RallyIQ

Game plan

Tatjana Maria v Serena Williams

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

Forecast

Tatjana Maria wins, best of 3 13%90%: 4%–33% · best of 5: 8%
Serve points won 55.0% / 63.6% Tatjana / Serena · tour 56.3%
Strengths only, no similarity priors 13%serve 55.2% / 63.8%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Tatjana Maria's record against Serena Williams's tactical lookalikes and in their charted head-to-heads (lookalikes: −3.4 on serve, +4.5 on return vs expectation (177 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

CareerTatjanaSerena
Direction choice+0.17 ±0.11
better than 82%
+0.34 ±0.04
better than 97%
Shot selection−4.80 ±0.55
better than 0%
+0.47 ±0.05
better than 93%
Execution+1.80 ±0.44
better than 98%
−0.04 ±0.27
better than 59%
Points left on the table3.32 ±0.20
lower than 3%
2.20 ±0.07
lower than 94%

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: Tatjana Maria +1.86, Serena Williams −3.33. 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.

Tatjana Maria serving

Deuce court

1st serveNowTatjana winsv SerenaMatchupOptimal
Wide38%70%65%68.5%±5.754% ▲
Body14%60%53%55.7%±9.20% ▼
T47%75%66%73.3%±5.546% ▼

Optimal v Serena Williams: +1.5±0.9 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowTatjana winsv SerenaMatchupOptimal
Wide24%74%66%74.7%±7.039% ▲
Body11%54%57%55.3%±9.80% ▼
T65%68%61%65.2%±5.361% ▼

Optimal v Serena Williams: +0.8±0.8 per 100 first serves (faults included) over the current mix. Serving wide every time would read +8.3 per 100 first serves in before the returner adjusts.

Serena Williams serving

Deuce court

1st serveNowSerena winsv TatjanaMatchupOptimal
Wide50%70%61%65.5%±6.043% ▼
Body8%62%61%65.2%±7.60% ▼
T42%79%66%78.3%±4.457% ▲

Optimal v Tatjana Maria: +0.6±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSerena winsv TatjanaMatchupOptimal
Wide45%75%58%68.7%±5.354% ▲
Body6%60%58%62.1%±8.20% ▼
T49%70%56%61.9%±6.546% ▼

Optimal v Tatjana Maria: +0.2±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.8 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.

Tatjana Maria returning

1st serve to the forehand

ReturnNowTourOwnv SerenaValue
FH slice through the middle44%−6.7+3.5+2.1−1.1±2.2
FH slice crosscourt19%−6.6+4.2−2.4−4.8±2.7
FH through the middle14%+4.2−3.2−1.3−0.4±2.4
FH crosscourt11%+5.3+0.7−4.0+2.1±3.4
FH slice down the line9%−10.5+3.7+0.9−5.8±3.3

Lean FH crosscourt: +3.8±3.3 per 100 returns v the current mix (254 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SerenaValue
BH slice through the middle46%−6.2+4.6−0.2−1.9±2.1
BH slice crosscourt31%−4.2+3.2−2.8−3.8±2.8
BH slice down the line9%−12.5+3.9−1.2−9.7±3.6
BH through the middle8%+6.0−1.0−1.0+4.0±2.3
BH crosscourt4%+7.7+0.9−0.2+8.4±2.8

Lean BH crosscourt: +10.7±3.0 per 100 returns v the current mix (356 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SerenaValue
FH slice through the middle33%−15.2+3.0−0.4−12.6±2.3
FH crosscourt25%+0.5−0.4−3.0−2.9±3.6
FH through the middle16%−3.2−0.3−0.9−4.4±2.1
FH slice crosscourt14%−14.9+1.4±0.0−13.5±2.3
FH slice down the line12%−14.1+1.2±0.0−12.9±1.9

Lean FH crosscourt: +6.1±2.8 per 100 returns v the current mix (76 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv SerenaValue
BH slice through the middle34%−11.7+1.2+0.8−9.7±2.4
BH slice crosscourt30%−7.5+0.2−1.0−8.2±2.7
BH through the middle7%−2.6−0.5−0.3−3.3±1.9
BH slice down the line7%−10.6+4.5±0.0−6.1±2.6
BH down the line6%−0.5−1.3−2.1−3.9±3.9

Lean BH through the middle: +3.6±2.1 per 100 returns v the current mix (202 returns charted)

