RallyIQ

Game plan

Victoria Azarenka v Martina Hingis

Every number combines what Victoria Azarenka does well with what Martina Hingis allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Victoria Azarenka wins, best of 3 60%90%: 27%–87% · best of 5: 63%
Serve points won 54.3% / 52.3% Victoria / Martina · tour 58.1%
Strengths only, no similarity priors 58%serve 55.3% / 53.7%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Victoria Azarenka's record against Martina Hingis's tactical lookalikes and in their charted head-to-heads (lookalikes: −3.9 on serve, +5.9 on return vs expectation (986 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

CareerVictoriaMartina
Direction choice+0.06 ±0.05
better than 65%
+0.18 ±0.09
better than 83%
Shot selection+0.21 ±0.07
better than 67%
+0.09 ±0.11
better than 54%
Execution+0.96 ±0.29
better than 90%
+1.18 ±0.34
better than 94%
Points left on the table2.42 ±0.07
lower than 74%
2.55 ±0.14
lower than 59%

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.

Victoria Azarenka serving

Deuce court

1st serveNowVictoria winsv MartinaMatchupOptimal
Wide40%65%59%57.9%±4.755% ▲
Body18%58%54%54.6%±6.93% ▼
T41%68%61%61.4%±5.842%

Optimal v Martina Hingis: +0.6±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowVictoria winsv MartinaMatchupOptimal
Wide42%67%60%60.7%±5.357% ▲
Body21%57%49%50.1%±7.38% ▼
T37%60%59%53.7%±5.335% ▼

Optimal v Martina Hingis: +0.6±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.8 per 100 first serves in before the returner adjusts.

Martina Hingis serving

Deuce court

1st serveNowMartina winsv VictoriaMatchupOptimal
Wide47%62%65%61.3%±4.562% ▲
Body18%51%56%49.5%±6.53% ▼
T35%67%66%65.3%±5.535%

Optimal v Victoria Azarenka: +0.8±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMartina winsv VictoriaMatchupOptimal
Wide53%59%69%62.1%±4.942% ▼
Body12%57%51%52.1%±7.827% ▲
T35%62%62%60.0%±5.331% ▼

Optimal v Victoria Azarenka: +0.1±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.0 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.

Victoria Azarenka returning

1st serve to the forehand

ReturnNowTourOwnv MartinaValue
FH through the middle48%+4.2+2.0−1.0+5.1±1.9
FH crosscourt24%+5.3+0.9+4.5+10.8±3.1
FH down the line21%+1.5+1.7+1.9+5.1±3.8
FH slice through the middle4%−6.7−0.9+3.6−4.1±2.5
FH slice down the line1%−10.5−0.2+3.3−7.3±3.1

Lean FH crosscourt: +5.0±2.6 per 100 returns v the current mix (1610 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MartinaValue
BH through the middle42%+6.0+1.0−0.7+6.3±1.9
BH crosscourt28%+7.7+3.2+0.2+11.1±2.8
BH slice through the middle12%−6.2−0.7+0.9−6.0±2.3
BH down the line10%+2.2±0.0+1.5+3.7±4.3
BH slice down the line4%−12.5−1.0−0.3−13.7±3.6

Lean BH crosscourt: +6.3±2.2 per 100 returns v the current mix (1134 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MartinaValue
FH through the middle37%−3.2−0.7+0.1−3.8±2.9
FH down the line31%−0.6+3.1+1.3+3.9±4.9
FH crosscourt31%+0.5+1.1+2.9+4.5±4.0
BH through the middle1%−1.0+0.4−1.5−2.1±1.9

Lean FH crosscourt: +3.3±3.3 per 100 returns v the current mix (392 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MartinaValue
BH crosscourt47%+1.5+0.4−0.9+1.0±2.9
BH through the middle37%−2.6+1.3−1.5−2.8±2.4
BH down the line14%−0.5+5.2+1.8+6.5±5.0
BH slice through the middle2%−11.7+0.7+3.0−8.0±2.1
FH through the middle1%−2.7−1.3+0.1−3.9±2.2

Lean BH down the line: +6.3±4.6 per 100 returns v the current mix (679 returns charted)

