RallyIQ

Game plan

Rafael Nadal v Jiri Lehecka

Every number combines what Rafael Nadal does well with what Jiri Lehecka allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Rafael Nadal wins, best of 3 99%90%: 97%–100% · best of 5: 100%
Serve points won 69.8% / 51.1% Rafael / Jiri · tour 61.3%
Strengths only, no similarity priors 99%serve 69.8% / 51.0%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Rafael Nadal's record against Jiri Lehecka's tactical lookalikes and in their charted head-to-heads (lookalikes: ±0.0 on serve, −1.5 on return vs expectation (315 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

CareerRafaelJiri
Direction choice+0.02 ±0.03
better than 62%
−0.11 ±0.11
better than 30%
Shot selection+0.38 ±0.05
better than 85%
−0.02 ±0.14
better than 49%
Execution+1.32 ±0.10
better than 99%
−0.37 ±0.43
better than 50%
Points left on the table2.66 ±0.04
lower than 43%
2.73 ±0.18
lower than 37%

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: Rafael Nadal +1.85, Jiri Lehecka −1.09. 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.

Rafael Nadal serving

Deuce court

1st serveNowRafael winsv JiriMatchupOptimal
Wide31%75%77%78.8%±2.844% ▲
Body18%64%60%60.6%±7.25% ▼
T51%69%76%70.4%±3.351%

Optimal v Jiri Lehecka: +1.3±0.6 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.

Ad court

1st serveNowRafael winsv JiriMatchupOptimal
Wide54%71%77%76.0%±3.054%
Body18%67%67%70.5%±7.45% ▼
T28%75%77%79.6%±3.041% ▲

Optimal v Jiri Lehecka: +0.7±0.6 per 100 first serves (faults included) over the current mix. Serving T every time would read +3.5 per 100 first serves in before the returner adjusts.

Jiri Lehecka serving

Deuce court

1st serveNowJiri winsv RafaelMatchupOptimal
Wide44%72%66%65.3%±3.342% ▼
Body12%60%58%55.1%±6.10% ▼
T45%76%74%74.8%±3.158% ▲

Optimal v Rafael Nadal: +0.7±0.6 per 100 first serves (faults included) over the current mix. Serving T every time would read +6.4 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJiri winsv RafaelMatchupOptimal
Wide54%73%71%71.6%±3.167% ▲
Body9%65%57%59.6%±6.90% ▼
T37%72%66%66.5%±3.833% ▼

Optimal v Rafael Nadal: +0.4±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.0 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.

Rafael Nadal returning

1st serve to the forehand

ReturnNowTourOwnv JiriValue
FH through the middle46%+4.3+0.4+1.8+6.4±1.5
FH crosscourt31%+5.5+2.4+1.1+9.1±2.9
FH down the line16%+1.7−0.8+4.2+5.1±3.1
FH slice through the middle3%−4.2+0.1+0.5−3.6±2.0
FH slice crosscourt2%−4.3+7.5+1.4+4.6±2.8
BH inside-out0%+6.3+1.4+3.7+11.4±3.4

Lean BH inside-out: +4.8±3.7 per 100 returns v the current mix (5711 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JiriValue
BH through the middle38%+6.4−0.2+4.1+10.3±1.4
BH crosscourt19%+8.8−1.2+1.9+9.5±2.6
BH slice through the middle17%−4.2+2.1+1.0−1.2±1.7
BH down the line15%+4.2+3.3+3.7+11.3±2.9
BH slice down the line7%−8.4+5.7+0.3−2.4±2.8
FH through the middle1%+7.7+2.5+1.8+12.0±2.2

Lean FH through the middle: +4.9±2.4 per 100 returns v the current mix (9039 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JiriValue
FH crosscourt48%−0.2+0.7−1.2−0.7±3.2
FH through the middle33%−3.5−2.6+1.1−5.0±1.7
FH down the line17%−1.8+3.8−0.9+1.2±3.7
BH inside-out1%+0.9+0.3+1.6+2.8±3.5
FH slice through the middle1%−12.7−0.2+0.4−12.4±1.9

Lean FH down the line: +3.1±3.5 per 100 returns v the current mix (2037 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JiriValue
BH through the middle35%−2.9+2.0+2.3+1.4±1.3
BH crosscourt28%+1.0−1.0−2.8−2.8±2.4
BH down the line17%−0.2+1.8+1.6+3.2±3.0
FH through the middle9%−2.9+1.2+1.1−0.6±1.5
FH inside-in8%+0.6+1.5−1.2+0.9±3.4