Serena Williams returning

1st serve to the forehand

ReturnNowTourOwnv TatjanaValue
FH through the middle49%+4.2−2.6−0.1+1.4±2.1
FH crosscourt36%+5.3−1.6+0.4+4.1±3.4
FH down the line11%+1.5−0.4−6.0−4.9±4.1
BH through the middle1%+5.2−3.4−2.0−0.1±2.7
FH slice through the middle1%−6.7−0.7±0.0−7.4±2.3

Lean FH crosscourt: +2.5±2.5 per 100 returns v the current mix (2166 returns charted)

1st serve to the backhand

ReturnNowTourOwnv TatjanaValue
BH through the middle48%+6.0+0.3−2.0+4.3±2.1
BH crosscourt33%+7.7+1.3−2.5+6.6±2.9
BH down the line12%+2.2+1.1−6.2−2.9±4.2
BH slice through the middle3%−6.2−4.5+0.3−10.4±2.6
BH slice crosscourt2%−4.2−2.8−1.5−8.5±2.9
FH through the middle1%+5.1+2.0−0.1+6.9±2.5

Lean FH through the middle: +3.5±2.9 per 100 returns v the current mix (1939 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv TatjanaValue
FH crosscourt43%+0.5−0.5+3.2+3.3±3.8
FH through the middle37%−3.2−0.1+0.4−2.9±2.5
FH down the line18%−0.6+5.3−0.1+4.7±4.9
BH inside-in1%+2.0−1.4±0.0+0.6±3.5
BH through the middle1%−1.0−0.2+2.2+1.0±2.1

Lean FH down the line: +3.5±4.5 per 100 returns v the current mix (750 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv TatjanaValue
BH crosscourt51%+1.5+0.9±0.0+2.4±3.0
BH through the middle30%−2.6−1.8+2.2−2.2±2.3
BH down the line17%−0.5+3.4−1.1+1.7±4.9
FH inside-in1%+0.7+0.7+3.2+4.7±4.0
FH inside-out1%+1.4+0.2−0.1+1.4±3.6

Lean BH crosscourt: +1.6±1.8 per 100 returns v the current mix (954 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.

Tatjana Maria

Favour

ShotEdgeOwnTheirs
FH slice to their backhand · rally+5.6±3.5+5.5+0.1
BH slice to their backhand · serve +1+4.8±2.9+3.8+1.0
FH slice to the middle · return+4.7±2.0+2.6+2.1
FH slice to their forehand · rally+4.3±3.5+3.2+1.1
FH slice to the middle · serve +1+4.3±2.7+4.3−0.1
BH slice to the middle · serve +1+3.2±2.2+0.4+2.8

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−3.1±2.3−1.9−1.3
FH to their forehand · return−2.4±3.5+1.3−3.6
BH slice to their backhand · return−1.5±2.6+1.3−2.9
FH to their backhand · rally−1.0±3.1−0.9−0.1
FH to their backhand · serve +1−0.1±3.3+1.8−2.0

Serena Williams

Favour

ShotEdgeOwnTheirs
FH to their forehand · return+2.0±3.1+0.1+1.9
FH volley to their forehand · rally+1.3±5.3+1.9−0.7
FH to their backhand · return +1+0.5±3.1+1.7−1.1
BH to their backhand · return−0.8±2.6+1.1−1.9
BH to the middle · return−1.1±1.8−0.4−0.6
FH to their backhand · return−1.2±3.1+2.9−4.1

Avoid

ShotEdgeOwnTheirs
BH slice to their backhand · rally−8.3±2.7−2.9−5.5
BH to their backhand · rally−7.0±1.8−1.4−5.6
BH slice to the middle · rally−6.9±2.2−2.3−4.6
BH to the middle · serve +1−6.1±2.1−1.9−4.3
FH volley to their backhand · rally−5.5±5.5+0.9−6.4

Against Serena Williams-like opponents

Tatjana Maria vMatchesServe pts wonReturn pts won
All charted opponents–58.5%42.6%
Players most similar to Serena Williams1 53.4%47.2%

Similar by tactical fingerprint: Naomi Osaka, Karolina Pliskova, Ekaterina Alexandrova, Sorana Cirstea, Elena Gabriela Ruse, Veronika Kudermetova, Anett Kontaveit, Daniela Hantuchova, Jelena Dokic, Lindsay Davenport. When two players have rarely met, their records against these lookalikes fill the gap.