RallyIQ

Game plan

Rafael Nadal v Lorenzo Musetti

Every number combines what Rafael Nadal does well with what Lorenzo Musetti 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 79%90%: 71%–86% · best of 5: 85%
Serve points won 65.0% / 58.5% Rafael / Lorenzo · tour 63.8%
Strengths only, no similarity priors 80%serve 66.1% / 59.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Rafael Nadal's record against Lorenzo Musetti's tactical lookalikes and in their charted head-to-heads (lookalikes: −1.5 on serve, +1.0 on return vs expectation (12599 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

CareerRafaelLorenzo
Direction choice+0.02 ±0.03
better than 62%
−0.02 ±0.04
better than 50%
Shot selection+0.38 ±0.05
better than 85%
−0.57 ±0.10
better than 9%
Execution+1.32 ±0.10
better than 99%
+0.48 ±0.22
better than 83%
Points left on the table2.66 ±0.04
lower than 43%
2.74 ±0.06
lower than 35%

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 +0.74, Lorenzo Musetti +0.58. 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 LorenzoMatchupOptimal
Wide31%75%72%73.6%±2.144% ▲
Body18%64%61%62.2%±4.45% ▼
T51%69%71%65.3%±2.451%

Optimal v Lorenzo Musetti: +0.6±0.5 per 100 first serves (faults included) over the current mix. Serving wide every time would read +6.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRafael winsv LorenzoMatchupOptimal
Wide54%71%68%66.1%±2.254%
Body18%67%63%66.3%±4.85% ▼
T28%75%71%74.4%±2.441% ▲

Optimal v Lorenzo Musetti: +0.4±0.5 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.9 per 100 first serves in before the returner adjusts.

Lorenzo Musetti serving

Deuce court

1st serveNowLorenzo winsv RafaelMatchupOptimal
Wide41%70%66%62.9%±2.438% ▼
Body9%64%58%58.6%±4.80% ▼
T49%72%74%71.4%±2.162% ▲

Optimal v Rafael Nadal: +0.7±0.4 per 100 first serves (faults included) over the current mix. Serving T every time would read +4.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLorenzo winsv RafaelMatchupOptimal
Wide55%69%71%67.7%±2.268% ▲
Body8%61%57%55.2%±5.20% ▼
T37%69%66%62.5%±2.732% ▼

Optimal v Rafael Nadal: +0.5±0.4 per 100 first serves (faults included) over the current mix. Serving wide every time would read +2.9 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 LorenzoValue
FH through the middle46%+4.3+0.4+0.8+5.4±1.1
FH crosscourt31%+5.5+2.4−2.1+5.8±2.0
FH down the line16%+1.7−0.8+0.4+1.3±2.6
FH slice through the middle3%−4.2+0.1+0.4−3.7±2.0
FH slice crosscourt2%−4.3+7.5+1.1+4.2±2.8
BH through the middle0%+6.6+0.4+0.5+7.4±2.0

Lean BH through the middle: +2.9±2.2 per 100 returns v the current mix (5711 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LorenzoValue
BH through the middle38%+6.4−0.2+0.5+6.7±0.9
BH crosscourt19%+8.8−1.2−0.7+6.9±1.9
BH slice through the middle17%−4.2+2.1−0.8−2.9±1.5
BH down the line15%+4.2+3.3−0.9+6.7±1.7
BH slice down the line7%−8.4+5.7−1.0−3.7±2.5
FH through the middle1%+7.7+2.5+0.8+11.0±2.0

Lean FH through the middle: +6.9±2.1 per 100 returns v the current mix (9039 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv LorenzoValue
FH crosscourt48%−0.2+0.7−0.5±0.0±2.4
FH through the middle33%−3.5−2.6−0.8−6.9±1.5
FH down the line17%−1.8+3.8+1.1+3.1±3.3
BH inside-out1%+0.9+0.3−0.7+0.5±2.9
FH slice through the middle1%−12.7−0.2−1.7−14.5±2.0

Lean FH down the line: +5.0±3.0 per 100 returns v the current mix (2037 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LorenzoValue
BH through the middle35%−2.9+2.0+0.2−0.7±1.0
BH crosscourt28%+1.0−1.0−0.8−0.8±2.0
BH down the line17%−0.2+1.8−0.7+0.9±2.2
FH through the middle9%−2.9+1.2−0.8−2.4±1.3
FH inside-in8%+0.6+1.5−0.5+1.6±2.7
FH inside-out3%+1.0−0.2+1.1+1.9±3.0

