RallyIQ

Game plan

Filippo Volandri v Miomir Kecmanovic

Every number combines what Filippo Volandri does well with what Miomir Kecmanovic allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Filippo Volandri wins, best of 3 67%90%: 31%–92% · best of 5: 71%
Serve points won 64.7% / 61.2% Filippo / Miomir · tour 65.7%
Strengths only, no similarity priors 67%serve 64.7% / 61.2%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerFilippoMiomir
Direction choice+0.30 ±0.18
better than 98%
−0.06 ±0.09
better than 43%
Shot selection−0.02 ±0.31
better than 50%
−0.28 ±0.10
better than 25%
Execution−1.02 ±0.90
better than 25%
+1.00 ±0.38
better than 95%

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.

Filippo Volandri serving

Deuce court

1st serveNowFilippo winsv MiomirMatchupOptimal
Wide27%64%76%67.5%±9.527%
Body34%58%58%52.8%±11.021% ▼
T39%71%80%76.7%±8.552% ▲

Optimal v Miomir Kecmanovic: +1.3±0.9 per 100 first serves (faults included) over the current mix. Serving T every time would read +10.7 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowFilippo winsv MiomirMatchupOptimal
Wide54%69%73%69.2%±8.354%
Body29%60%58%54.3%±11.816% ▼
T17%68%73%69.2%±11.730% ▲

Optimal v Miomir Kecmanovic: +0.7±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.3 per 100 first serves in before the returner adjusts.

Miomir Kecmanovic serving

Deuce court

1st serveNowMiomir winsv FilippoMatchupOptimal
Wide41%68%75%70.1%±9.442%
Body16%61%68%65.7%±12.92% ▼
T43%73%73%70.9%±10.156% ▲

Optimal v Filippo Volandri: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMiomir winsv FilippoMatchupOptimal
Wide45%71%70%68.2%±8.858% ▲
Body14%65%64%65.9%±13.91% ▼
T41%68%71%66.6%±10.441%

Optimal v Filippo Volandri: +0.6±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.0 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.

Filippo Volandri returning

1st serve to the forehand

ReturnNowTourOwnv MiomirValue
FH crosscourt40%+5.5−1.7+4.0+7.8±4.0
FH through the middle37%+4.3−0.9+1.1+4.4±2.4
FH slice through the middle15%−4.2+0.4+0.5−3.3±2.0
FH down the line8%+1.7−0.6+1.8+2.8±3.2

Lean FH crosscourt: +3.3±2.6 per 100 returns v the current mix (62 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MiomirValue
BH crosscourt36%+8.8+0.1+1.4+10.3±3.1
BH through the middle27%+6.4+0.3+2.4+9.2±2.2
BH slice through the middle19%−4.2−0.8+0.9−4.2±2.2
BH down the line12%+4.2+1.2−0.5+5.0±4.1
BH slice crosscourt6%+0.5−1.1−0.8−1.4±2.5

Lean BH crosscourt: +4.4±2.2 per 100 returns v the current mix (81 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv MiomirValue
BH crosscourt63%+1.0−0.5+0.4+0.9±2.9
BH through the middle37%−2.9−1.0+0.3−3.6±2.0

Lean BH crosscourt: +1.7±1.3 per 100 returns v the current mix (62 returns charted)

Miomir Kecmanovic returning

1st serve to the forehand

ReturnNowTourOwnv FilippoValue
FH through the middle51%+4.3+2.7+1.6+8.6±2.4
FH crosscourt21%+5.5+0.3−0.4+5.4±3.8
FH down the line13%+1.7+4.3−1.2+4.8±3.9
FH slice through the middle10%−4.2−0.1±0.0−4.3±1.6
FH slice down the line3%−4.3−0.3±0.0−4.6±2.1

Lean FH through the middle: +3.1±1.5 per 100 returns v the current mix (845 returns charted)

1st serve to the backhand

ReturnNowTourOwnv FilippoValue
BH crosscourt37%+8.8+3.2−0.7+11.3±3.1
BH through the middle35%+6.4+1.6−1.0+7.0±2.5
BH slice through the middle13%−4.2−0.2−0.9−5.3±2.4
BH slice crosscourt9%+0.5+0.5+1.1+2.1±2.9
BH down the line5%+4.2+0.7+1.1+5.9±4.4

Lean BH crosscourt: +5.0±2.2 per 100 returns v the current mix (721 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv FilippoValue
FH through the middle56%−3.5+0.6+0.3−2.6±2.8
FH crosscourt28%−0.2+2.8+2.1+4.7±4.4
FH down the line16%−1.8+1.1−0.3−1.0±4.5

Lean FH crosscourt: +5.0±3.6 per 100 returns v the current mix (172 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv FilippoValue
BH crosscourt46%+1.0+2.0−1.3+1.7±2.6
BH through the middle42%−2.9+1.8+0.5−0.6±2.1
BH down the line6%−0.2+0.5−1.4−1.1±4.6
FH through the middle3%−2.9+0.9+0.3−1.7±2.2
FH inside-in2%+0.6+2.6+2.1+5.3±3.9

Lean BH crosscourt: +1.4±1.7 per 100 returns v the current mix (550 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.

Filippo Volandri

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+7.3±3.9+0.9+6.4
FH to their backhand · serve +1+5.5±4.3−2.5+8.0
BH to their forehand · rally+5.0±5.0−0.2+5.2
FH to their forehand · serve +1+4.8±4.7−1.8+6.6
BH to their backhand · return+1.3±4.1−0.3+1.6
FH to their backhand · rally±0.0±3.9−1.0+1.0

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−2.4±3.2−1.2−1.2
FH to their backhand · rally±0.0±3.9−1.0+1.0
BH to their backhand · return+1.3±4.1−0.3+1.6
FH to their forehand · serve +1+4.8±4.7−1.8+6.6
BH to their forehand · rally+5.0±5.0−0.2+5.2

Miomir Kecmanovic

Favour

ShotEdgeOwnTheirs
FH to their forehand · rally+4.9±4.0+3.3+1.6
BH to their forehand · rally+4.1±5.0+4.6−0.5
BH to the middle · return+2.4±3.0+1.3+1.1
FH to their forehand · serve +1+1.4±4.7+4.1−2.7
FH to their backhand · rally+0.7±3.8+2.6−1.8
FH to their backhand · serve +1+0.3±4.5+1.0−0.7

Avoid

ShotEdgeOwnTheirs
BH to their backhand · rally−3.9±3.3−1.1−2.8
FH to their backhand · serve +1+0.3±4.5+1.0−0.7
FH to their backhand · rally+0.7±3.8+2.6−1.8
FH to their forehand · serve +1+1.4±4.7+4.1−2.7
BH to the middle · return+2.4±3.0+1.3+1.1

Against Miomir Kecmanovic-like opponents

Filippo Volandri vMatchesServe pts wonReturn pts won
All charted opponents–56.7%41.1%

Similar by tactical fingerprint: Alex De Minaur, Gael Monfils, Botic Van De Zandschulp, Novak Djokovic, Marcos Giron, Taylor Fritz, Nuno Borges, Arthur Cazaux, Emil Ruusuvuori, Ilya Ivashka. When two players have rarely met, their records against these lookalikes fill the gap.