Game plan

Laura Siegemund v Tatjana Maria

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

Forecast

Laura Siegemund wins, best of 3 34%90%: 11%–64% · best of 5: 30%

Serve points won 55.2% / 58.4% Laura / Tatjana · tour 56.3%

Strengths only, no similarity priors 35%serve 55.4% / 58.3%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Laura Siegemund's record against Tatjana Maria's tactical lookalikes and in their charted head-to-heads (lookalikes: −6.2 on serve, −2.4 on return vs expectation (110 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

Career	Laura	Tatjana
Direction choice	−0.01 ±0.09 better than 52%	+0.17 ±0.11 better than 82%
Shot selection	−0.15 ±0.31 better than 32%	−4.80 ±0.55 better than 0%
Execution	−1.01 ±0.57 better than 17%	+1.80 ±0.44 better than 98%
Points left on the table	2.66 ±0.08 lower than 41%	3.32 ±0.20 lower than 3%

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: Laura Siegemund −3.51, Tatjana Maria +1.26. 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.

Laura Siegemund serving

Deuce court

1st serve	Now	Laura wins	v Tatjana	Matchup	Optimal
Wide	38%	61%	61%	55.3%±8.1	38%
Body	38%	57%	61%	60.3%±8.0	23% ▼
T	24%	65%	66%	63.0%±8.3	39% ▲

Optimal v Tatjana Maria: +0.4±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.0 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Laura wins	v Tatjana	Matchup	Optimal
Wide	30%	57%	58%	49.3%±8.0	45% ▲
Body	34%	53%	58%	55.6%±8.6	29% ▼
T	36%	59%	56%	50.8%±8.5	26% ▼

Optimal v Tatjana Maria: +0.2±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +3.6 per 100 first serves in before the returner adjusts.

Tatjana Maria serving

Deuce court

1st serve	Now	Tatjana wins	v Laura	Matchup	Optimal
Wide	38%	70%	66%	70.0%±6.7	54% ▲
Body	14%	60%	61%	63.4%±10.4	0% ▼
T	47%	75%	71%	78.1%±6.5	46% ▼

Optimal v Laura Siegemund: +1.4±1.0 per 100 first serves (faults included) over the current mix. Serving T every time would read +5.2 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Tatjana wins	v Laura	Matchup	Optimal
Wide	24%	74%	67%	75.5%±7.8	39% ▲
Body	11%	54%	53%	50.7%±11.5	0% ▼
T	65%	68%	64%	68.1%±7.0	61% ▼

Optimal v Laura Siegemund: +1.1±1.0 per 100 first serves (faults included) over the current mix. Serving wide every time would read +7.6 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.

Laura Siegemund returning

1st serve to the forehand

Return	Now	Tour	Own	v Tatjana	Value
FH through the middle	37%	+4.2	−2.3	−0.1	+1.7±2.7
FH crosscourt	20%	+5.3	−4.3	+0.4	+1.4±4.3
FH down the line	17%	+1.5	+1.4	−6.0	−3.2±4.6
FH slice through the middle	13%	−6.7	−0.8	±0.0	−7.5±2.6
FH slice crosscourt	9%	−6.6	+0.7	−2.5	−8.3±2.6

Lean FH through the middle: +3.6±2.1 per 100 returns v the current mix (385 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Tatjana	Value
BH through the middle	45%	+6.0	+1.0	−2.0	+5.0±2.7
BH crosscourt	23%	+7.7	−2.1	−2.5	+3.2±3.7
BH slice through the middle	12%	−6.2	−2.8	+0.3	−8.8±2.5
BH down the line	9%	+2.2	−2.0	−6.2	−6.0±4.6
BH slice crosscourt	5%	−4.2	−0.2	−1.5	−5.9±2.7

Lean BH through the middle: +4.6±1.8 per 100 returns v the current mix (311 returns charted)

2nd serve to the forehand

Return	Now	Tour	Own	v Tatjana	Value
FH through the middle	34%	−3.2	−1.4	+0.4	−4.2±2.9
FH crosscourt	26%	+0.5	−1.0	+3.2	+2.8±4.3
FH slice crosscourt	15%	−14.9	+0.3	±0.0	−14.6±1.6
FH down the line	14%	−0.6	−0.2	−0.1	−0.8±4.7
FH slice through the middle	10%	−15.2	−0.9	±0.0	−16.1±1.3

Lean FH crosscourt: +7.5±3.4 per 100 returns v the current mix (87 returns charted)

2nd serve to the backhand

Return	Now	Tour	Own	v Tatjana	Value
BH through the middle	40%	−2.6	−0.5	+2.2	−0.9±2.7
BH crosscourt	36%	+1.5	−1.2	±0.0	+0.3±3.6
BH down the line	20%	−0.5	+3.1	−1.1	+1.4±5.1
FH through the middle	4%	−2.7	+0.4	+0.4	−1.9±2.1

Lean BH down the line: +1.5±4.4 per 100 returns v the current mix (138 returns charted, inside the 90% margin)

