Game plan

Tatjana Maria v Maja Chwalinska

Every number combines what Tatjana Maria does well with what Maja Chwalinska 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 43%90%: 11%–82% · best of 5: 42%

Serve points won 55.4% / 56.6% Tatjana / Maja · tour 56.4%

Strengths only, no similarity priors 41%serve 55.6% / 57.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Maja Chwalinska's tactical lookalikes and in their charted head-to-heads (lookalikes: −5.9 on serve, +17.4 on return vs expectation (107 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	Tatjana	Maja
Direction choice	+0.17 ±0.11 better than 82%	−0.08 ±0.06 better than 40%
Shot selection	−4.80 ±0.55 better than 0%	−0.52 ±0.28 better than 11%
Execution	+1.80 ±0.44 better than 98%	+2.12 ±0.53 better than 99%
Points left on the table	3.32 ±0.20 lower than 3%	2.93 ±0.10 lower than 14%

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 +1.33, Maja Chwalinska −1.25. 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 serve	Now	Tatjana wins	v Maja	Matchup	Optimal
Wide	38%	70%	58%	61.9%±8.3	54% ▲
Body	14%	60%	57%	59.2%±11.8	0% ▼
T	47%	75%	62%	69.9%±8.9	46% ▼

Optimal v Maja Chwalinska: +0.5±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.6 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Tatjana wins	v Maja	Matchup	Optimal
Wide	24%	74%	59%	68.5%±10.7	39% ▲
Body	11%	54%	53%	51.0%±12.5	0% ▼
T	65%	68%	58%	62.4%±8.1	61% ▼

Optimal v Maja Chwalinska: +0.7±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +5.8 per 100 first serves in before the returner adjusts.

Maja Chwalinska serving

Deuce court

1st serve	Now	Maja wins	v Tatjana	Matchup	Optimal
Wide	26%	62%	61%	56.2%±10.3	15% ▼
Body	28%	55%	61%	58.6%±9.9	24% ▼
T	46%	65%	66%	63.5%±8.3	61% ▲

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 +3.3 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Maja wins	v Tatjana	Matchup	Optimal
Wide	53%	60%	58%	52.6%±8.3	52%
Body	22%	53%	58%	54.9%±10.9	7% ▼
T	26%	67%	56%	58.9%±11.1	41% ▲

Optimal v Tatjana Maria: +0.2±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.2 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.

Tatjana Maria returning

1st serve to the forehand

Return	Now	Tour	Own	v Maja	Value
FH slice through the middle	44%	−6.7	+3.5	−1.2	−4.5±2.1
FH slice crosscourt	19%	−6.6	+4.2	+1.0	−1.5±2.5
FH through the middle	14%	+4.2	−3.2	+0.2	+1.1±3.1
FH crosscourt	11%	+5.3	+0.7	+2.7	+8.7±4.3
FH slice down the line	9%	−10.5	+3.7	±0.0	−6.8±2.3

Lean FH crosscourt: +10.3±4.0 per 100 returns v the current mix (254 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Maja	Value
BH slice through the middle	46%	−6.2	+4.6	+0.6	−1.1±2.0
BH slice crosscourt	31%	−4.2	+3.2	±0.0	−1.0±2.0
BH slice down the line	9%	−12.5	+3.9	±0.0	−8.6±2.5
BH through the middle	8%	+6.0	−1.0	+2.1	+7.1±2.7
BH crosscourt	4%	+7.7	+0.9	+1.3	+10.0±3.4

Lean BH crosscourt: +10.5±3.4 per 100 returns v the current mix (356 returns charted)

2nd serve to the forehand

Return	Now	Tour	Own	v Maja	Value
FH slice through the middle	33%	−15.2	+3.0	±0.0	−12.2±1.8
FH crosscourt	25%	+0.5	−0.4	+0.4	+0.5±4.1
FH through the middle	16%	−3.2	−0.3	−1.2	−4.7±2.8
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: +8.6±3.2 per 100 returns v the current mix (76 returns charted)

2nd serve to the backhand

Return	Now	Tour	Own	v Maja	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	+1.4	−1.7±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	−1.4	−3.3±4.4

Lean BH through the middle: +4.9±2.6 per 100 returns v the current mix (202 returns charted)

