RallyIQ

Game plan

Katie Boulter v Lulu Sun

Every number combines what Katie Boulter does well with what Lulu Sun allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Katie Boulter wins, best of 3 49%90%: 20%–78% · best of 5: 48%
Serve points won 61.2% / 61.5% Katie / Lulu · tour 56.4%
Strengths only, no similarity priors 49%serve 61.2% / 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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Katie Boulter's record against Lulu Sun'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

CareerKatieLulu
Direction choice−0.15 ±0.07
better than 26%
−0.04 ±0.13
better than 48%
Shot selection+0.24 ±0.18
better than 72%
+0.31 ±0.35
better than 79%
Execution−0.88 ±0.63
better than 21%
−0.39 ±1.24
better than 39%
Points left on the table2.79 ±0.11
lower than 25%
2.91 ±0.34
lower than 16%

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.

Katie Boulter serving

Deuce court

1st serveNowKatie winsv LuluMatchupOptimal
Wide39%68%70%72.4%±7.554% ▲
Body21%55%53%50.3%±11.36% ▼
T40%71%71%74.2%±9.340%

Optimal v Lulu Sun: +1.5±1.1 per 100 first serves (faults included) over the current mix. Serving T every time would read +5.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowKatie winsv LuluMatchupOptimal
Wide53%68%71%73.4%±8.368% ▲
Body17%62%58%63.2%±11.52% ▼
T31%66%65%66.1%±9.630%

Optimal v Lulu Sun: +0.5±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.9 per 100 first serves in before the returner adjusts.

Lulu Sun serving

Deuce court

1st serveNowLulu winsv KatieMatchupOptimal
Wide30%67%64%64.7%±10.346% ▲
Body24%53%66%61.2%±11.116% ▼
T45%69%71%71.5%±8.638% ▼

Optimal v Katie Boulter: +0.2±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLulu winsv KatieMatchupOptimal
Wide42%73%70%77.2%±7.547% ▲
Body16%62%61%66.2%±12.01% ▼
T42%84%67%85.7%±6.652% ▲

Optimal v Katie Boulter: +1.3±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +6.6 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.

Katie Boulter returning

1st serve to the forehand

ReturnNowTourOwnv LuluValue
FH through the middle28%+4.2+1.8−0.1+5.8±3.1
FH slice through the middle27%−6.7−2.2−1.5−10.5±2.4
FH crosscourt19%+5.3−0.3−2.7+2.3±4.3
FH down the line14%+1.5+2.9−2.8+1.6±4.5
FH slice crosscourt9%−6.6+1.6+0.6−4.5±2.5

Lean FH through the middle: +7.0±2.6 per 100 returns v the current mix (285 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LuluValue
BH through the middle45%+6.0−2.9+1.2+4.3±2.8
BH down the line26%+2.2−1.8−5.2−4.9±4.6
BH crosscourt16%+7.7+0.5−1.4+6.8±3.6
BH slice crosscourt5%−4.2−1.3+2.1−3.3±2.1
BH slice down the line4%−12.5−0.7−1.5−14.7±2.6

Lean BH crosscourt: +6.0±3.5 per 100 returns v the current mix (269 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LuluValue
FH through the middle37%−3.2−3.1+2.4−3.9±3.1
FH crosscourt31%+0.5+2.3−1.6+1.2±3.9
FH down the line23%−0.6−1.4−7.2−9.2±5.0
FH slice through the middle9%−15.2−0.2+1.7−13.7±1.8

Lean FH crosscourt: +5.7±3.2 per 100 returns v the current mix (98 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LuluValue
BH through the middle43%−2.6−0.9−0.1−3.6±2.8
BH crosscourt18%+1.5−0.6+2.5+3.4±3.6
FH through the middle15%−2.7−0.6+2.4−0.9±2.6
BH down the line13%−0.5−2.3−2.3−5.2±4.9
FH inside-in7%+0.7+0.1−1.6−0.8±3.7

Lean BH crosscourt: +5.4±3.3 per 100 returns v the current mix (168 returns charted)

Lulu Sun returning

1st serve to the forehand

ReturnNowTourOwnv KatieValue
FH through the middle59%+4.2−0.2−0.5+3.4±3.0
FH crosscourt26%+5.3+0.9+0.2+6.4±4.3
FH down the line15%+1.5−3.0+2.3+0.8±4.3

Lean FH crosscourt: +2.5±3.7 per 100 returns v the current mix (95 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv KatieValue
BH through the middle46%+6.0−1.6−2.2+2.2±2.7
BH crosscourt27%+7.7+2.1−0.5+9.3±3.7
BH slice through the middle12%−6.2±0.0±0.0−6.2±2.5
BH slice crosscourt8%−4.2−3.5−1.3−9.0±2.5
BH down the line7%+2.2−0.5+0.4+2.1±4.3

Lean BH crosscourt: +7.1±3.0 per 100 returns v the current mix (214 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv KatieValue
BH crosscourt48%+1.5−1.3−0.9−0.7±3.6
BH through the middle46%−2.6−0.1+0.3−2.3±2.8
FH through the middle6%−2.7−0.5−1.7−4.8±2.0

Lean BH crosscourt: +1.0±2.3 per 100 returns v the current mix (87 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.

Katie Boulter

Favour

ShotEdgeOwnTheirs
FH to their backhand · return +1+10.3±5.8+4.5+5.8
FH to their backhand · serve +1+6.3±5.4+5.9+0.4
FH to their forehand · rally+3.5±4.7+0.8+2.7
FH to their forehand · serve +1+2.7±5.7−1.4+4.2
FH to the middle · serve +1+1.5±3.8+0.9+0.6
FH to their backhand · rally−0.5±5.0−1.3+0.9

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−7.2±6.5−5.5−1.7
BH to the middle · return−4.1±3.3−2.7−1.3
BH to the middle · rally−3.9±3.0−2.6−1.3
FH to the middle · return−3.8±3.8−3.2−0.5
BH to their forehand · return−3.3±6.4−6.4+3.2

Lulu Sun

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+4.8±4.8+3.1+1.7
BH to their forehand · return+3.7±6.4+4.0−0.3
BH to their forehand · rally+2.4±6.3+0.2+2.2
FH to their backhand · rally+2.3±5.2+1.9+0.4
FH to their backhand · return +1+1.1±6.4−2.7+3.8
FH to their forehand · serve +1+0.2±5.4+3.0−2.7

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−7.2±3.7−4.1−3.1
FH to their backhand · serve +1−6.6±5.8−0.2−6.4
BH to the middle · rally−5.9±3.2−4.8−1.1
FH to the middle · rally−1.6±3.4+0.8−2.5
FH to the middle · serve +1−1.2±3.8−1.8+0.6

Against Lulu Sun-like opponents

Katie Boulter vMatchesServe pts wonReturn pts won
All charted opponents–56.4%41.3%

Similar by tactical fingerprint: Alexandra Eala, Diana Shnaider, Xin Yu Wang, Marta Kostyuk, Robin Montgomery, Arianne Hartono, Jule Niemeier, Caroline Garcia, Eugenie Bouchard. When two players have rarely met, their records against these lookalikes fill the gap.