RallyIQ

Game plan

Serena Williams v Angelique Kerber

Every number combines what Serena Williams does well with what Angelique Kerber allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Serena Williams wins, best of 3 82%90%: 61%–94% · best of 5: 87%
Serve points won 62.3% / 55.3% Serena / Angelique · tour 56.3%
Strengths only, no similarity priors 82%serve 62.1% / 55.0%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Serena Williams's record against Angelique Kerber's tactical lookalikes and in their charted head-to-heads (lookalikes: +1.0 on serve, +9.8 on return vs expectation (112 points); head-to-head: +2.0 on serve, −8.7 on return vs expectation (233 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

CareerSerenaAngelique
Direction choice+0.34 ±0.04
better than 97%
+0.18 ±0.05
better than 83%
Shot selection+0.47 ±0.05
better than 93%
+0.05 ±0.08
better than 50%
Execution−0.04 ±0.27
better than 59%
+1.65 ±0.29
better than 97%
Points left on the table2.20 ±0.07
lower than 94%
2.57 ±0.07
lower than 56%

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.

Structural compatibility

Expected edge per 100 rally shots from style alone: Serena Williams +1.27, Angelique Kerber +1.42. Each player's shot mix weighted by their own skill with each shot and by how much the other gives up against it. This is why some rankings gaps don't hold in a given matchup.

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.

Serena Williams serving

Deuce court

1st serveNowSerena winsv AngeliqueMatchupOptimal
Wide50%70%69%72.9%±3.065% ▲
Body8%62%59%63.9%±5.80% ▼
T42%79%63%76.0%±3.235% ▼

Optimal v Angelique Kerber: +0.4±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSerena winsv AngeliqueMatchupOptimal
Wide45%75%67%76.5%±3.360% ▲
Body6%60%58%61.5%±6.30% ▼
T49%70%60%65.5%±3.340% ▼

Optimal v Angelique Kerber: +0.5±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +6.3 per 100 first serves in before the returner adjusts.

Angelique Kerber serving

Deuce court

1st serveNowAngelique winsv SerenaMatchupOptimal
Wide36%65%65%64.0%±3.951% ▲
Body27%56%53%51.4%±4.412% ▼
T37%59%66%56.7%±3.837%

Optimal v Serena Williams: +1.0±0.7 per 100 first serves (faults included) over the current mix. Serving wide every time would read +6.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAngelique winsv SerenaMatchupOptimal
Wide62%62%66%62.1%±3.377% ▲
Body19%54%57%54.9%±5.14% ▼
T18%71%61%68.0%±5.219%

Optimal v Serena Williams: +0.7±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +6.2 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.

Serena Williams returning

1st serve to the forehand

ReturnNowTourOwnv AngeliqueValue
FH through the middle49%+4.2−2.6+1.1+2.7±1.5
FH crosscourt36%+5.3−1.6+3.8+7.5±2.6
FH down the line11%+1.5−0.4−0.6+0.5±3.6
BH through the middle1%+5.2−3.4+1.3+3.1±2.1
FH slice through the middle1%−6.7−0.7−1.0−8.4±2.3

Lean FH crosscourt: +3.3±1.9 per 100 returns v the current mix (2166 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AngeliqueValue
BH through the middle48%+6.0+0.3+1.3+7.6±1.2
BH crosscourt33%+7.7+1.3+6.5+15.6±2.0
BH down the line12%+2.2+1.1−1.7+1.6±3.3
BH slice through the middle3%−6.2−4.5+0.6−10.1±2.5
BH slice crosscourt2%−4.2−2.8+2.1−4.8±3.0

Lean BH crosscourt: +7.0±1.5 per 100 returns v the current mix (1939 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv AngeliqueValue
FH crosscourt43%+0.5−0.5+2.0+2.0±3.7
FH through the middle37%−3.2−0.1+2.0−1.2±2.5
FH down the line18%−0.6+5.3+2.4+7.2±4.9
BH inside-in1%+2.0−1.4+3.7+4.3±2.9
BH through the middle1%−1.0−0.2−0.1−1.3±1.6

Lean FH down the line: +5.4±4.4 per 100 returns v the current mix (750 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv AngeliqueValue
BH crosscourt51%+1.5+0.9+3.7+6.1±2.3
BH through the middle30%−2.6−1.8−0.1−4.5±1.8
BH down the line17%−0.5+3.4+0.4+3.2±4.1
FH inside-in1%+0.7+0.7+2.0+3.4±3.9
FH inside-out1%+1.4+0.2+2.4+3.9±3.5

