RallyIQ

Game plan

Jessica Pegula v Amelie Mauresmo

Every number combines what Jessica Pegula does well with what Amelie Mauresmo 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 46%90%: 18%–76% · best of 5: 45%
Serve points won 61.1% / 61.9% Jessica / Amelie · tour 58.1%
Strengths only, no similarity priors 50%serve 61.4% / 61.5%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Amelie Mauresmo's tactical lookalikes and in their charted head-to-heads (lookalikes: −11.6 on serve, −13.7 on return vs expectation (90 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

CareerJessicaAmelie
Direction choice−0.15 ±0.04
better than 25%
+0.31 ±0.13
better than 95%
Shot selection−0.24 ±0.07
better than 26%
−0.31 ±0.21
better than 21%
Execution+0.29 ±0.30
better than 72%
+0.61 ±0.36
better than 82%
Points left on the table2.72 ±0.06
lower than 31%
2.65 ±0.21
lower than 43%

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 AmelieMatchupOptimal
Wide31%67%65%66.5%±4.946% ▲
Body29%62%58%62.3%±7.514% ▼
T40%74%68%73.4%±5.140%

Optimal v Amelie Mauresmo: +0.5±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJessica winsv AmelieMatchupOptimal
Wide29%66%65%65.8%±5.738% ▲
Body22%61%69%72.6%±7.328% ▲
T49%63%62%61.2%±5.534% ▼

Optimal v Amelie Mauresmo: +0.4±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +7.5 per 100 first serves in before the returner adjusts.

Amelie Mauresmo serving

Deuce court

1st serveNowAmelie winsv JessicaMatchupOptimal
Wide56%66%65%64.9%±4.859% ▲
Body10%61%55%58.7%±8.60% ▼
T35%73%70%75.0%±5.241% ▲

Optimal v Jessica Pegula: +0.3±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAmelie winsv JessicaMatchupOptimal
Wide46%64%64%62.7%±5.561% ▲
Body7%51%54%48.8%±10.00% ▼
T47%65%62%63.0%±5.439% ▼

Optimal v Jessica Pegula: +0.7±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.1 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 AmelieValue
FH through the middle49%+4.2−1.8−0.3+2.0±2.0
FH crosscourt19%+5.3+1.4+2.1+8.9±3.6
FH slice through the middle13%−6.7+0.3+0.9−5.6±2.3
FH down the line11%+1.5+0.4−1.5+0.4±4.2
FH slice crosscourt4%−6.6−0.2−0.9−7.7±2.6

Lean FH crosscourt: +7.5±3.1 per 100 returns v the current mix (1257 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AmelieValue
BH through the middle42%+6.0−3.0−1.9+1.2±2.0
BH crosscourt24%+7.7+0.5−2.3+5.9±3.0
BH slice through the middle12%−6.2−0.2−0.7−7.1±2.4
BH down the line12%+2.2−1.4+0.9+1.6±4.3
BH slice crosscourt6%−4.2−0.9+0.7−4.4±2.8

Lean BH crosscourt: +5.4±2.5 per 100 returns v the current mix (1269 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv AmelieValue
FH through the middle46%−3.2−1.4−0.6−5.2±2.6
FH crosscourt27%+0.5+0.2−2.1−1.3±4.1
FH down the line23%−0.6+2.7−1.4+0.7±5.1
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: +3.9±4.2 per 100 returns v the current mix (359 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv AmelieValue
BH through the middle48%−2.6−1.0+0.8−2.8±2.3
BH crosscourt34%+1.5−6.1+1.3−3.3±3.2
BH down the line17%−0.5−0.4−0.1−1.0±5.1
BH slice through the middle2%−11.7−0.9−0.1−12.7±1.7

Lean BH down the line: +1.8±4.5 per 100 returns v the current mix (637 returns charted, inside the 90% margin)

