Game plan

Jil Teichmann v Magdalena Frech

Every number combines what Jil Teichmann does well with what Magdalena Frech allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jil Teichmann wins, best of 3 53%90%: 27%–78% · best of 5: 54%

Serve points won 56.0% / 55.4% Jil / Magdalena · tour 56.4%

Strengths only, no similarity priors 52%serve 56.2% / 55.8%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Jil Teichmann's record against Magdalena Frech's tactical lookalikes and in their charted head-to-heads (lookalikes: −1.2 on serve, +2.2 on return vs expectation (628 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	Jil	Magdalena
Direction choice	−0.19 ±0.09 better than 18%	+0.14 ±0.09 better than 78%
Shot selection	+0.14 ±0.14 better than 60%	−0.42 ±0.11 better than 15%
Execution	−0.19 ±0.42 better than 51%	+1.36 ±0.49 better than 96%
Points left on the table	3.14 ±0.15 lower than 6%	2.39 ±0.15 lower than 78%

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: Jil Teichmann +1.35, Magdalena Frech +1.35. 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.

Jil Teichmann serving

Deuce court

1st serve	Now	Jil wins	v Magdalena	Matchup	Optimal
Wide	31%	61%	68%	62.7%±7.5	31%
Body	25%	56%	57%	55.7%±8.4	10% ▼
T	44%	61%	71%	64.7%±7.4	59% ▲

Optimal v Magdalena Frech: +0.8±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.9 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Jil wins	v Magdalena	Matchup	Optimal
Wide	52%	64%	66%	64.4%±6.7	52%
Body	23%	57%	61%	61.6%±8.5	8% ▼
T	24%	66%	68%	69.7%±7.9	40% ▲

Optimal v Magdalena Frech: +0.7±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.6 per 100 first serves in before the returner adjusts.

Magdalena Frech serving

Deuce court

1st serve	Now	Magdalena wins	v Jil	Matchup	Optimal
Wide	37%	62%	65%	60.7%±6.8	34% ▼
Body	12%	59%	57%	58.1%±10.2	0% ▼
T	51%	63%	67%	62.3%±7.2	66% ▲

Optimal v Jil Teichmann: +0.6±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.1 per 100 first serves in before the returner adjusts.

Ad court

1st serve	Now	Magdalena wins	v Jil	Matchup	Optimal
Wide	47%	66%	65%	65.4%±7.2	62% ▲
Body	13%	48%	60%	51.5%±10.1	13%
T	40%	56%	60%	51.0%±7.4	25% ▼

Optimal v Jil Teichmann: +0.8±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +7.5 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.

Jil Teichmann returning

1st serve to the forehand

Return	Now	Tour	Own	v Magdalena	Value
FH through the middle	50%	+4.2	+1.2	+2.3	+7.7±2.5
FH crosscourt	27%	+5.3	+2.6	+0.5	+8.5±4.2
FH down the line	13%	+1.5	−0.2	+2.0	+3.3±4.7
FH slice through the middle	6%	−6.7	−0.3	+1.2	−5.8±2.5
FH slice crosscourt	4%	−6.6	+1.6	±0.0	−4.9±2.0

Lean FH crosscourt: +2.6±3.4 per 100 returns v the current mix (400 returns charted, inside the 90% margin)

1st serve to the backhand

Return	Now	Tour	Own	v Magdalena	Value
BH through the middle	55%	+6.0	±0.0	+0.6	+6.6±2.2
BH crosscourt	22%	+7.7	+1.1	−0.9	+7.9±3.5
BH down the line	13%	+2.2	−0.2	+1.5	+3.6±4.6
BH slice through the middle	7%	−6.2	−0.9	−0.4	−7.6±2.5
BH slice crosscourt	2%	−4.2	−0.8	±0.0	−4.9±1.8

Lean BH crosscourt: +3.0±3.1 per 100 returns v the current mix (570 returns charted, inside the 90% margin)

2nd serve to the forehand

Return	Now	Tour	Own	v Magdalena	Value
FH through the middle	44%	−3.2	−2.1	−1.7	−7.0±3.0
FH crosscourt	41%	+0.5	−1.4	−0.4	−1.2±4.5
FH down the line	16%	−0.6	+1.3	+0.9	+1.6±4.8

Lean FH down the line: +4.9±4.6 per 100 returns v the current mix (116 returns charted)

2nd serve to the backhand

Return	Now	Tour	Own	v Magdalena	Value
BH through the middle	39%	−2.6	−0.4	+0.9	−2.2±2.7
BH crosscourt	36%	+1.5	−0.4	+1.3	+2.3±3.6
FH inside-in	9%	+0.7	+2.2	−0.4	+2.6±4.6
FH through the middle	8%	−2.7	+1.2	−1.7	−3.2±2.4
BH down the line	6%	−0.5	−2.2	−2.7	−5.5±4.8

