RallyIQ

Game plan

Heather Watson v Jaqueline Cristian

Every number combines what Heather Watson does well with what Jaqueline Cristian 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 70%90%: 28%–95% · best of 5: 74%
Serve points won 61.6% / 57.6% Heather / Jaqueline · tour 55.0%
Strengths only, no similarity priors 70%serve 61.6% / 57.6%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Jaqueline Cristian'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

CareerHeatherJaqueline
Direction choice+0.13 ±0.21
better than 77%
−0.15 ±0.12
better than 25%
Shot selection+0.05 ±0.18
better than 51%
−0.05 ±0.12
better than 41%
Execution−0.49 ±0.88
better than 33%
−0.25 ±0.59
better than 46%
Points left on the table2.27 ±0.23
lower than 86%
2.61 ±0.17
lower than 51%

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 JaquelineMatchupOptimal
Wide38%67%72%72.6%±7.950% ▲
Body14%63%58%63.9%±11.90% ▼
T48%76%70%77.9%±7.450% ▲

Optimal v Jaqueline Cristian: +1.1±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowHeather winsv JaquelineMatchupOptimal
Wide36%70%74%77.9%±7.751% ▲
Body16%55%55%54.3%±12.61% ▼
T48%69%68%71.8%±8.148%

Optimal v Jaqueline Cristian: +1.2±1.1 per 100 first serves (faults included) over the current mix. Serving wide every time would read +6.6 per 100 first serves in before the returner adjusts.

Jaqueline Cristian serving

Deuce court

1st serveNowJaqueline winsv HeatherMatchupOptimal
Wide33%58%70%63.0%±9.548% ▲
Body25%57%70%70.3%±9.610% ▼
T42%69%75%76.1%±8.142%

Optimal v Heather Watson: +0.2±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJaqueline winsv HeatherMatchupOptimal
Wide37%63%63%59.9%±10.438%
Body21%54%55%52.7%±12.45% ▼
T42%65%61%61.5%±9.257% ▲

Optimal v Heather Watson: +0.9±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.4 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.

Heather Watson returning

1st serve to the forehand

ReturnNowTourOwnv JaquelineValue
FH through the middle46%+4.2+1.0+0.3+5.4±2.9
FH crosscourt32%+5.3−1.1+0.3+4.6±4.4
FH down the line17%+1.5+2.9−2.7+1.8±4.5
FH slice through the middle5%−6.7+0.7+0.3−5.7±2.1

Lean FH through the middle: +1.4±2.2 per 100 returns v the current mix (132 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JaquelineValue
BH through the middle55%+6.0+1.0−0.1+6.9±2.7
BH crosscourt36%+7.7+0.8+3.3+11.9±3.6
BH down the line8%+2.2−0.8−1.7−0.3±4.0

Lean BH crosscourt: +3.7±2.8 per 100 returns v the current mix (96 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JaquelineValue
BH crosscourt43%+1.5−0.3+1.3+2.5±3.6
BH through the middle41%−2.6+1.4−1.5−2.7±2.7
BH down the line16%−0.5+0.4−1.5−1.7±4.8

Lean BH crosscourt: +2.8±2.4 per 100 returns v the current mix (79 returns charted)

Jaqueline Cristian returning

1st serve to the forehand

ReturnNowTourOwnv HeatherValue
FH through the middle53%+4.2+1.3+0.2+5.7±2.9
FH crosscourt22%+5.3+2.9+3.0+11.3±4.3
FH slice through the middle10%−6.7−1.3−1.9−9.9±2.4
FH down the line9%+1.5−1.4+1.0+1.2±4.6
FH slice crosscourt4%−6.6+0.6+0.1−6.0±2.1

Lean FH crosscourt: +7.0±3.7 per 100 returns v the current mix (313 returns charted)

1st serve to the backhand

ReturnNowTourOwnv HeatherValue
BH through the middle42%+6.0+0.4+0.5+6.9±2.8
BH crosscourt23%+7.7−0.2−0.1+7.5±3.7
BH down the line14%+2.2−2.8−1.9−2.6±4.5
BH slice through the middle11%−6.2−0.6−0.4−7.2±2.1
BH slice crosscourt5%−4.2+0.1±0.0−4.1±1.8

Lean BH crosscourt: +4.8±3.1 per 100 returns v the current mix (285 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv HeatherValue
FH through the middle53%−3.2−0.1+0.7−2.5±3.1
FH crosscourt38%+0.5+1.3+0.7+2.5±4.0
FH down the line9%−0.6+1.9+2.0+3.3±4.2

Lean FH crosscourt: +2.6±3.0 per 100 returns v the current mix (58 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv HeatherValue
BH through the middle44%−2.6+1.4+0.1−1.1±2.8
BH crosscourt25%+1.5+0.2−0.4+1.2±3.7
FH inside-out11%+1.4+0.7+2.0+4.1±4.0
BH down the line8%−0.5−1.9−2.1−4.6±4.8
FH through the middle7%−2.7+1.0+0.7−1.0±2.4

Lean FH inside-out: +4.3±3.9 per 100 returns v the current mix (167 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 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.

Heather Watson

Favour

ShotEdgeOwnTheirs
BH to their backhand · rally+5.7±4.2+4.2+1.5
FH to their forehand · return+4.4±6.0+0.3+4.1
FH to their forehand · rally+4.0±4.6+0.4+3.6
FH to their backhand · rally+3.4±5.0+1.2+2.2
BH to the middle · serve +1+3.1±3.0+2.7+0.4
BH to the middle · return+1.3±3.0+0.7+0.6

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−4.7±4.8−3.8−0.9
BH to their forehand · rally−1.8±5.3−1.7−0.1
FH to their forehand · return +1−1.4±5.4−0.8−0.6
FH to the middle · return−0.8±3.7−2.9+2.1
BH to their backhand · serve +1−0.6±5.0−0.1−0.6

Jaqueline Cristian

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+6.3±4.8+2.0+4.3
BH to their backhand · serve +1+2.6±5.0+0.8+1.8
BH to their backhand · rally+2.4±4.3−0.7+3.1
FH to the middle · serve +1+2.3±3.0+1.4+0.9
BH to the middle · rally+2.1±3.1+0.7+1.4
FH to their forehand · return +1+1.4±5.3+2.2−0.8

Avoid

ShotEdgeOwnTheirs
BH to their backhand · return−3.5±4.8−1.1−2.3
FH to their backhand · rally−2.8±5.0+2.4−5.2
BH to their forehand · rally−2.3±6.2+0.9−3.2
BH to the middle · return−1.5±3.5−1.0−0.6
FH to their backhand · return−1.5±5.8−3.8+2.3

Against Jaqueline Cristian-like opponents

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

Similar by tactical fingerprint: Alexandra Eala, Elina Svitolina, Jessica Pegula, Jasmine Paolini, Nao Hibino, Linda Fruhvirtova, Irina Camelia Begu, Qiang Wang, Lauren Davis, Dominika Cibulkova. When two players have rarely met, their records against these lookalikes fill the gap.