Game plan

Tamara Zidansek v Maja Chwalinska

Every number combines what Tamara Zidansek 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

Tamara Zidansek wins, best of 3 24%90%: 7%–53% · best of 5: 18%

Serve points won 51.0% / 56.4% Tamara / Maja · tour 55.0%

Strengths only, no similarity priors 24%serve 51.0% / 56.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Tamara Zidansek's record against Maja Chwalinska's tactical lookalikes and in their charted head-to-heads. 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	Tamara	Maja
Direction choice	−0.10 ±0.09 better than 36%	−0.08 ±0.06 better than 40%
Shot selection	+0.29 ±0.17 better than 78%	−0.52 ±0.28 better than 11%
Execution	−0.43 ±0.41 better than 36%	+2.12 ±0.53 better than 99%
Points left on the table	2.62 ±0.11 lower than 49%	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: Tamara Zidansek ±0.00, Maja Chwalinska +1.37. 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.

Tamara Zidansek serving

Deuce court

1st serve	Now	Tamara wins	v Maja	Matchup	Optimal
Wide	39%	64%	58%	55.8%±8.3	40%
Body	34%	55%	57%	54.6%±9.8	19% ▼
T	26%	68%	62%	61.3%±10.2	41% ▲

Optimal v Maja Chwalinska: +0.7±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.4 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Tamara wins	v Maja	Matchup	Optimal
Wide	42%	63%	59%	56.4%±10.2	41%
Body	27%	52%	53%	48.8%±10.6	12% ▼
T	32%	64%	58%	57.4%±9.1	47% ▲

Optimal v Maja Chwalinska: +0.5±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.7 per 100 first serves in before the returner adjusts.

Maja Chwalinska serving

Deuce court

1st serve	Now	Maja wins	v Tamara	Matchup	Optimal
Wide	26%	62%	68%	64.1%±9.8	26%
Body	28%	55%	52%	49.6%±10.1	13% ▼
T	46%	65%	64%	61.1%±8.6	61% ▲

Optimal v Tamara Zidansek: +0.7±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +5.5 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Maja wins	v Tamara	Matchup	Optimal
Wide	53%	60%	63%	57.7%±8.2	47% ▼
Body	22%	53%	62%	58.7%±11.1	12% ▼
T	26%	67%	62%	65.0%±10.6	41% ▲

Optimal v Tamara Zidansek: +0.3±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.2 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.

Tamara Zidansek returning

1st serve to the forehand

Return	Now	Tour	Own	v Maja	Value
FH through the middle	49%	+4.2	−0.6	+0.2	+3.7±3.0
FH down the line	21%	+1.5	−0.1	+3.2	+4.7±4.7
FH crosscourt	17%	+5.3	+0.5	+2.7	+8.5±4.4
FH slice through the middle	7%	−6.7	−1.9	−1.2	−9.9±2.0
FH slice crosscourt	5%	−6.6	+0.1	+1.0	−5.5±2.2

Lean FH crosscourt: +5.5±4.0 per 100 returns v the current mix (244 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Maja	Value
BH through the middle	52%	+6.0	+0.4	+2.1	+8.5±2.5
BH crosscourt	18%	+7.7	−0.5	+1.3	+8.6±3.6
BH down the line	16%	+2.2	−0.9	+2.7	+4.0±4.7
BH slice through the middle	8%	−6.2	−0.4	+0.6	−6.1±2.1
BH slice crosscourt	4%	−4.2	−0.4	±0.0	−4.5±1.8

Lean BH crosscourt: +2.8±3.4 per 100 returns v the current mix (334 returns charted, inside the 90% margin)

2nd serve to the forehand

Return	Now	Tour	Own	v Maja	Value
FH through the middle	43%	−3.2	+2.4	−1.2	−2.0±3.1
FH crosscourt	29%	+0.5	+0.9	+0.4	+1.8±4.2
FH down the line	19%	−0.6	+1.0	−1.4	−1.0±4.7
FH slice through the middle	10%	−15.2	+0.3	±0.0	−14.9±1.3

Lean FH crosscourt: +3.8±3.4 per 100 returns v the current mix (91 returns charted)