Lean BH crosscourt: +3.8±1.4 per 100 returns v the current mix (954 returns charted)

Angelique Kerber returning

1st serve to the forehand

ReturnNowTourOwnv SerenaValue
FH through the middle53%+4.2+2.6−1.3+5.4±1.6
FH crosscourt34%+5.3+5.1−1.4+9.0±2.8
FH down the line11%+1.5+5.5−4.0+3.1±3.6
FH slice through the middle1%−6.7−0.1+2.1−4.7±2.0
BH through the middle1%+5.2+1.3−1.0+5.6±1.7

Lean FH crosscourt: +2.8±2.1 per 100 returns v the current mix (1007 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SerenaValue
BH through the middle48%+6.0+1.1−1.0+6.2±1.4
BH crosscourt30%+7.7−0.4−4.1+3.3±2.5
BH down the line12%+2.2+7.3−0.2+9.2±3.5
BH slice through the middle5%−6.2−0.7−0.2−7.2±2.2
BH slice crosscourt2%−4.2−0.4−1.2−5.8±3.0

Lean BH down the line: +4.8±3.3 per 100 returns v the current mix (1499 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SerenaValue
FH crosscourt39%+0.5−1.4+0.6−0.3±3.7
FH down the line32%−0.6+1.3−3.0−2.3±4.4
FH through the middle28%−3.2+0.3−0.9−3.8±2.5

Lean FH crosscourt: +1.7±2.7 per 100 returns v the current mix (285 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SerenaValue
BH crosscourt39%+1.5+2.8−2.1+2.2±2.6
BH through the middle37%−2.6+1.3−0.3−1.6±1.7
BH down the line20%−0.5+4.0−0.2+3.2±3.8
FH inside-in1%+0.7−0.9+0.6+0.4±3.4
FH through the middle1%−2.7+1.2−0.9−2.4±1.7

Lean BH down the line: +2.4±3.3 per 100 returns v the current mix (646 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.

Serena Williams

Favour

ShotEdgeOwnTheirs
FH volley to their backhand · rally+8.1±5.1+0.9+7.2
BH to their forehand · return+7.6±2.2+1.8+5.8
FH to their backhand · return+6.7±2.6+2.9+3.8
BH volley to their backhand · rally+6.1±5.8+1.9+4.2
FH to their forehand · serve +1+5.8±1.9+1.4+4.4
FH to their backhand · serve +1+5.7±2.0+2.6+3.2

Avoid

ShotEdgeOwnTheirs
BH slice to the middle · return−4.0±2.4−4.9+0.9
BH to their backhand · return +1−3.4±2.2−1.0−2.4
BH slice to their backhand · rally−3.4±2.4−2.9−0.5
FH slice to the middle · rally−2.7±2.4−1.9−0.8
BH to the middle · return +1−2.2±1.6−1.8−0.4

Angelique Kerber

Favour

ShotEdgeOwnTheirs
BH slice to the middle · rally+4.0±1.7+2.3+1.7
FH to their backhand · return+3.7±2.2+4.4−0.7
FH to their backhand · rally+3.0±1.3+3.0−0.1
FH to their backhand · return +1+2.8±2.1+3.6−0.7
BH slice to their forehand · rally+2.8±3.1+2.8±0.0
BH to their backhand · serve +1+2.8±2.2+2.5+0.3

Avoid

ShotEdgeOwnTheirs
FH to their forehand · return−3.3±2.4+0.3−3.6
BH slice to their backhand · rally−2.5±2.2−2.6±0.0
FH to their backhand · serve +1−0.9±1.9+1.1−2.0
BH slice to the middle · return +1−0.5±2.2−0.1−0.4
BH slice to the middle · return−0.2±2.2−0.2±0.0

Against Angelique Kerber-like opponents

Serena Williams vMatchesServe pts wonReturn pts won
All charted opponents–62.1%45.1%
Players most similar to Angelique Kerber1 62.5%55.4%
Angelique Kerber (charted head-to-head)2 64.1%36.2%

Similar by tactical fingerprint: Cristina Bucsa, Arantxa Rus, Leylah Fernandez, Magda Linette, Sara Bejlek, Olga Danilovic, Anhelina Kalinina, Brenda Fruhvirtova, Anna Lena Friedsam, Flavia Pennetta. When two players have rarely met, their records against these lookalikes fill the gap.

Charted head-to-head