Lean FH inside-out: +2.3±3.0 per 100 returns v the current mix (5854 returns charted, inside the 90% margin)

Lorenzo Musetti returning

1st serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle40%+4.3−0.5−0.9+2.9±1.1
FH down the line24%+1.7−1.4+0.1+0.3±2.3
FH slice through the middle15%−4.2−0.4±0.0−4.6±1.6
FH crosscourt10%+5.5+2.3+1.7+9.6±2.6
FH slice down the line8%−4.3+0.2−3.6−7.7±2.9

Lean FH crosscourt: +8.8±2.4 per 100 returns v the current mix (2257 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RafaelValue
BH slice through the middle27%−4.2+1.4+1.9−1.0±1.1
BH through the middle25%+6.4+1.1+0.7+8.2±1.1
BH crosscourt20%+8.8+1.4+4.3+14.4±1.7
BH slice crosscourt11%+0.5−0.6+3.6+3.5±2.0
BH down the line9%+4.2±0.0−1.0+3.2±2.6

Lean BH crosscourt: +9.8±1.4 per 100 returns v the current mix (2587 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle47%−3.5+1.1−0.4−2.9±1.6
FH down the line25%−1.8−1.0+0.4−2.4±3.3
FH crosscourt23%−0.2−1.2−0.7−2.1±3.1
FH slice through the middle3%−12.7−0.7+0.1−13.3±2.3
FH slice down the line2%−9.4+1.2−1.2−9.4±2.2

Lean FH crosscourt: +0.9±2.6 per 100 returns v the current mix (600 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle33%−2.9+1.0+0.1−1.8±1.1
BH crosscourt27%+1.0+1.4−0.2+2.2±1.6
BH down the line14%−0.2−1.8−1.3−3.3±3.0
FH through the middle10%−2.9+1.2−0.4−2.1±1.5
FH inside-out6%+1.0−1.1+0.4+0.2±2.7

Lean BH crosscourt: +3.7±1.3 per 100 returns v the current mix (1827 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 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.

Rafael Nadal

Favour

ShotEdgeOwnTheirs
FH volley to their backhand · rally+10.8±6.2+8.8+2.1
BH volley to their forehand · rally+10.1±5.8+10.2−0.1
BH volley to the middle · rally+8.9±7.0+6.0+2.9
FH drop shot to their forehand · rally+8.8±7.0+8.1+0.6
FH volley to the middle · rally+7.5±7.6+8.0−0.5
BH drop shot to their backhand · rally+7.1±5.8+6.7+0.4

Avoid

ShotEdgeOwnTheirs
FH slice to their forehand · rally−10.2±4.9−8.5−1.8
BH volley to their backhand · serve +1−9.4±7.6−3.8−5.5
FH slice to their backhand · return +1−7.1±4.8+1.2−8.3
BH lob to their backhand · rally−5.5±5.8−1.7−3.7
BH drop shot to their forehand · rally−5.2±7.4+0.3−5.5

Lorenzo Musetti

Favour

ShotEdgeOwnTheirs
BH lob to the middle · rally+6.1±3.6+3.2+2.9
FH lob to their backhand · rally+5.2±6.4−0.4+5.6
BH volley to their forehand · serve +1+3.7±7.0−0.3+4.0
FH slice to their backhand · rally+3.6±3.7+1.6+2.0
FH volley to their backhand · rally+3.4±5.9−0.3+3.7
BH slice to their forehand · return +1+3.1±3.8−2.0+5.1

Avoid

ShotEdgeOwnTheirs
FH volley to their forehand · rally−13.2±5.7−7.5−5.7
BH volley to their backhand · rally−9.0±6.1−1.3−7.7
BH lob to their backhand · return +1−5.8±6.1+0.1−5.9
BH slice to their forehand · serve +1−4.4±5.2−4.4±0.0
Smash to their forehand · rally−2.9±5.1−1.7−1.1

Against Lorenzo Musetti-like opponents

Rafael Nadal vMatchesServe pts wonReturn pts won
All charted opponents–66.0%40.1%
Players most similar to Lorenzo Musetti75 62.2%38.7%

Similar by tactical fingerprint: Learner Tien, Novak Djokovic, Grigor Dimitrov, Marton Fucsovics, Pedro Martinez, Dusan Lajovic, Dominic Thiem, Robin Haase, Philipp Kohlschreiber, Guillermo Garcia Lopez. When two players have rarely met, their records against these lookalikes fill the gap.