RallyIQ

Game plan

Heather Watson v Jessica Pegula

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

Forecast

Heather Watson wins, best of 3 20%90%: 4%–52% · best of 5: 14%
Serve points won 59.2% / 66.0% Heather / Jessica · tour 58.1%
Strengths only, no similarity priors 20%serve 59.2% / 66.0%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Heather Watson's record against Jessica Pegula's tactical lookalikes and in their charted head-to-heads. 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

CareerHeatherJessica
Direction choice+0.13 ±0.21
better than 77%
−0.15 ±0.04
better than 25%
Shot selection+0.05 ±0.18
better than 51%
−0.24 ±0.07
better than 26%
Execution−0.49 ±0.88
better than 33%
+0.29 ±0.30
better than 72%
Points left on the table2.27 ±0.23
lower than 86%
2.72 ±0.06
lower than 31%

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.

Heather Watson serving

Deuce court

1st serveNowHeather winsv JessicaMatchupOptimal
Wide38%67%65%65.8%±7.537% ▼
Body14%63%55%60.2%±10.70% ▼
T48%76%70%78.1%±6.363% ▲

Optimal v Jessica Pegula: +0.7±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowHeather winsv JessicaMatchupOptimal
Wide36%70%64%68.8%±8.251% ▲
Body16%55%54%52.8%±10.91% ▼
T48%69%62%66.9%±7.448%

Optimal v Jessica Pegula: +0.7±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.4 per 100 first serves in before the returner adjusts.

Jessica Pegula serving

Deuce court

1st serveNowJessica winsv HeatherMatchupOptimal
Wide31%67%70%71.2%±7.346% ▲
Body29%62%70%74.4%±7.529%
T40%74%75%79.9%±6.325% ▼

Optimal v Heather Watson: +0.3±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJessica winsv HeatherMatchupOptimal
Wide29%66%63%63.0%±8.744% ▲
Body22%61%55%59.5%±10.28% ▼
T49%63%61%60.0%±7.948%

Optimal v Heather Watson: +0.3±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.2 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.

Heather Watson returning

1st serve to the forehand

ReturnNowTourOwnv JessicaValue
FH through the middle46%+4.2+1.0+0.4+5.5±2.5
FH crosscourt32%+5.3−1.1±0.0+4.2±3.7
FH down the line17%+1.5+2.9−1.3+3.1±4.0
FH slice through the middle5%−6.7+0.7+0.8−5.2±1.9

Lean FH through the middle: +1.3±1.9 per 100 returns v the current mix (132 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JessicaValue
BH through the middle55%+6.0+1.0−0.2+6.8±2.3
BH crosscourt36%+7.7+0.8−1.5+7.0±3.1
BH down the line8%+2.2−0.8−3.2−1.8±3.3

Lean BH crosscourt: +0.9±2.4 per 100 returns v the current mix (96 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JessicaValue
BH crosscourt43%+1.5−0.3−0.5+0.7±3.0
BH through the middle41%−2.6+1.4+0.1−1.0±2.2
BH down the line16%−0.5+0.4−0.8−0.9±4.1

Lean BH crosscourt: +1.0±2.0 per 100 returns v the current mix (79 returns charted, inside the 90% margin)

Jessica Pegula returning

1st serve to the forehand

ReturnNowTourOwnv HeatherValue
FH through the middle49%+4.2−1.8+0.2+2.5±2.5
FH crosscourt19%+5.3+1.4+3.0+9.7±3.8
FH slice through the middle13%−6.7+0.3−1.9−8.3±2.2
FH down the line11%+1.5+0.4+1.0+3.0±4.4
FH slice crosscourt4%−6.6−0.2+0.1−6.7±2.5

Lean FH crosscourt: +8.0±3.3 per 100 returns v the current mix (1257 returns charted)

1st serve to the backhand

ReturnNowTourOwnv HeatherValue
BH through the middle42%+6.0−3.0+0.5+3.5±2.4
BH crosscourt24%+7.7+0.5−0.1+8.2±3.2
BH slice through the middle12%−6.2−0.2−0.4−6.8±1.9
BH down the line12%+2.2−1.4−1.9−1.2±4.2
BH slice crosscourt6%−4.2−0.9±0.0−5.1±2.1

Lean BH crosscourt: +6.5±2.7 per 100 returns v the current mix (1269 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv HeatherValue
FH through the middle46%−3.2−1.4+0.7−3.8±2.9
FH crosscourt27%+0.5+0.2+0.7+1.4±4.1
FH down the line23%−0.6+2.7+2.0+4.1±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: +5.2±4.3 per 100 returns v the current mix (359 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv HeatherValue
BH through the middle48%−2.6−1.0+0.1−3.4±2.4
BH crosscourt34%+1.5−6.1−0.4−5.1±3.3
BH down the line17%−0.5−0.4−2.1−3.1±5.0
BH slice through the middle2%−11.7−0.9±0.0−12.6±1.3

Lean BH down the line: +1.0±4.5 per 100 returns v the current mix (637 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 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.

Heather Watson

Favour

ShotEdgeOwnTheirs
BH to the middle · serve +1+4.0±3.6+2.9+1.1
FH to their forehand · return+3.0±5.9+2.3+0.7
BH to their backhand · rally+0.9±4.4+2.5−1.7
BH to the middle · rally+0.2±3.3+1.3−1.1
BH to the middle · return+0.1±3.5−0.1+0.2
FH to the middle · return±0.0±4.0+0.3−0.2

Avoid

ShotEdgeOwnTheirs
BH to their backhand · return +1−11.0±4.9−5.6−5.4
FH to their backhand · serve +1−10.8±5.8−4.3−6.4
BH to the middle · return +1−5.7±3.7−2.6−3.1
FH to their backhand · rally−4.0±5.4−4.3+0.3
FH to their forehand · return +1−3.2±5.5+0.1−3.3

Jessica Pegula

Favour

ShotEdgeOwnTheirs
BH to their backhand · return +1+7.9±5.0+4.1+3.8
FH to their forehand · serve +1+4.0±5.6+2.6+1.5
BH to their backhand · rally+3.4±4.6+4.3−0.9
BH to the middle · rally+3.3±3.3+0.4+2.9
FH to the middle · serve +1+2.5±3.8+0.6+1.9
BH to the middle · serve +1+1.6±3.6−0.4+2.0

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−8.9±6.2+0.4−9.2
BH to their backhand · serve +1−6.5±5.0−4.9−1.6
FH to their backhand · serve +1−4.9±5.9−4.1−0.8
BH to the middle · return−4.3±3.6−4.4±0.0
FH to the middle · return−1.5±3.9−1.8+0.3

Against Jessica Pegula-like opponents

Heather Watson vMatchesServe pts wonReturn pts won
All charted opponents–61.6%42.1%

Similar by tactical fingerprint: Alexandra Eala, Anna Blinkova, Ashlyn Krueger, Elina Svitolina, Jaqueline Cristian, Katerina Siniakova, Elisabetta Cocciaretto, R, Dominika Cibulkova. When two players have rarely met, their records against these lookalikes fill the gap.