RallyIQ

Game plan

Suzan Lamens v Johanna Larsson

Every number combines what Suzan Lamens does well with what Johanna Larsson allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Suzan Lamens wins, best of 3 92%90%: 70%–99% · best of 5: 96%
Serve points won 62.8% / 52.2% Suzan / Johanna · tour 56.3%
Strengths only, no similarity priors 92%serve 62.4% / 51.6%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Suzan Lamens's record against Johanna Larsson's tactical lookalikes and in their charted head-to-heads (lookalikes: +2.2 on serve, −4.6 on return vs expectation (522 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

CareerSuzanJohanna
Direction choice−0.13 ±0.09
better than 29%
−0.20 ±0.22
better than 16%
Shot selection+0.27 ±0.13
better than 75%
−0.07 ±0.27
better than 38%
Execution−0.34 ±0.45
better than 41%
−0.86 ±0.93
better than 22%

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.

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.

Suzan Lamens serving

Deuce court

1st serveNowSuzan winsv JohannaMatchupOptimal
Wide38%67%72%72.5%±8.453% ▲
Body19%57%68%67.5%±11.94% ▼
T43%73%69%74.2%±8.243%

Optimal v Johanna Larsson: +0.6±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSuzan winsv JohannaMatchupOptimal
Wide42%71%65%70.5%±8.844% ▲
Body21%60%58%61.8%±11.66% ▼
T37%66%70%71.4%±9.150% ▲

Optimal v Johanna Larsson: +0.6±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.4 per 100 first serves in before the returner adjusts.

Johanna Larsson serving

Deuce court

1st serveNowJohanna winsv SuzanMatchupOptimal
Wide44%59%63%55.2%±9.759% ▲
Body17%54%57%53.9%±11.818%
T39%60%62%54.2%±10.623% ▼

Optimal v Suzan Lamens: +0.4±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +0.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJohanna winsv SuzanMatchupOptimal
Wide51%54%59%47.8%±9.463% ▲
Body17%53%52%49.1%±12.31% ▼
T32%60%62%56.6%±11.436% ▲

Optimal v Suzan Lamens: +0.5±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.7 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.

Suzan Lamens returning

1st serve to the forehand

ReturnNowTourOwnv JohannaValue
FH through the middle47%+4.2+2.0+0.7+6.9±2.9
FH down the line21%+1.5−0.1+0.1+1.5±4.3
FH crosscourt19%+5.3+0.1−1.6+3.8±4.2
FH slice through the middle9%−6.7−1.0+0.9−6.8±2.2
FH slice down the line3%−10.5−1.5±0.0−12.0±2.0

Lean FH through the middle: +3.7±2.0 per 100 returns v the current mix (435 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JohannaValue
BH through the middle48%+6.0+0.8+0.1+7.0±2.7
BH crosscourt32%+7.7+1.2+2.3+11.2±3.5
BH down the line11%+2.2−0.1±0.0+2.1±4.6
BH slice through the middle5%−6.2−1.8+0.5−7.6±1.9
BH slice crosscourt2%−4.2−0.6±0.0−4.8±1.6

Lean BH crosscourt: +4.6±2.7 per 100 returns v the current mix (425 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JohannaValue
FH through the middle47%−3.2+1.0+0.4−1.8±3.0
FH crosscourt27%+0.5+0.8−0.9+0.5±4.0
FH down the line20%−0.6−3.5±0.0−4.1±3.4
FH slice through the middle5%−15.2−0.2±0.0−15.4±1.1

Lean FH crosscourt: +2.8±3.3 per 100 returns v the current mix (99 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JohannaValue
BH through the middle44%−2.6−0.3+0.5−2.4±2.7
BH crosscourt34%+1.5−0.5−1.1−0.1±3.6
BH down the line9%−0.5−2.8+0.5−2.8±4.3
FH through the middle6%−2.7−0.2+0.4−2.5±2.3
FH inside-out4%+1.4−1.0±0.0+0.4±2.2

Lean BH crosscourt: +1.4±2.7 per 100 returns v the current mix (257 returns charted, inside the 90% margin)

Johanna Larsson returning

1st serve to the forehand

ReturnNowTourOwnv SuzanValue
FH through the middle41%+4.2−1.0−1.4+1.7±2.8
FH crosscourt29%+5.3+1.4−1.0+5.7±4.2
FH slice through the middle18%−6.7−0.6−1.0−8.3±2.4
FH down the line7%+1.5+1.8−2.4+0.9±3.6
FH slice crosscourt6%−6.6−1.0+1.0−6.6±2.2

Lean FH crosscourt: +5.2±3.3 per 100 returns v the current mix (101 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SuzanValue
BH through the middle55%+6.0+0.1+0.6+6.8±2.6
BH crosscourt27%+7.7−0.8−2.3+4.7±3.4
BH down the line11%+2.2−0.5+1.1+2.8±4.1
BH slice through the middle8%−6.2+0.4−1.3−7.2±2.1

Lean BH through the middle: +2.0±1.6 per 100 returns v the current mix (93 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv SuzanValue
BH through the middle29%−2.6+1.0−0.8−2.4±2.4
FH through the middle29%−2.7+0.5−1.0−3.2±2.2
BH crosscourt26%+1.5+0.5−0.4+1.7±3.2
FH inside-out17%+1.4+1.6−0.2+2.8±3.5

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.

Suzan Lamens

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+3.0±2.6+0.1+2.9
BH to their forehand · rally+3.0±4.1−1.0+4.0
BH to the middle · rally+3.0±2.0+1.3+1.7
FH to their forehand · serve +1+2.7±3.6+0.8+1.9
FH to the middle · return+2.7±2.6+1.8+1.0
BH to their backhand · return+1.9±3.1+1.1+0.7

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−0.5±2.5+0.3−0.8
FH to the middle · rally±0.0±2.1+0.6−0.6
FH to their backhand · serve +1+0.5±3.9−0.2+0.7
BH to the middle · return+0.9±2.2+0.7+0.3
FH to their backhand · rally+1.4±3.1+1.6−0.1

Johanna Larsson

Favour

ShotEdgeOwnTheirs
BH to the middle · return+2.0±2.4+1.4+0.6
BH to the middle · rally+0.4±1.9−0.3+0.8
FH to their forehand · rally±0.0±2.6−0.9+0.8
FH to their forehand · return−0.4±4.2+1.1−1.4
FH to their backhand · rally−0.7±3.4−0.7±0.0
FH to the middle · serve +1−1.0±2.5−0.1−0.9

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−3.2±2.5−1.4−1.7
BH to their backhand · rally−1.8±2.6−1.4−0.4
FH to the middle · rally−1.1±2.0−1.8+0.7
FH to the middle · serve +1−1.0±2.5−0.1−0.9
FH to their backhand · rally−0.7±3.4−0.7±0.0

Against Johanna Larsson-like opponents

Suzan Lamens vMatchesServe pts wonReturn pts won
All charted opponents–58.6%45.4%
Players most similar to Johanna Larsson4 60.2%39.8%

Similar by tactical fingerprint: Elina Svitolina, Arantxa Rus, Jil Teichmann, Emma Raducanu, Lucia Bronzetti, Ana Bogdan, Anna Lena Friedsam, Andrea Petkovic, Kiki Bertens. When two players have rarely met, their records against these lookalikes fill the gap.