Tatjana Maria returning

1st serve to the forehand

Return	Now	Tour	Own	v Laura	Value
FH slice through the middle	44%	−6.7	+3.5	+0.5	−2.7±2.4
FH slice crosscourt	19%	−6.6	+4.2	+0.7	−1.7±2.3
FH through the middle	14%	+4.2	−3.2	+1.0	+1.9±2.7
FH crosscourt	11%	+5.3	+0.7	+0.6	+6.6±3.9
FH slice down the line	9%	−10.5	+3.7	±0.0	−6.8±2.3

Lean FH crosscourt: +7.7±3.7 per 100 returns v the current mix (254 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Laura	Value
BH slice through the middle	46%	−6.2	+4.6	−0.4	−2.0±2.0
BH slice crosscourt	31%	−4.2	+3.2	−0.9	−1.9±2.4
BH slice down the line	9%	−12.5	+3.9	−0.7	−9.2±2.9
BH through the middle	8%	+6.0	−1.0	−0.1	+4.9±2.5
BH crosscourt	4%	+7.7	+0.9	−1.0	+7.7±3.1

Lean BH crosscourt: +9.3±3.3 per 100 returns v the current mix (356 returns charted)

2nd serve to the forehand

Return	Now	Tour	Own	v Laura	Value
FH slice through the middle	33%	−15.2	+3.0	±0.0	−12.2±1.8
FH crosscourt	25%	+0.5	−0.4	−1.7	−1.6±4.2
FH through the middle	16%	−3.2	−0.3	−1.7	−5.1±2.7
FH slice crosscourt	14%	−14.9	+1.4	±0.0	−13.5±1.6
FH slice down the line	12%	−14.1	+1.2	±0.0	−12.9±1.9

Lean FH crosscourt: +7.1±3.3 per 100 returns v the current mix (76 returns charted)

2nd serve to the backhand

Return	Now	Tour	Own	v Laura	Value
BH slice through the middle	34%	−11.7	+1.2	±0.0	−10.4±1.7
BH slice crosscourt	30%	−7.5	+0.2	±0.0	−7.3±2.1
BH through the middle	7%	−2.6	−0.5	−1.1	−4.2±2.6
BH slice down the line	7%	−10.6	+4.5	±0.0	−6.1±2.6
BH down the line	6%	−0.5	−1.3	+2.0	+0.1±4.8

Lean BH through the middle: +2.6±2.6 per 100 returns v the current mix (202 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.

Laura Siegemund

Favour

Shot	Edge	Own	Theirs
FH volley to their forehand · rally	+0.6±5.7	+1.2	−0.7
BH to the middle · return	+0.4±2.2	+1.1	−0.6
FH to the middle · serve +1	−0.7±2.6	+2.1	−2.8
BH to their forehand · rally	−0.8±4.1	+3.1	−3.9
FH to their forehand · return	−1.7±4.0	−3.6	+1.9
FH to the middle · return +1	−2.2±2.8	−0.5	−1.8

Avoid

Shot	Edge	Own	Theirs
FH to their forehand · rally	−7.5±2.6	−3.8	−3.7
FH to their forehand · serve +1	−7.3±3.1	−2.2	−5.1
BH to their backhand · rally	−6.0±2.5	−0.4	−5.6
BH to their backhand · return +1	−5.9±3.4	−2.3	−3.7
BH to their forehand · return	−5.7±4.4	−0.4	−5.2

Tatjana Maria

Favour

Shot	Edge	Own	Theirs
FH to their forehand · return	+1.6±4.0	+1.3	+0.3
FH to their forehand · serve +1	−0.2±3.5	+0.8	−1.1
FH to the middle · rally	−0.3±2.5	+0.5	−0.8
FH to their forehand · rally	−0.8±3.1	+1.3	−2.1
FH to the middle · return	−1.1±2.6	−1.9	+0.8
FH to their backhand · rally	−1.7±3.7	−0.9	−0.8

Avoid

Shot	Edge	Own	Theirs
FH to their backhand · serve +1	−3.1±4.0	+1.8	−4.9
FH to their backhand · rally	−1.7±3.7	−0.9	−0.8
FH to the middle · return	−1.1±2.6	−1.9	+0.8
FH to their forehand · rally	−0.8±3.1	+1.3	−2.1
FH to the middle · rally	−0.3±2.5	+0.5	−0.8

Against Tatjana Maria-like opponents

Laura Siegemund v	Matches	Serve pts won	Return pts won
All charted opponents	–	52.8%	41.7%
Players most similar to Tatjana Maria	1	46.4%	33.3%

Similar by tactical fingerprint: Karolina Muchova, Viktorija Golubic, Diane Parry, Alison Van Uytvanck, Kirsten Flipkens, Ashleigh Barty, Francesca Schiavone, Roberta Vinci, Justine Henin, Amelie Mauresmo. When two players have rarely met, their records against these lookalikes fill the gap.