Martina Hingis returning

1st serve to the forehand

ReturnNowTourOwnv VictoriaValue
FH through the middle46%+4.2+0.2+1.3+5.7±1.8
FH down the line39%+1.5+5.9+0.7+8.2±3.3
FH crosscourt13%+5.3+0.7+1.0+7.0±3.5
BH through the middle1%+5.2+0.5+0.4+6.1±1.7
FH slice through the middle1%−6.7+0.9+0.9−4.9±2.1

Lean FH down the line: +1.5±2.2 per 100 returns v the current mix (700 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv VictoriaValue
BH through the middle37%+6.0−2.4+0.4+4.0±2.0
BH crosscourt33%+7.7+1.1−0.1+8.6±2.8
BH slice through the middle11%−6.2+0.6−1.5−7.0±2.4
BH down the line11%+2.2+1.6+0.9+4.6±4.1
BH slice crosscourt7%−4.2−1.1−2.3−7.5±3.0

Lean BH crosscourt: +5.5±2.1 per 100 returns v the current mix (443 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv VictoriaValue
FH down the line47%−0.6+4.8−0.3+3.9±4.5
FH through the middle34%−3.2+3.0−0.2−0.4±2.6
FH crosscourt10%+0.5−2.4+1.2−0.7±3.8
BH through the middle6%−1.0+0.1−1.2−2.1±1.8
BH inside-out4%+2.2+1.9−1.2+2.9±3.4

Lean FH down the line: +2.3±2.6 per 100 returns v the current mix (268 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv VictoriaValue
BH crosscourt40%+1.5+0.7+0.2+2.4±3.1
BH through the middle38%−2.6+0.6−1.2−3.2±2.2
BH down the line15%−0.5+0.3−1.2−1.4±4.7
FH inside-out5%+1.4−2.2−0.3−1.1±3.4
FH through the middle2%−2.7−0.6−0.2−3.5±1.7

Lean BH crosscourt: +3.0±2.2 per 100 returns v the current mix (238 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 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.

Victoria Azarenka

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+9.7±5.3+2.7+7.0
BH to their forehand · return+8.7±5.6+1.8+6.8
BH slice to their backhand · rally+7.5±3.7+2.2+5.3
BH to their forehand · return +1+6.9±6.0+5.6+1.3
FH to their forehand · return +1+6.7±5.1+2.1+4.6
BH slice to their backhand · return +1+6.6±4.3+1.2+5.4

Avoid

ShotEdgeOwnTheirs
BH to the middle · serve +1−1.0±2.6−1.2+0.3
FH to their backhand · return +1−0.9±5.6−1.2+0.3
BH to their backhand · return +1−0.2±4.6+1.9−2.2
BH to their forehand · serve +1−0.1±5.9+4.3−4.4
BH to the middle · return +1+0.7±2.8+1.1−0.5

Martina Hingis

Favour

ShotEdgeOwnTheirs
BH to their forehand · return +1+7.1±6.0+4.2+2.9
FH volley to their forehand · rally+6.6±6.7+3.5+3.1
FH to their backhand · return+4.9±5.3+6.3−1.5
FH to their forehand · return +1+4.6±5.1+3.2+1.4
BH to their forehand · serve +1+4.0±5.9+1.8+2.1
FH to their backhand · return +1+3.9±5.5+0.6+3.3

Avoid

ShotEdgeOwnTheirs
BH slice to the middle · rally−1.0±3.0+0.4−1.4
FH to their forehand · rally−0.9±3.8−1.0+0.1
BH to the middle · return−0.7±3.2−0.7±0.0
BH to the middle · serve +1−0.3±3.3+1.0−1.2
BH slice to their backhand · rally−0.2±3.8−1.0+0.8

Against Martina Hingis-like opponents

Victoria Azarenka vMatchesServe pts wonReturn pts won
All charted opponents–56.5%45.4%
Players most similar to Martina Hingis8 52.4%50.6%

Similar by tactical fingerprint: Mirra Andreeva, Elise Mertens, Simona Halep, Svetlana Kuznetsova, Vera Zvonareva, Agnieszka Radwanska, Jelena Jankovic, Elena Dementieva, Mary Pierce. When two players have rarely met, their records against these lookalikes fill the gap.