Amelie Mauresmo returning

1st serve to the forehand

ReturnNowTourOwnv JessicaValue
FH through the middle38%+4.2+0.2+0.4+4.7±2.0
FH down the line19%+1.5+3.1−1.3+3.4±3.9
FH slice through the middle18%−6.7+1.4+0.8−4.5±2.3
FH crosscourt13%+5.3+0.9±0.0+6.2±3.6
FH slice crosscourt9%−6.6+1.4+0.2−5.1±2.8

Lean FH crosscourt: +4.3±3.4 per 100 returns v the current mix (580 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JessicaValue
BH slice through the middle49%−6.2+1.1−1.1−6.3±2.2
BH slice crosscourt22%−4.2+4.0−2.5−2.6±3.0
BH through the middle9%+6.0−3.6−0.2+2.2±2.3
BH slice down the line9%−12.5+3.3−1.4−10.6±3.6
BH down the line6%+2.2+1.4−3.2+0.3±4.0
BH crosscourt4%+7.7+1.8−1.5+8.0±2.8

Lean BH crosscourt: +12.1±3.0 per 100 returns v the current mix (412 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JessicaValue
FH down the line31%−0.6+4.2−0.8+2.8±4.8
FH through the middle31%−3.2+0.4−0.7−3.5±2.6
FH crosscourt28%+0.5+0.4+2.1+3.0±3.9
FH slice through the middle5%−15.2+2.2−0.1−13.2±1.8
FH slice crosscourt4%−14.9+0.6+2.6−11.7±2.1

Lean FH crosscourt: +3.6±3.2 per 100 returns v the current mix (201 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JessicaValue
BH through the middle27%−2.6−0.5+0.1−3.0±2.3
BH slice through the middle19%−11.7−0.7±0.0−12.4±1.7
BH crosscourt15%+1.5−1.5−0.5−0.6±3.0
BH down the line15%−0.5+0.1−0.8−1.2±4.6
BH slice crosscourt13%−7.5+0.6+0.1−6.8±2.4

Lean BH crosscourt: +3.9±2.7 per 100 returns v the current mix (246 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 on grass. Each player's grass 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 backhand · return +1+8.5±4.6+4.1+4.4
FH to their forehand · return +1+4.5±5.1+3.5+1.1
BH to the middle · return +1+4.3±3.4+2.1+2.1
BH to the middle · rally+2.7±3.1+0.4+2.4
BH to their forehand · return +1+2.4±6.0+1.7+0.8
FH to their backhand · return +1+2.2±5.7+2.5−0.3

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−9.5±5.4−4.1−5.4
BH to the middle · return−8.9±3.3−4.4−4.6
FH to their backhand · rally−7.9±5.0−2.8−5.1
BH to their backhand · serve +1−7.7±4.5−4.9−2.8
BH to their backhand · return−3.8±4.7−1.4−2.3

Amelie Mauresmo

Favour

ShotEdgeOwnTheirs
FH slice to their forehand · return+4.0±4.2+1.6+2.4
BH to their backhand · rally+3.3±4.3+5.0−1.7
FH to their forehand · rally+3.2±4.5+2.5+0.7
FH slice to the middle · return+3.0±3.4+0.8+2.2
BH to the middle · serve +1+1.7±3.5+0.6+1.1
BH to their forehand · serve +1+1.5±5.1+2.7−1.2

Avoid

ShotEdgeOwnTheirs
BH to their forehand · return−5.9±6.2−3.0−3.0
BH to the middle · return−4.4±3.5−4.6+0.2
BH to their backhand · return +1−4.0±4.6+1.4−5.4
FH to their backhand · return +1−3.1±5.6+1.5−4.6
BH to the middle · return +1−2.9±3.5+0.2−3.1

Against Amelie Mauresmo-like opponents

Jessica Pegula vMatchesServe pts wonReturn pts won
All charted opponents–58.5%43.9%
Players most similar to Amelie Mauresmo1 48.9%30.4%

Similar by tactical fingerprint: Mirra Andreeva, Elise Mertens, Kim Clijsters, Svetlana Kuznetsova, Christina Mchale, Saisai Zheng, Magdalena Rybarikova, Francesca Schiavone, Roberta Vinci, Martina Hingis. When two players have rarely met, their records against these lookalikes fill the gap.