Lean FH inside-in: +2.8±4.5 per 100 returns v the current mix (244 returns charted, inside the 90% margin)

Magdalena Frech returning

1st serve to the forehand

Return	Now	Tour	Own	v Jil	Value
FH through the middle	39%	+4.2	+2.5	+1.4	+8.0±2.6
FH slice through the middle	25%	−6.7	+1.5	−1.1	−6.3±2.5
FH down the line	16%	+1.5	−0.6	−3.9	−3.0±4.7
FH crosscourt	14%	+5.3	+0.1	+2.1	+7.5±4.1
FH slice down the line	4%	−10.5	+1.5	−0.7	−9.7±2.4

Lean FH through the middle: +6.4±1.9 per 100 returns v the current mix (317 returns charted)

1st serve to the backhand

Return	Now	Tour	Own	v Jil	Value
BH through the middle	41%	+6.0	+2.1	+0.3	+8.4±2.3
BH crosscourt	27%	+7.7	+1.5	+3.3	+12.6±3.5
BH slice through the middle	13%	−6.2	+1.2	+0.3	−4.7±2.6
BH down the line	8%	+2.2	+2.1	−1.4	+2.8±4.3
BH slice crosscourt	8%	−4.2	−0.9	−0.1	−5.2±2.7

Lean BH crosscourt: +6.8±2.8 per 100 returns v the current mix (300 returns charted)

2nd serve to the forehand

Return	Now	Tour	Own	v Jil	Value
FH through the middle	49%	−3.2	+1.1	+2.7	+0.6±2.9
FH crosscourt	26%	+0.5	+0.1	+0.6	+1.2±4.1
FH down the line	25%	−0.6	+1.8	−2.3	−1.1±4.8

Lean FH crosscourt: +0.9±3.5 per 100 returns v the current mix (68 returns charted, inside the 90% margin)

2nd serve to the backhand

Return	Now	Tour	Own	v Jil	Value
BH crosscourt	37%	+1.5	+1.2	−2.8	−0.1±3.5
BH down the line	34%	−0.5	+3.5	+0.3	+3.3±5.3
BH through the middle	29%	−2.6	+1.5	+2.0	+1.0±2.6

Lean BH down the line: +1.9±3.8 per 100 returns v the current mix (139 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.

Jil Teichmann

Favour

Shot	Edge	Own	Theirs
BH to the middle · return +1	+5.5±3.3	+0.9	+4.6
FH to their backhand · return +1	+5.4±5.2	+2.0	+3.4
FH to their forehand · return +1	+5.3±5.2	+3.7	+1.6
BH to their forehand · return +1	+5.2±6.7	+1.5	+3.6
FH to the middle · return +1	+4.5±3.5	+1.1	+3.4
BH to the middle · return	+3.3±2.6	+1.2	+2.1

Avoid

Shot	Edge	Own	Theirs
BH slice to their backhand · rally	−8.6±4.3	−5.5	−3.1
BH to their backhand · return	−4.8±4.8	−3.3	−1.4
FH to their forehand · rally	−4.4±3.2	−5.8	+1.3
FH to their backhand · return	−2.9±5.4	−0.5	−2.5
FH to their forehand · serve +1	−1.8±4.7	+0.4	−2.2

Magdalena Frech

Favour

Shot	Edge	Own	Theirs
FH to their backhand · return	+6.5±5.8	+4.7	+1.9
BH to their backhand · serve +1	+5.2±4.9	+0.6	+4.6
BH to their forehand · serve +1	+4.2±6.0	+0.9	+3.4
FH to the middle · return	+3.9±3.1	+2.6	+1.3
BH to their backhand · rally	+3.8±3.3	+2.3	+1.5
FH to their backhand · return +1	+3.7±5.4	+2.4	+1.3

Avoid

Shot	Edge	Own	Theirs
FH to their forehand · return	−12.2±6.1	−3.6	−8.6
BH slice to their backhand · rally	−6.3±4.1	+1.0	−7.4
FH to their backhand · rally	−3.8±3.3	−1.0	−2.8
BH to their backhand · return	−1.8±4.6	−0.3	−1.6
FH to their forehand · rally	−1.6±3.1	+1.5	−3.1

Against Magdalena Frech-like opponents

Jil Teichmann v	Matches	Serve pts won	Return pts won
All charted opponents	–	54.7%	42.8%
Players most similar to Magdalena Frech	3	52.9%	44.6%

Similar by tactical fingerprint: Elina Svitolina, Daria Kasatkina, Jaqueline Cristian, Victoria Azarenka, Linda Fruhvirtova, Caroline Wozniacki, Vera Zvonareva, Agnieszka Radwanska, Flavia Pennetta, Dinara Safina. When two players have rarely met, their records against these lookalikes fill the gap.