Lean BH down the line: +3.0±2.7 per 100 returns v the current mix (5854 returns charted)

Jiri Lehecka returning

1st serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle36%+4.3−0.8−0.9+2.6±1.7
FH crosscourt20%+5.5+1.9+1.7+9.2±2.9
FH slice through the middle19%−4.2−1.2±0.0−5.5±1.9
FH slice crosscourt10%−4.3−0.3+1.5−3.1±2.5
FH down the line10%+1.7−0.9+0.1+0.8±3.5

Lean FH crosscourt: +8.2±2.5 per 100 returns v the current mix (705 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle30%+6.4+1.8+0.7+8.9±1.6
BH slice through the middle24%−4.2−0.9+1.9−3.2±1.6
BH crosscourt22%+8.8+1.6+4.3+14.7±2.3
BH slice crosscourt14%+0.5−1.6+3.6+2.5±2.4
BH down the line5%+4.2+2.0−1.0+5.2±3.4

Lean BH crosscourt: +9.4±1.9 per 100 returns v the current mix (786 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle43%−3.5−0.8−0.4−4.7±2.1
FH crosscourt30%−0.2+1.8−0.7+0.9±3.4
FH down the line20%−1.8−1.7+0.4−3.0±3.7
FH slice through the middle5%−12.7+0.6+0.1−12.0±2.1
FH slice down the line3%−9.4+0.3−1.2−10.3±2.0

Lean FH crosscourt: +4.1±2.6 per 100 returns v the current mix (210 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle44%−2.9−0.5+0.1−3.2±1.4
BH crosscourt30%+1.0+1.1−0.2+1.9±2.1
FH through the middle9%−2.9+1.6−0.4−1.7±1.8
BH down the line9%−0.2+5.3−1.3+3.8±3.9
FH inside-in3%+0.6−1.7−0.7−1.9±3.1

Lean BH down the line: +4.9±3.6 per 100 returns v the current mix (626 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.

Rafael Nadal

Favour

ShotEdgeOwnTheirs
FH to their backhand · return+7.7±3.4+3.1+4.5
BH to their forehand · return +1+7.6±4.7+4.0+3.7
BH to the middle · return+6.0±1.8+1.9+4.1
FH to their forehand · return +1+5.4±3.8+2.0+3.3
BH slice to their forehand · rally+4.5±3.9+5.4−0.9
BH to their backhand · serve +1+4.2±3.2+2.0+2.2

Avoid

ShotEdgeOwnTheirs
FH slice to the middle · rally−2.9±3.1−0.8−2.1
BH slice to their backhand · rally−2.1±2.6−1.0−1.1
BH slice to their backhand · return−2.0±2.9−1.9−0.1
FH to the middle · return +1−0.9±2.5−0.8−0.1
BH slice to their backhand · return +1−0.9±2.5−1.2+0.3

Jiri Lehecka

Favour

ShotEdgeOwnTheirs
BH to their forehand · serve +1+10.5±4.7+9.1+1.4
BH to their forehand · return+6.4±4.1+4.2+2.2
FH to their forehand · return+4.1±4.2+2.6+1.6
BH to their backhand · return+3.9±2.5+3.1+0.8
FH volley to their backhand · rally+3.3±5.3+1.0+2.3
BH volley to their forehand · rally+3.3±5.4−2.2+5.4

Avoid

ShotEdgeOwnTheirs
FH volley to their forehand · rally−15.6±6.5−7.2−8.4
BH slice to their backhand · return +1−8.1±3.2−2.7−5.5
FH slice to their forehand · rally−8.1±5.2−0.7−7.4
BH to their backhand · return +1−6.7±2.9−4.1−2.6
BH slice to their backhand · return−6.5±3.4−1.0−5.5

Against Jiri Lehecka-like opponents

Rafael Nadal vMatchesServe pts wonReturn pts won
All charted opponents–66.0%40.1%
Players most similar to Jiri Lehecka2 67.1%43.0%

Similar by tactical fingerprint: Ben Shelton, Arthur Rinderknech, Zhizhen Zhang, Alexander Shevchenko, Zizou Bergs, Jan Lennard Struff, Luca Nardi, Gabriel Diallo, Fabio Fognini, Gregoire Barrere. When two players have rarely met, their records against these lookalikes fill the gap.