RallyIQ

Game plan

Emilio Nava v Jaume Munar

Every number combines what Emilio Nava does well with what Jaume Munar 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 51%90%: 21%–80% · best of 5: 51%
Serve points won 63.6% / 63.4% Emilio / Jaume · tour 63.4%
Strengths only, no similarity priors 51%serve 63.6% / 63.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerEmilioJaume
Direction choice−0.13 ±0.10
better than 23%
−0.01 ±0.08
better than 53%
Shot selection+0.50 ±0.42
better than 93%
−0.31 ±0.21
better than 22%
Execution−1.45 ±1.41
better than 11%
+0.60 ±0.36
better than 86%

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 JaumeMatchupOptimal
Wide40%75%72%74.0%±8.047% ▲
Body11%62%54%52.5%±13.60% ▼
T50%76%71%73.0%±8.153% ▲

Optimal v Jaume Munar: +0.8±0.7 per 100 first serves (faults included) over the current mix. Serving wide every time would read +2.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowEmilio winsv JaumeMatchupOptimal
Wide56%70%70%66.5%±8.156%
Body15%63%63%63.4%±12.82% ▼
T29%76%69%74.2%±9.342% ▲

Optimal v Jaume Munar: +0.7±1.0 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.

Jaume Munar serving

Deuce court

1st serveNowJaume winsv EmilioMatchupOptimal
Wide55%68%75%70.2%±7.851% ▼
Body10%65%65%66.8%±12.50% ▼
T35%73%78%76.0%±8.749% ▲

Optimal v Emilio Nava: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJaume winsv EmilioMatchupOptimal
Wide51%68%68%62.8%±9.351%
Body14%64%61%62.3%±12.91% ▼
T35%66%69%62.9%±9.048% ▲

Optimal v Emilio Nava: +0.3±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +0.1 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 JaumeValue
FH through the middle55%+4.3−0.4+1.2+5.1±2.5
FH down the line31%+1.7−3.6+0.3−1.7±4.2
FH crosscourt15%+5.5−2.1+2.3+5.8±3.8

Lean FH crosscourt: +2.6±3.8 per 100 returns v the current mix (144 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv JaumeValue
BH through the middle50%+6.4−4.0−0.8+1.7±2.5
BH crosscourt29%+8.8−2.9+0.3+6.2±3.2
BH down the line21%+4.2−1.5+1.6+4.3±4.3

Lean BH crosscourt: +2.7±2.7 per 100 returns v the current mix (96 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv JaumeValue
BH through the middle43%−2.9−1.3−1.6−5.8±2.3
BH crosscourt38%+1.0−2.1−1.1−2.2±2.9
BH down the line19%−0.2+0.3+3.3+3.3±4.4

Lean BH crosscourt: +0.5±2.2 per 100 returns v the current mix (58 returns charted, inside the 90% margin)

Jaume Munar returning

1st serve to the forehand

ReturnNowTourOwnv EmilioValue
FH through the middle44%+4.3−0.4−0.2+3.6±2.7
FH slice through the middle22%−4.2+0.7+0.1−3.4±1.8
FH down the line13%+1.7−0.2+1.5+2.9±4.3
FH crosscourt11%+5.5+2.3−1.6+6.2±3.9
FH slice down the line7%−4.3+1.8+0.1−2.3±2.6

Lean FH crosscourt: +4.6±3.7 per 100 returns v the current mix (701 returns charted)

1st serve to the backhand

ReturnNowTourOwnv EmilioValue
BH through the middle42%+6.4+2.3−2.2+6.5±2.4
BH crosscourt27%+8.8+1.2−1.3+8.7±3.2
BH slice through the middle13%−4.2−0.1+0.6−3.6±2.0
BH down the line10%+4.2+1.9−0.5+5.6±4.0
BH slice crosscourt6%+0.5−1.6−1.6−2.6±2.7

Lean BH crosscourt: +3.8±2.6 per 100 returns v the current mix (760 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv EmilioValue
FH through the middle44%−3.5+2.5−0.2−1.2±2.7
FH crosscourt25%−0.2+0.4+0.1+0.2±3.9
FH down the line21%−1.8+0.8−2.8−3.7±4.0
FH slice through the middle6%−12.7+0.8±0.0−11.9±1.3
FH slice down the line4%−9.4+0.6±0.0−8.8±1.4

Lean FH crosscourt: +2.5±3.2 per 100 returns v the current mix (170 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv EmilioValue
BH through the middle47%−2.9−0.7+0.9−2.7±2.3
BH crosscourt29%+1.0+1.3±0.0+2.3±3.1
BH down the line13%−0.2+2.2−1.5+0.4±4.5
FH through the middle6%−2.9−1.1−0.2−4.2±2.2
FH inside-in3%+0.6−0.1+0.1+0.5±3.5

Lean BH crosscourt: +3.2±2.6 per 100 returns v the current mix (456 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.

Emilio Nava

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+2.7±2.8+2.0+0.7
FH to their forehand · serve +1+2.3±3.4+2.5−0.2
FH to the middle · return+0.9±2.2−0.1+1.0
BH to the middle · rally+0.6±1.9+0.8−0.3
BH to their backhand · serve +1−0.5±3.1−1.2+0.8
BH to their backhand · rally−0.5±2.2−0.7+0.2

Avoid

ShotEdgeOwnTheirs
BH to their backhand · return−3.6±2.9−3.9+0.3
BH to the middle · return−2.4±2.2−2.2−0.2
FH to their forehand · rally−1.5±2.8−3.7+2.1
FH to the middle · rally−1.0±2.1−2.2+1.2
BH to their backhand · rally−0.5±2.2−0.7+0.2

Jaume Munar

Favour

ShotEdgeOwnTheirs
BH to their backhand · rally+3.0±2.2+2.1+0.9
BH to their backhand · return+1.8±2.8+2.1−0.3
BH to the middle · rally+1.8±1.9+1.7+0.1
FH to their forehand · serve +1+1.2±3.6+1.1+0.1
FH to the middle · rally+1.2±2.1+1.3−0.1
FH to the middle · return+0.8±2.5+0.6+0.2

Avoid

ShotEdgeOwnTheirs
FH to their backhand · serve +1−5.2±3.2−1.8−3.4
FH to their backhand · rally−2.8±2.8+0.9−3.7
FH to their forehand · rally+0.1±2.9−0.2+0.3
BH to the middle · return+0.2±2.1+0.9−0.7
FH to the middle · return+0.8±2.5+0.6+0.2

Against Jaume Munar-like opponents

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

Similar by tactical fingerprint: Brandon Nakashima, Novak Djokovic, Jenson Brooksby, Karen Khachanov, Pablo Carreno Busta, Andy Murray, Bernabe Zapata Miralles, Mikhail Kukushkin, Carlos Berlocq, Guillermo Coria. When two players have rarely met, their records against these lookalikes fill the gap.