RallyIQ

Game plan

Sebastian Baez v Rafael Nadal

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

Forecast

Sebastian Baez wins, best of 3 5%90%: 1%–20% · best of 5: 2%
Serve points won 55.8% / 69.1% Sebastian / Rafael · tour 65.7%
Strengths only, no similarity priors 5%serve 56.0% / 69.1%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Sebastian Baez's record against Rafael Nadal's tactical lookalikes and in their charted head-to-heads (lookalikes: −5.3 on serve, −0.9 on return vs expectation (149 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

CareerSebastianRafael
Direction choice−0.08 ±0.10
better than 34%
+0.02 ±0.03
better than 62%
Shot selection+0.02 ±0.14
better than 54%
+0.38 ±0.05
better than 85%
Execution−0.04 ±0.36
better than 66%
+1.32 ±0.10
better than 99%
Points left on the table2.58 ±0.13
lower than 51%
2.66 ±0.04
lower than 43%

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: Sebastian Baez +0.45, Rafael Nadal +1.91. 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.

Sebastian Baez serving

Deuce court

1st serveNowSebastian winsv RafaelMatchupOptimal
Wide46%66%66%58.4%±3.559% ▲
Body22%61%58%56.0%±5.19% ▼
T32%59%74%58.4%±4.232%

Optimal v Rafael Nadal: +0.3±0.6 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +0.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowSebastian winsv RafaelMatchupOptimal
Wide30%60%71%59.0%±4.243% ▲
Body19%62%57%56.4%±5.76% ▼
T51%64%66%57.6%±3.751%

Optimal v Rafael Nadal: +0.4±0.6 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.2 per 100 first serves in before the returner adjusts.

Rafael Nadal serving

Deuce court

1st serveNowRafael winsv SebastianMatchupOptimal
Wide31%75%68%69.7%±3.431%
Body18%64%61%61.6%±6.15% ▼
T51%69%73%67.4%±3.664% ▲

Optimal v Sebastian Baez: +0.3±0.6 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRafael winsv SebastianMatchupOptimal
Wide54%71%70%68.0%±3.354%
Body18%67%56%60.3%±6.75% ▼
T28%75%73%76.3%±3.541% ▲

Optimal v Sebastian Baez: +0.9±0.6 per 100 first serves (faults included) over the current mix. Serving T every time would read +7.4 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.

Sebastian Baez returning

1st serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle39%+4.3+0.6−0.9+4.0±1.7
FH down the line20%+1.7+2.2+0.1+4.0±3.2
FH slice through the middle17%−4.2−0.5±0.0−4.8±1.9
FH crosscourt13%+5.5+0.4+1.7+7.6±3.2
FH slice crosscourt6%−4.3+1.3+1.5−1.6±2.5

Lean FH crosscourt: +5.6±3.0 per 100 returns v the current mix (679 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle47%+6.4+0.4+0.7+7.5±1.4
BH crosscourt27%+8.8−1.3+4.3+11.7±2.2
BH down the line10%+4.2+2.6−1.0+5.8±3.3
BH slice through the middle7%−4.2−1.8+1.9−4.1±1.9
BH slice crosscourt5%+0.5−2.1+3.6+2.1±2.5

Lean BH crosscourt: +4.9±1.8 per 100 returns v the current mix (748 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle58%−3.5+2.8−0.4−1.1±1.9
FH crosscourt23%−0.2−0.4−0.7−1.3±3.4
FH down the line18%−1.8+0.7+0.4−0.7±3.7

Lean FH down the line: +0.4±3.3 per 100 returns v the current mix (226 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle32%−2.9+0.1+0.1−2.6±1.6
BH crosscourt23%+1.0−1.1−0.2−0.2±2.3
FH inside-out16%+1.0−2.1+0.4−0.7±2.8
FH through the middle13%−2.9−0.4−0.4−3.7±1.8
BH down the line9%−0.2−2.9−1.3−4.5±3.9

Lean BH crosscourt: +1.7±1.9 per 100 returns v the current mix (566 returns charted, inside the 90% margin)

