RallyIQ

Game plan

Pavel Kotov v Rafael Nadal

Every number combines what Pavel Kotov 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

Pavel Kotov wins, best of 3 3%90%: 1%–11% · best of 5: 1%
Serve points won 59.5% / 74.8% Pavel / Rafael · tour 65.7%
Strengths only, no similarity priors 3%serve 59.5% / 74.8%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Pavel Kotov's record against Rafael Nadal's tactical lookalikes and in their charted head-to-heads. 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

CareerPavelRafael
Direction choice−0.11 ±0.16
better than 28%
+0.02 ±0.03
better than 62%
Shot selection−0.07 ±0.22
better than 44%
+0.38 ±0.05
better than 85%
Execution−0.81 ±1.28
better than 32%
+1.32 ±0.10
better than 99%

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.

Pavel Kotov serving

Deuce court

1st serveNowPavel winsv RafaelMatchupOptimal
Wide45%66%66%58.9%±7.945%
Body17%65%58%59.5%±10.54% ▼
T38%74%74%73.6%±7.751% ▲

Optimal v Rafael Nadal: +0.7±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +9.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowPavel winsv RafaelMatchupOptimal
Wide59%62%71%60.8%±8.072% ▲
Body10%58%57%52.4%±12.50% ▼
T32%67%66%60.8%±9.828% ▼

Optimal v Rafael Nadal: +0.4±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +0.8 per 100 first serves in before the returner adjusts.

Rafael Nadal serving

Deuce court

1st serveNowRafael winsv PavelMatchupOptimal
Wide31%75%81%82.6%±6.244% ▲
Body18%64%67%68.2%±10.65% ▼
T51%69%79%73.8%±8.251%

Optimal v Pavel Kotov: +1.1±0.8 per 100 first serves (faults included) over the current mix. Serving wide every time would read +7.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRafael winsv PavelMatchupOptimal
Wide54%71%81%80.2%±6.867% ▲
Body18%67%72%75.4%±10.05% ▼
T28%75%68%71.8%±7.828%

Optimal v Pavel Kotov: +0.6±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.2 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.

Pavel Kotov returning

1st serve to the forehand

ReturnNowTourOwnv RafaelValue
FH through the middle34%+4.3+0.3−0.9+3.7±2.2
FH crosscourt22%+5.5−5.5+1.7+1.7±3.1
FH slice through the middle20%−4.2−0.7±0.0−4.9±1.9
FH down the line9%+1.7−3.8+0.1−2.0±2.7
FH slice down the line9%−4.3−0.7−3.6−8.6±2.7

Lean FH through the middle: +4.2±1.7 per 100 returns v the current mix (98 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle40%+6.4−1.0+0.7+6.1±2.1
BH crosscourt35%+8.8−1.6+4.3+11.5±2.6
BH down the line10%+4.2−1.4−1.0+1.8±2.5
BH slice through the middle9%−4.2−0.9+1.9−3.2±1.4
BH slice down the line6%−8.4−2.0−3.0−13.4±2.1

Lean BH crosscourt: +5.9±1.9 per 100 returns v the current mix (94 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv RafaelValue
BH through the middle50%−2.9±0.0+0.1−2.7±1.8
BH crosscourt37%+1.0+0.2−0.2+1.0±2.2
BH down the line13%−0.2−0.3−1.3−1.8±2.7

Lean BH crosscourt: +2.3±1.7 per 100 returns v the current mix (46 returns charted)

Rafael Nadal returning

1st serve to the forehand

ReturnNowTourOwnv PavelValue
FH through the middle46%+4.3+0.4−0.6+4.0±2.3
FH crosscourt31%+5.5+2.4+0.4+8.3±3.2
FH down the line16%+1.7−0.8−3.2−2.3±3.4
FH slice through the middle3%−4.2+0.1+0.3−3.8±1.9
FH slice crosscourt2%−4.3+7.5±0.0+3.1±1.9
BH inside-out0%+6.3+1.4+0.7+8.5±3.9

Lean BH inside-out: +4.4±4.2 per 100 returns v the current mix (5711 returns charted)

1st serve to the backhand

ReturnNowTourOwnv PavelValue
BH through the middle38%+6.4−0.2−0.1+6.1±2.1
BH crosscourt19%+8.8−1.2+1.6+9.2±2.4
BH slice through the middle17%−4.2+2.1−1.2−3.3±1.7
BH down the line15%+4.2+3.3+0.7+8.3±3.5
BH slice down the line7%−8.4+5.7−0.5−3.2±2.3
FH inside-in0%+8.0+2.3+0.4+10.7±4.0

Lean FH inside-in: +6.3±4.1 per 100 returns v the current mix (9039 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv PavelValue
FH crosscourt48%−0.2+0.7+1.3+1.7±3.2
FH through the middle33%−3.5−2.6−0.8−6.9±2.3
FH down the line17%−1.8+3.8+3.5+5.6±3.9
BH inside-out1%+0.9+0.3+0.2+1.4±4.0
FH slice through the middle1%−12.7−0.2±0.0−12.8±1.3

Lean FH down the line: +6.2±3.7 per 100 returns v the current mix (2037 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv PavelValue
BH through the middle35%−2.9+2.0+0.1−0.8±1.7
BH crosscourt28%+1.0−1.0±0.0±0.0±0.8
BH down the line17%−0.2+1.8+0.2+1.8±3.7
FH through the middle9%−2.9+1.2−0.8−2.5±2.0
FH inside-in8%+0.6+1.5+1.3+3.4±3.4
FH inside-out3%+1.0−0.2+3.5+4.3±3.4

Lean FH inside-out: +4.2±3.4 per 100 returns v the current mix (5854 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 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.

Pavel Kotov

Favour

ShotEdgeOwnTheirs
BH to the middle · rally+3.2±2.0+2.6+0.6
BH to the middle · return+2.2±2.2−1.2+3.4
BH to their backhand · return+1.5±3.2−1.2+2.7
BH to their forehand · rally+0.7±3.5−0.3+1.0
FH to their backhand · rally±0.0±2.6−1.3+1.3
FH to the middle · return−0.1±2.4+0.2−0.3

Avoid

ShotEdgeOwnTheirs
FH to their forehand · rally−3.4±2.9−0.9−2.5
FH to their forehand · serve +1−2.5±3.5−0.6−1.9
BH to their backhand · rally−2.4±2.3+0.8−3.2
BH to their backhand · serve +1−1.8±3.3−0.6−1.1
FH to the middle · rally−1.2±2.3+0.1−1.2

Rafael Nadal

Favour

ShotEdgeOwnTheirs
FH to their backhand · serve +1+5.4±3.2+1.8+3.6
FH to their backhand · rally+4.3±2.5+2.3+1.9
FH to the middle · rally+3.9±2.4+2.1+1.9
BH to their backhand · return+3.5±3.1+2.2+1.3
BH to their backhand · rally+2.6±2.4+1.6+1.0
BH to the middle · return+2.3±2.3+1.1+1.1

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−1.7±2.4+0.3−2.0
FH to their forehand · rally−0.7±2.9±0.0−0.7
FH to their forehand · serve +1+1.1±3.4±0.0+1.1
BH to the middle · rally+2.2±2.1+1.8+0.4
BH to the middle · return+2.3±2.3+1.1+1.1

Against Rafael Nadal-like opponents

Pavel Kotov vMatchesServe pts wonReturn pts won
All charted opponents–58.2%28.2%

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.