Maja Chwalinska returning

1st serve to the forehand

Return	Now	Tour	Own	v Tatjana	Value
FH through the middle	41%	+4.2	+3.2	−0.1	+7.2±2.9
FH crosscourt	21%	+5.3	+3.3	−6.0	+2.5±4.1
FH slice through the middle	17%	−6.7	+1.6	±0.0	−5.1±2.4
FH down the line	14%	+1.5	+1.1	+0.4	+3.0±4.4
FH slice crosscourt	7%	−6.6	+1.5	−1.8	−7.0±2.2

Lean FH through the middle: +4.7±2.1 per 100 returns v the current mix (111 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Tatjana	Value
BH through the middle	43%	+6.0	+1.2	−2.0	+5.2±2.8
BH crosscourt	33%	+7.7	+2.4	−6.2	+4.0±3.6
BH down the line	16%	+2.2	+3.6	−2.5	+3.3±4.7
BH slice through the middle	3%	−6.2	−0.5	+0.3	−6.5±2.2
BH slice crosscourt	3%	−4.2	+0.1	−0.4	−4.5±1.9

Lean BH through the middle: +1.8±2.1 per 100 returns v the current mix (236 returns charted, inside the 90% margin)

2nd serve to the backhand

Return	Now	Tour	Own	v Tatjana	Value
BH through the middle	31%	−2.6	+1.6	+2.2	+1.1±2.7
BH crosscourt	29%	+1.5	±0.0	−1.1	+0.4±3.6
FH through the middle	18%	−2.7	−1.1	+0.4	−3.4±2.4
BH down the line	11%	−0.5	−1.3	±0.0	−1.8±4.7
FH inside-in	5%	+0.7	+0.5	−0.1	+1.2±3.9

Lean BH through the middle: +1.2±2.3 per 100 returns v the current mix (110 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.

Tatjana Maria

Favour

Shot	Edge	Own	Theirs
FH to their forehand · serve +1	+1.0±5.7	+1.8	−0.8
FH to their forehand · return	+0.9±6.3	+1.0	−0.1
FH to their backhand · serve +1	+0.5±6.1	+1.3	−0.8
FH to the middle · return	−2.1±4.2	−1.7	−0.5
FH to their forehand · rally	−2.6±5.0	+2.2	−4.7
FH to their backhand · rally	−2.8±5.6	−1.9	−0.9

Avoid

Shot	Edge	Own	Theirs
FH to the middle · rally	−2.9±3.8	−0.4	−2.5
FH to their backhand · rally	−2.8±5.6	−1.9	−0.9
FH to their forehand · rally	−2.6±5.0	+2.2	−4.7
FH to the middle · return	−2.1±4.2	−1.7	−0.5
FH to their backhand · serve +1	+0.5±6.1	+1.3	−0.8

Maja Chwalinska

Favour

Shot	Edge	Own	Theirs
BH to the middle · return	+3.5±3.0	+3.3	+0.3
FH to their backhand · return +1	+2.9±4.8	+3.9	−1.0
FH to their forehand · rally	+1.6±4.1	+4.1	−2.6
FH to their backhand · return	−0.1±5.9	+4.0	−4.0
BH to the middle · rally	−0.1±3.3	+1.9	−2.0
BH to their backhand · return	−0.2±4.4	+2.8	−2.9

Avoid

Shot	Edge	Own	Theirs
FH to their backhand · serve +1	−8.1±5.0	−2.6	−5.5
FH to their forehand · serve +1	−6.7±4.4	+1.6	−8.3
BH slice to their backhand · rally	−5.8±4.0	+0.3	−6.0
BH slice to the middle · rally	−4.1±3.3	+1.5	−5.6
BH to their forehand · serve +1	−3.4±6.2	+3.9	−7.3

Against Maja Chwalinska-like opponents

Tatjana Maria v	Matches	Serve pts won	Return pts won
All charted opponents	–	58.5%	42.6%
Players most similar to Maja Chwalinska	1	53.8%	58.2%

Similar by tactical fingerprint: Magdalena Frech, Sara Bejlek, Kaja Juvan, Tiantsoa Sarah Rakotomanga Rajaonah, Sara Errani, Angelique Kerber, Brenda Fruhvirtova, Martina Trevisan, Kateryna Baindl, Agnieszka Radwanska. When two players have rarely met, their records against these lookalikes fill the gap.