Rafael Nadal returning

1st serve to the forehand

ReturnNowTourOwnv SebastianValue
FH through the middle46%+4.3+0.4+2.0+6.6±1.3
FH crosscourt31%+5.5+2.4+2.8+10.7±2.7
FH down the line16%+1.7−0.8+5.7+6.6±2.8
FH slice through the middle3%−4.2+0.1−0.6−4.7±2.1
FH slice crosscourt2%−4.3+7.5−0.1+3.0±2.4

Lean FH crosscourt: +3.3±2.0 per 100 returns v the current mix (5711 returns charted)

1st serve to the backhand

ReturnNowTourOwnv SebastianValue
BH through the middle38%+6.4−0.2+1.9+8.0±1.3
BH crosscourt19%+8.8−1.2+3.5+11.2±2.5
BH slice through the middle17%−4.2+2.1+0.4−1.7±1.8
BH down the line15%+4.2+3.3+2.2+9.8±2.5
BH slice down the line7%−8.4+5.7−0.9−3.6±2.6
FH inside-in0%+8.0+2.3+2.8+13.1±3.6

Lean FH inside-in: +7.0±3.7 per 100 returns v the current mix (9039 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv SebastianValue
FH crosscourt48%−0.2+0.7+0.7+1.1±3.2
FH through the middle33%−3.5−2.6−1.2−7.3±2.1
FH down the line17%−1.8+3.8±0.0+2.0±4.0
BH inside-out1%+0.9+0.3−0.7+0.5±3.5
FH slice through the middle1%−12.7−0.2−0.5−13.3±1.7

Lean FH down the line: +3.7±3.7 per 100 returns v the current mix (2037 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv SebastianValue
BH through the middle35%−2.9+2.0+0.1−0.8±1.5
BH crosscourt28%+1.0−1.0+0.8+0.8±2.5
BH down the line17%−0.2+1.8−0.7+0.9±3.1
FH through the middle9%−2.9+1.2−1.2−2.9±1.8
FH inside-in8%+0.6+1.5+0.7+2.8±3.5

Lean FH inside-in: +2.8±3.4 per 100 returns v the current mix (5854 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 grass. Each player's grass record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Sebastian Baez

Favour

ShotEdgeOwnTheirs
BH volley to their forehand · rally+10.9±6.2+0.4+10.5
BH to the middle · return+5.0±1.5+1.6+3.4
BH slice to the middle · return+4.6±2.3−1.2+5.9
BH drop shot to their forehand · rally+4.3±5.7+6.0−1.7
BH to their forehand · return +1+4.0±4.5+1.0+3.0
BH to their forehand · return+3.2±3.7+0.8+2.4

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−5.0±2.8−1.8−3.2
BH slice to their backhand · return +1−4.3±3.0+0.6−4.8
FH to their forehand · return−4.0±3.8−1.5−2.5
BH slice to their backhand · rally−3.2±2.6−0.4−2.8
FH to their forehand · serve +1−3.1±2.4−1.2−1.9

Rafael Nadal

Favour

ShotEdgeOwnTheirs
BH to their forehand · return +1+6.7±4.3+6.1+0.5
FH to their forehand · return+6.5±3.7+1.1+5.5
BH slice to their forehand · rally+5.3±3.3+5.3±0.0
FH to their backhand · return +1+4.9±3.0+3.7+1.2
FH to the middle · return+4.3±2.5+0.3+4.0
BH to their backhand · return+4.2±2.3+2.2+2.0

Avoid

ShotEdgeOwnTheirs
FH volley to their forehand · rally−2.6±6.2−1.0−1.6
BH volley to their backhand · rally−2.3±6.2+0.3−2.6
BH slice to their backhand · return +1−2.2±2.8−0.9−1.2
BH slice to the middle · rally−1.9±2.1+0.6−2.5
BH slice to their backhand · rally−1.8±2.0−1.0−0.8

Against Rafael Nadal-like opponents

Sebastian Baez vMatchesServe pts wonReturn pts won
All charted opponents–57.8%39.7%
Players most similar to Rafael Nadal1 51.4%37.7%

Similar by tactical fingerprint: Cameron Norrie, Lorenzo Musetti, Mariano Navone, Yoshihito Nishioka, Albert Ramos, Federico Delbonis, Fernando Verdasco, Juan Martin Del Potro, Nikolay Davydenko, Juan Carlos Ferrero. When two players have rarely met, their records against these lookalikes fill the gap.