RallyIQ

Game plan

Helena Sukova v Madison Keys

Every number combines what Helena Sukova does well with what Madison Keys allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Helena Sukova wins, best of 3 8%90%: 2%–24% · best of 5: 4%
Serve points won 54.9% / 65.9% Helena / Madison · tour 56.4%
Strengths only, no similarity priors 8%serve 54.9% / 65.9%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Helena Sukova's record against Madison Keys'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

CareerHelenaMadison
Direction choice+0.12 ±0.30
better than 76%
+0.06 ±0.06
better than 67%
Shot selection+0.20 ±0.33
better than 66%
+0.34 ±0.10
better than 83%
Execution−1.46 ±0.74
better than 11%
−0.69 ±0.38
better than 28%

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.

Helena Sukova serving

Deuce court

1st serveNowHelena winsv MadisonMatchupOptimal
Wide44%68%70%71.3%±7.959% ▲
Body10%57%57%57.1%±12.60% ▼
T46%61%67%59.2%±8.841% ▼

Optimal v Madison Keys: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +7.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowHelena winsv MadisonMatchupOptimal
Wide45%61%64%59.5%±8.934% ▼
Body9%66%56%66.2%±12.75% ▼
T46%71%65%72.4%±8.661% ▲

Optimal v Madison Keys: +0.5±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +6.4 per 100 first serves in before the returner adjusts.

Madison Keys serving

Deuce court

1st serveNowMadison winsv HelenaMatchupOptimal
Wide50%69%65%68.4%±7.848% ▼
Body14%54%61%57.7%±11.30% ▼
T37%78%75%83.7%±5.552% ▲

Optimal v Helena Sukova: +1.9±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +11.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMadison winsv HelenaMatchupOptimal
Wide41%65%65%64.6%±7.437% ▼
Body11%54%55%52.5%±13.50% ▼
T48%71%68%74.4%±8.263% ▲

Optimal v Helena Sukova: +1.3±0.9 per 100 first serves (faults included) over the current mix. Serving T every time would read +6.3 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.

Helena Sukova returning

1st serve to the forehand

ReturnNowTourOwnv MadisonValue
FH through the middle33%+4.2−2.5−0.4+1.2±2.5
FH crosscourt26%+5.3+1.3−1.5+5.2±3.8
FH down the line21%+1.5+1.7±0.0+3.2±4.1
FH slice through the middle15%−6.7+0.9+0.8−5.0±2.2
FH slice down the line5%−10.5+0.4+0.8−9.3±2.8

Lean FH crosscourt: +3.9±3.0 per 100 returns v the current mix (102 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MadisonValue
BH slice through the middle37%−6.2+1.4−2.0−6.8±2.5
BH slice down the line20%−12.5+3.4−1.1−10.1±3.6
BH slice crosscourt17%−4.2+2.6−0.6−2.2±2.9
BH through the middle14%+6.0−0.8−0.5+4.7±2.3
BH crosscourt7%+7.7−1.4+1.1+7.5±2.7

Lean BH through the middle: +8.4±2.4 per 100 returns v the current mix (175 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MadisonValue
FH crosscourt40%+0.5+1.6−0.3+1.9±3.8
FH down the line33%−0.6+1.2−2.5−1.8±4.5
FH through the middle28%−3.2−2.2+0.8−4.6±2.4

Lean FH crosscourt: +3.0±2.8 per 100 returns v the current mix (43 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv MadisonValue
BH slice crosscourt31%−7.5−0.5±0.0−8.0±1.9
BH slice through the middle29%−11.7+0.2±0.0−11.4±1.6
BH slice down the line21%−10.6+0.4±0.0−10.2±2.6
FH inside-out10%+1.4−1.1−2.5−2.2±3.3
BH down the line9%−0.5+1.5−2.9−1.9±4.1

Lean BH slice crosscourt: +0.4±1.6 per 100 returns v the current mix (70 returns charted, inside the 90% margin)

Madison Keys returning

1st serve to the forehand

ReturnNowTourOwnv HelenaValue
FH through the middle44%+4.2−6.1+0.6−1.3±2.6
FH crosscourt28%+5.3−2.5+1.3+4.1±3.6
FH down the line11%+1.5−4.7+1.4−1.8±4.4
FH slice through the middle11%−6.7−1.1+1.3−6.5±2.1
FH slice crosscourt3%−6.6−0.4±0.0−7.0±1.9

Lean FH crosscourt: +4.9±2.9 per 100 returns v the current mix (845 returns charted)

1st serve to the backhand

ReturnNowTourOwnv HelenaValue
BH through the middle52%+6.0−1.6−2.4+2.0±2.4
BH crosscourt20%+7.7+1.1+0.9+9.7±3.0
BH down the line17%+2.2−1.7−1.2−0.7±3.4
BH slice through the middle5%−6.2−1.8−0.7−8.7±2.6
BH slice down the line3%−12.5−2.0+5.0−9.5±3.4

Lean BH crosscourt: +7.6±2.7 per 100 returns v the current mix (1240 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv HelenaValue
FH through the middle38%−3.2+2.5−0.9−1.6±3.0
FH crosscourt30%+0.5+1.4+1.1+3.0±4.4
FH down the line21%−0.6−4.4+0.5−4.5±5.2
FH slice through the middle6%−15.2+1.4±0.0−13.8±1.5
FH slice crosscourt4%−14.9+0.5±0.0−14.4±1.5

Lean FH crosscourt: +5.1±3.5 per 100 returns v the current mix (217 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv HelenaValue
BH through the middle40%−2.6−0.7+0.5−2.8±2.3
BH crosscourt29%+1.5+0.8+1.9+4.2±3.2
BH down the line21%−0.5+1.7−0.7+0.5±4.4
FH inside-out4%+1.4+2.7+0.5+4.5±4.2
FH through the middle4%−2.7+0.1−0.9−3.5±2.5

Lean FH inside-out: +4.1±4.3 per 100 returns v the current mix (569 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.

Helena Sukova

Favour

ShotEdgeOwnTheirs
FH to their forehand · return−0.1±5.4+2.5−2.6
BH slice to the middle · return−1.1±3.5+0.6−1.7
FH to the middle · return−6.0±3.5−5.6−0.4

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−6.0±3.5−5.6−0.4
BH slice to the middle · return−1.1±3.5+0.6−1.7
FH to their forehand · return−0.1±5.4+2.5−2.6

Madison Keys

Favour

ShotEdgeOwnTheirs
BH slice to the middle · return−1.5±3.6−1.3−0.2
BH to the middle · return−5.1±3.3−1.3−3.8
FH to their forehand · rally−5.6±4.6−1.0−4.6
FH to the middle · return−8.2±3.5−5.2−2.9

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−8.2±3.5−5.2−2.9
FH to their forehand · rally−5.6±4.6−1.0−4.6
BH to the middle · return−5.1±3.3−1.3−3.8
BH slice to the middle · return−1.5±3.6−1.3−0.2

Against Madison Keys-like opponents

Helena Sukova vMatchesServe pts wonReturn pts won
All charted opponents–55.4%36.8%

Similar by tactical fingerprint: Naomi Osaka, Karolina Pliskova, Dayana Yastremska, Anastasia Pavlyuchenkova, Shelby Rogers, Kaia Kanepi, Julia Goerges, Maria Sharapova, Ana Ivanovic, Daniela Hantuchova. When two players have rarely met, their records against these lookalikes fill the gap.