RallyIQ

Game plan

Emilio Nava v Richard Gasquet

Every number combines what Emilio Nava does well with what Richard Gasquet allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Emilio Nava wins, best of 3 52%90%: 29%–75% · best of 5: 52%
Serve points won 66.0% / 65.6% Emilio / Richard · tour 63.8%
Strengths only, no similarity priors 52%serve 66.0% / 65.6%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Emilio Nava's record against Richard Gasquet'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

CareerEmilioRichard
Direction choice−0.13 ±0.10
better than 23%
+0.17 ±0.05
better than 91%
Shot selection+0.50 ±0.42
better than 93%
−0.47 ±0.11
better than 12%
Execution−1.45 ±1.41
better than 11%
+0.78 ±0.25
better than 91%

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.

Emilio Nava serving

Deuce court

1st serveNowEmilio winsv RichardMatchupOptimal
Wide40%75%74%75.7%±7.437% ▼
Body11%62%70%68.1%±11.10% ▼
T50%76%78%79.8%±6.363% ▲

Optimal v Richard Gasquet: +0.7±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowEmilio winsv RichardMatchupOptimal
Wide56%70%78%75.2%±6.669% ▲
Body15%63%63%63.1%±11.92% ▼
T29%76%71%75.2%±8.729%

Optimal v Richard Gasquet: +0.9±0.9 per 100 first serves (faults included) over the current mix. Serving T every time would read +1.8 per 100 first serves in before the returner adjusts.

Richard Gasquet serving

Deuce court

1st serveNowRichard winsv EmilioMatchupOptimal
Wide50%68%75%70.4%±7.542% ▼
Body5%62%65%63.4%±12.60% ▼
T45%75%78%77.6%±7.858% ▲

Optimal v Emilio Nava: +0.4±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRichard winsv EmilioMatchupOptimal
Wide52%71%68%66.5%±8.544% ▼
Body5%56%61%53.5%±13.70% ▼
T43%69%69%66.7%±8.056% ▲

Optimal v Emilio Nava: +0.9±0.7 per 100 first serves (faults included) over the current mix. Serving T every time would read +0.8 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.

Emilio Nava returning

1st serve to the forehand

ReturnNowTourOwnv RichardValue
FH through the middle55%+4.3−0.4+1.1+5.0±2.3
FH down the line31%+1.7−3.6+2.1+0.1±3.8
FH crosscourt15%+5.5−2.1+4.6+8.0±3.4

Lean FH crosscourt: +4.1±3.4 per 100 returns v the current mix (144 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RichardValue
BH through the middle50%+6.4−4.0+0.5+2.9±2.3
BH crosscourt29%+8.8−2.9+2.1+8.0±2.9
BH down the line21%+4.2−1.5+1.9+4.7±4.1

Lean BH crosscourt: +3.2±2.5 per 100 returns v the current mix (96 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv RichardValue
BH through the middle43%−2.9−1.3+1.0−3.2±1.9
BH crosscourt38%+1.0−2.1+2.0+1.0±2.5
BH down the line19%−0.2+0.3−0.1±0.0±3.6

Lean BH crosscourt: +2.0±1.9 per 100 returns v the current mix (58 returns charted)

Richard Gasquet returning

1st serve to the forehand

ReturnNowTourOwnv EmilioValue
FH through the middle49%+4.3−0.4−0.2+3.7±2.4
FH crosscourt28%+5.5−2.1−1.6+1.8±3.1
FH down the line17%+1.7+3.3+1.5+6.5±3.8
FH slice through the middle4%−4.2+2.2+0.1−1.9±2.0
FH slice down the line1%−4.3+2.2+0.1−2.0±2.3

Lean FH down the line: +3.1±3.5 per 100 returns v the current mix (1536 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv EmilioValue
BH slice through the middle30%−4.2+3.4+0.6−0.2±1.5
BH slice crosscourt22%+0.5+1.1−1.6+0.1±2.2
BH crosscourt18%+8.8−1.0−1.3+6.5±3.1
BH through the middle18%+6.4−2.2−2.2+2.0±2.5
BH slice down the line6%−8.4+2.3±0.0−6.1±2.4

Lean BH crosscourt: +5.3±2.7 per 100 returns v the current mix (1628 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv EmilioValue
FH through the middle42%−3.5+0.4−0.2−3.3±2.5
FH crosscourt37%−0.2−2.2+0.1−2.3±3.6
FH down the line17%−1.8+3.8−2.8−0.7±4.1
BH through the middle2%+0.1+0.6+0.9+1.5±1.8
FH slice through the middle1%−12.7+0.3±0.0−12.4±1.0

Lean FH down the line: +1.8±3.8 per 100 returns v the current mix (364 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv EmilioValue
BH crosscourt36%+1.0+0.4±0.0+1.5±2.7
BH through the middle27%−2.9±0.0+0.9−2.0±2.2
BH slice crosscourt15%−4.0−0.4±0.0−4.4±1.5
BH slice through the middle11%−11.3+0.7±0.0−10.6±1.5
BH down the line7%−0.2+2.2−1.5+0.5±4.4

Lean BH crosscourt: +3.4±1.9 per 100 returns v the current mix (1238 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.

Emilio Nava

Favour

ShotEdgeOwnTheirs
FH to their forehand · serve +1+4.9±4.6+5.0−0.1
FH to their backhand · rally+3.3±3.7+2.5+0.8
BH to the middle · rally+2.4±2.4+1.2+1.2
FH to the middle · return+2.2±2.9−0.1+2.3
BH to their backhand · rally−0.5±2.7−0.9+0.4
BH to their backhand · serve +1−1.0±4.0−0.4−0.5

Avoid

ShotEdgeOwnTheirs
BH to their backhand · return−3.6±3.9−5.4+1.8
FH to the middle · rally−3.4±2.9−3.6+0.2
BH to the middle · return−3.1±2.7−3.4+0.3
FH to their forehand · rally−2.5±3.5−4.2+1.7
BH to their backhand · serve +1−1.0±4.0−0.4−0.5

Richard Gasquet

Favour

ShotEdgeOwnTheirs
BH to their backhand · rally+3.3±2.7+2.5+0.7
BH to the middle · rally+1.6±2.5+1.2+0.4
FH to the middle · return+1.6±3.3+1.1+0.5
BH to their backhand · return+0.8±3.6+0.5+0.3
FH to the middle · rally+0.4±2.7+0.8−0.4
FH to their forehand · rally−0.5±3.7−0.4−0.1

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−4.0±4.4+0.8−4.8
FH to their backhand · rally−3.6±3.8+0.9−4.5
FH to their forehand · serve +1−3.4±4.8−2.7−0.6
BH to the middle · return−1.4±2.8−1.1−0.4
FH to their forehand · rally−0.5±3.7−0.4−0.1

Against Richard Gasquet-like opponents

Emilio Nava vMatchesServe pts wonReturn pts won
All charted opponents–66.3%33.2%

Similar by tactical fingerprint: Learner Tien, Daniil Medvedev, Novak Djokovic, Karen Khachanov, Nishesh Basavareddy, Benjamin Bonzi, Andy Murray, Marcos Baghdatis, David Nalbandian, Ivan Ljubicic. When two players have rarely met, their records against these lookalikes fill the gap.