
lower than 31%
2.53 ±0.14
lower than 61%

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.

Jessica Pegula serving

Deuce court

1st serveNowJessica winsv DominikaMatchupOptimal
Wide31%67%67%67.9%±5.346% ▲
Body29%62%60%64.6%±6.729%
T40%74%69%74.5%±4.925% ▼

Optimal v Dominika Cibulkova: +0.4±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJessica winsv DominikaMatchupOptimal
Wide29%66%70%70.2%±5.844% ▲
Body22%61%58%62.7%±7.67% ▼
T49%63%70%68.5%±5.449%

Optimal v Dominika Cibulkova: +0.8±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.5 per 100 first serves in before the returner adjusts.

Dominika Cibulkova serving

Deuce court

1st serveNowDominika winsv JessicaMatchupOptimal
Wide29%62%65%61.2%±6.044% ▲
Body37%58%55%55.1%±5.922% ▼
T34%61%70%63.4%±6.234%

Optimal v Jessica Pegula: +0.5±0.9 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 serveNowDominika winsv JessicaMatchupOptimal
Wide25%62%64%60.6%±6.741% ▲
Body31%55%54%53.1%±6.930%
T44%58%62%55.9%±5.729% ▼

Optimal v Jessica Pegula: +0.4±0.8 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.

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.

Jessica Pegula returning

1st serve to the forehand

ReturnNowTourOwnv DominikaValue
FH through the middle49%+4.2−1.8−1.9+0.5±1.9
FH crosscourt19%+5.3+1.4+2.9+9.7±3.5
FH slice through the middle13%−6.7+0.3−0.7−7.2±2.1
FH down the line11%+1.5+0.4+4.4+6.3±4.3
FH slice crosscourt4%−6.6−0.2−0.2−7.0±2.4

Lean FH crosscourt: +8.4±3.0 per 100 returns v the current mix (1257 returns charted)

1st serve to the backhand

ReturnNowTourOwnv DominikaValue
BH through the middle42%+6.0−3.0−0.8+2.2±1.9
BH crosscourt24%+7.7+0.5+2.1+10.3±2.8
BH slice through the middle12%−6.2−0.2+0.6−5.8±2.1
BH down the line12%+2.2−1.4+4.3+5.0±4.3
BH slice crosscourt6%−4.2−0.9+0.5−4.6±2.7

Lean BH crosscourt: +7.8±2.4 per 100 returns v the current mix (1269 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv DominikaValue
FH through the middle46%−3.2−1.4−2.7−7.2±2.8
FH crosscourt27%+0.5+0.2−1.1−0.4±4.3
FH down the line23%−0.6+2.7+1.5+3.6±5.2
FH slice through the middle2%−15.2−1.2±0.0−16.4±1.3
FH slice down the line2%−14.1−1.7±0.0−15.8±1.7

Lean FH down the line: +6.8±4.4 per 100 returns v the current mix (359 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv DominikaValue
BH through the middle48%−2.6−1.0−2.4−6.0±2.1
BH crosscourt34%+1.5−6.1+2.9−1.8±3.1
BH down the line17%−0.5−0.4+3.5+2.6±5.1
BH slice through the middle2%−11.7−0.9±0.0−12.6±1.3

Lean BH down the line: +5.8±4.5 per 100 returns v the current mix (637 returns charted)

Dominika Cibulkova returning

1st serve to the forehand

ReturnNowTourOwnv JessicaValue
FH through the middle56%+4.2−0.8+0.4+3.7±2.1
FH crosscourt25%+5.3+1.7±0.0+7.0±3.6
FH down the line17%+1.5−5.3−1.3−5.1±4.1
FH slice through the middle2%−6.7−1.4+0.8−7.2±2.0

Lean FH crosscourt: +4.2±3.0 per 100 returns v the current mix (366 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JessicaValue
BH through the middle44%+6.0−0.9−0.2+5.0±2.0
BH crosscourt21%+7.7+1.6−1.5+7.8±3.1
BH slice through the middle18%−6.2+0.4−1.1−7.0±2.5
BH down the line8%+2.2+0.4−3.2−0.7±4.0
BH slice crosscourt6%−4.2+0.2−2.5−6.4±2.9

Lean BH crosscourt: +6.1±2.7 per 100 returns v the current mix (358 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JessicaValue
FH through the middle53%−3.2+0.7−0.7−3.2±2.6
FH crosscourt26%+0.5+1.1+2.1+3.7±3.8
FH down the line22%−0.6+2.6−0.8+1.2±4.7

Lean FH crosscourt: +4.1±3.3 per 100 returns v the current mix (139 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JessicaValue
BH through the middle41%−2.6−1.4+0.1−3.8±2.2
BH crosscourt39%+1.5−0.6−0.5+0.4±3.0
FH through the middle7%−2.7−1.0−0.7−4.4±2.0
BH down the line6%−0.5−1.0−0.8−2.3±3.9
FH inside-in4%+0.7+1.7+2.1+4.5±3.2

Lean BH crosscourt: +2.1±2.1 per 100 returns v the current mix (181 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 clay. Each player's clay record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Jessica Pegula

Favour

ShotEdgeOwnTheirs
BH to their forehand · return+5.1±5.3−2.9+8.1
FH to their backhand · rally+3.2±4.0−0.2+3.4
FH to their backhand · serve +1+3.0±4.7−0.3+3.3
BH to their forehand · return +1+2.8±6.2+2.8±0.0
BH to their backhand · return+2.5±3.7−0.8+3.4
BH to the middle · serve +1+2.1±2.9+0.3+1.7

Avoid

ShotEdgeOwnTheirs
BH to the middle · return−8.8±2.6−3.8−5.0
FH to the middle · serve +1−6.4±3.1−2.6−3.8
FH to the middle · return−6.4±2.8−2.5−3.9
FH to the middle · return +1−1.9±3.3−0.1−1.8
FH to the middle · rally−1.6±2.8+0.1−1.7

Dominika Cibulkova

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+3.4±3.4+1.9+1.4
BH to the middle · return +1+2.1±3.1+1.2+0.9
FH to their backhand · return +1+2.0±4.9+5.5−3.5
BH to the middle · rally+1.0±2.6+2.0−1.1
FH to the middle · serve +1+0.7±3.1+0.5+0.2
FH to the middle · rally+0.6±2.6−0.1+0.7

Avoid

ShotEdgeOwnTheirs
BH to their backhand · return−7.3±3.9−3.4−4.0
FH to their backhand · serve +1−6.7±4.5−5.0−1.7
BH to their forehand · return−5.9±5.4−3.8−2.2
BH to their forehand · rally−4.0±5.2−1.8−2.3
BH to their forehand · return +1−3.4±6.1−1.1−2.3

Against Dominika Cibulkova-like opponents

Jessica Pegula vMatchesServe pts wonReturn pts won
All charted opponents–58.5%43.9%
Players most similar to Dominika Cibulkova2 61.1%50.3%

Similar by tactical fingerprint: Alexandra Eala, Anna Blinkova, Ashlyn Krueger, Jasmine Paolini, Jaqueline Cristian, Maria Sakkari, Robin Montgomery, Nao Hibino, R. When two players have rarely met, their records against these lookalikes fill the gap.