2nd serve to the backhand

Return	Now	Tour	Own	v Maja	Value
BH through the middle	38%	−2.6	±0.0	+1.4	−1.2±2.8
BH crosscourt	23%	+1.5	−1.0	−0.1	+0.4±3.6
FH inside-out	12%	+1.4	+1.3	−1.4	+1.3±3.9
FH through the middle	11%	−2.7	+0.8	−1.2	−3.1±2.4
BH down the line	8%	−0.5	−0.1	−1.4	−2.1±4.3

Lean FH inside-out: +1.9±3.7 per 100 returns v the current mix (130 returns charted, inside the 90% margin)

Maja Chwalinska returning

1st serve to the forehand

Return	Now	Tour	Own	v Tamara	Value
FH through the middle	41%	+4.2	+3.2	+1.1	+8.4±2.9
FH crosscourt	21%	+5.3	+3.3	+0.6	+9.1±4.1
FH slice through the middle	17%	−6.7	+1.6	+1.2	−4.0±2.1
FH down the line	14%	+1.5	+1.1	−2.9	−0.3±4.2
FH slice crosscourt	7%	−6.6	+1.5	+0.4	−4.8±1.8

Lean FH crosscourt: +4.9±3.6 per 100 returns v the current mix (111 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Tamara	Value
BH through the middle	43%	+6.0	+1.2	+2.0	+9.2±2.5
BH crosscourt	33%	+7.7	+2.4	−3.0	+7.2±3.6
BH down the line	16%	+2.2	+3.6	+1.8	+7.5±4.3
BH slice through the middle	3%	−6.2	−0.5	+1.4	−5.4±2.1
BH slice crosscourt	3%	−4.2	+0.1	±0.0	−4.1±1.3

Lean BH through the middle: +2.2±2.0 per 100 returns v the current mix (236 returns charted)

2nd serve to the backhand

Return	Now	Tour	Own	v Tamara	Value
BH through the middle	31%	−2.6	+1.6	+1.4	+0.4±2.7
BH crosscourt	29%	+1.5	±0.0	+4.3	+5.9±3.6
FH through the middle	18%	−2.7	−1.1	+2.5	−1.3±2.5
BH down the line	11%	−0.5	−1.3	+1.0	−0.9±4.6
FH inside-in	5%	+0.7	+0.5	−1.1	+0.1±4.0

Lean BH crosscourt: +4.5±2.8 per 100 returns v the current mix (110 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 clay. Each player's clay record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Tamara Zidansek

Favour

Shot	Edge	Own	Theirs
FH to their backhand · return	+7.3±5.6	+3.6	+3.6
BH to the middle · return	+6.2±2.7	+2.4	+3.8
BH to their backhand · serve +1	+5.4±5.3	+2.4	+3.0
FH to their backhand · serve +1	+3.4±4.3	+1.5	+1.9
FH to their forehand · return	+3.0±6.2	−1.0	+4.0
BH to the middle · return +1	+3.0±3.5	+1.4	+1.7

Avoid

Shot	Edge	Own	Theirs
BH to their forehand · serve +1	−7.4±6.8	−2.0	−5.3
FH to their backhand · return +1	−5.6±5.1	−2.7	−2.9
BH to their forehand · rally	−3.0±4.7	−1.9	−1.1
BH to their forehand · return	−2.7±5.9	−2.9	+0.2
FH to the middle · rally	−2.7±2.9	−0.4	−2.3

Maja Chwalinska

Favour

Shot	Edge	Own	Theirs
BH to their forehand · return	+7.8±6.2	+6.5	+1.3
BH to their backhand · return	+6.8±4.1	+4.1	+2.7
BH to the middle · return	+6.2±2.9	+3.5	+2.6
FH to their backhand · return +1	+5.0±5.1	+5.3	−0.3
FH to their forehand · rally	+4.9±3.6	+4.1	+0.8
BH to their backhand · rally	+4.7±3.6	+4.8	−0.1

Avoid

Shot	Edge	Own	Theirs
FH to their backhand · serve +1	−4.2±4.5	−1.9	−2.3
FH to their forehand · return +1	−2.7±5.6	−1.9	−0.8
BH to their forehand · serve +1	−2.6±6.9	+4.6	−7.2
BH slice to their backhand · rally	−0.6±3.9	+0.4	−1.1
FH to the middle · rally	−0.6±2.7	+1.0	−1.5

Against Maja Chwalinska-like opponents

Tamara Zidansek v	Matches	Serve pts won	Return pts won
All charted opponents	–	56.4%	43.9%

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.