RallyIQ

Game plan

Brad Gilbert v Mario Ancic

Every number combines what Brad Gilbert does well with what Mario Ancic allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Brad Gilbert wins, best of 3 62%90%: 25%–90% · best of 5: 65%
Serve points won 63.0% / 60.6% Brad / Mario · tour 61.3%
Strengths only, no similarity priors 63%serve 63.1% / 60.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Brad Gilbert's record against Mario Ancic's tactical lookalikes and in their charted head-to-heads (lookalikes: −2.1 on serve, −7.3 on return vs expectation (126 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

CareerBradMario
Direction choice+0.13 ±0.18
better than 86%
−0.19 ±0.20
better than 15%
Shot selection+0.20 ±0.28
better than 72%
+0.43 ±0.22
better than 88%
Execution−0.12 ±0.50
better than 63%
−1.93 ±0.54
better than 4%
Points left on the table3.65 ±0.41
lower than 6%
3.42 ±0.55
lower than 9%

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.

Brad Gilbert serving

Deuce court

1st serveNowBrad winsv MarioMatchupOptimal
Wide52%66%82%76.4%±8.465% ▲
Body7%65%64%65.6%±14.80% ▼
T41%69%82%76.9%±9.035% ▼

Optimal v Mario Ancic: +0.7±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +1.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowBrad winsv MarioMatchupOptimal
Wide47%66%78%71.6%±9.560% ▲
Body7%53%63%52.4%±17.50% ▼
T46%65%72%65.5%±10.540% ▼

Optimal v Mario Ancic: +0.4±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.1 per 100 first serves in before the returner adjusts.

Mario Ancic serving

Deuce court

1st serveNowMario winsv BradMatchupOptimal
Wide47%75%71%73.5%±9.143% ▼
Body10%71%75%80.8%±10.30% ▼
T44%70%76%71.1%±9.257% ▲

Optimal v Brad Gilbert: +0.2±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +7.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMario winsv BradMatchupOptimal
Wide44%69%72%68.6%±9.544%
Body13%64%55%56.9%±15.20% ▼
T43%74%73%75.4%±9.856% ▲

Optimal v Brad Gilbert: +0.7±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +5.3 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.

Brad Gilbert returning

1st serve to the forehand

ReturnNowTourOwnv MarioValue
FH through the middle41%+4.3+0.3−2.0+2.6±3.1
FH crosscourt39%+5.5+2.6−2.9+5.3±4.3
FH down the line20%+1.7−1.4−1.1−0.9±4.3

Lean FH crosscourt: +2.3±3.1 per 100 returns v the current mix (90 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv MarioValue
BH through the middle31%+6.4−1.0−2.4+3.0±2.9
BH crosscourt19%+8.8+0.8−3.8+5.8±3.6
BH slice crosscourt17%+0.5+2.0−1.1+1.4±2.9
BH slice through the middle16%−4.2−1.5+0.2−5.5±2.4
BH down the line12%+4.2−0.2+1.9+5.8±4.4

Lean BH crosscourt: +4.1±3.2 per 100 returns v the current mix (193 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv MarioValue
BH through the middle30%−2.9+0.3−0.6−3.2±2.5
BH slice through the middle17%−11.3+0.3+0.2−10.8±2.1
BH slice crosscourt16%−4.0+0.1+0.8−3.1±2.3
FH through the middle11%−2.9−0.9+0.5−3.3±2.0
BH crosscourt9%+1.0−1.0+0.2+0.2±2.8

Lean BH through the middle: +0.2±1.9 per 100 returns v the current mix (64 returns charted, inside the 90% margin)

Mario Ancic returning

1st serve to the forehand

ReturnNowTourOwnv BradValue
FH through the middle44%+4.3+3.0+2.6+9.8±3.0
FH down the line37%+1.7−1.0+0.8+1.5±4.5
FH crosscourt15%+5.5−2.8−2.5+0.3±4.1
FH slice down the line4%−4.3+0.5±0.0−3.8±1.3

Lean FH through the middle: +5.0±2.4 per 100 returns v the current mix (131 returns charted)

1st serve to the backhand

ReturnNowTourOwnv BradValue
BH crosscourt33%+8.8+2.7+3.4+14.9±3.5
BH through the middle28%+6.4−1.5−0.3+4.6±2.9
BH down the line19%+4.2−3.2−2.6−1.6±4.4
BH slice through the middle10%−4.2−0.9+2.6−2.6±2.3
BH slice crosscourt6%+0.5−2.0+0.9−0.6±2.5

Lean BH crosscourt: +9.6±2.6 per 100 returns v the current mix (156 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv BradValue
FH through the middle52%−3.5+1.2+2.5+0.2±2.9
FH down the line32%−1.8−2.4+1.6−2.6±4.5
FH crosscourt17%−0.2−0.6+1.0+0.2±3.9

Lean FH through the middle: +0.9±2.1 per 100 returns v the current mix (60 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv BradValue
BH through the middle50%−2.9−2.1+0.1−4.9±2.3
BH crosscourt42%+1.0−1.7+3.3+2.6±3.2
BH down the line8%−0.2±0.0+1.1+0.9±3.2

Lean BH crosscourt: +3.8±2.2 per 100 returns v the current mix (106 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 clay. Each player's clay record is shrunk toward their all-surface one, so a thin sample on it moves the numbers only a little.

Brad Gilbert

Favour

ShotEdgeOwnTheirs
BH slice to their backhand · rally+5.3±3.3+2.7+2.6
FH to their forehand · rally+4.1±4.3+2.8+1.3
FH to their backhand · serve +1+2.5±4.8−0.8+3.3
FH to their backhand · rally+2.0±4.2−0.4+2.4
BH to the middle · rally+1.5±3.0−0.3+1.8
BH to their backhand · rally−0.1±3.5+0.6−0.7

Avoid

ShotEdgeOwnTheirs
BH to the middle · return−3.7±3.2±0.0−3.7
FH to the middle · return−0.8±3.5−0.5−0.4
BH to their backhand · return−0.1±4.0+2.5−2.6
BH to their backhand · rally−0.1±3.5+0.6−0.7
BH to the middle · rally+1.5±3.0−0.3+1.8

Mario Ancic

Favour

ShotEdgeOwnTheirs
FH to the middle · return+4.0±3.3+0.6+3.4
FH to their backhand · rally+4.0±4.0+0.7+3.3
BH to their backhand · rally−0.9±3.4−3.8+2.8
BH to the middle · return−1.4±3.2−2.8+1.3
FH to their forehand · rally−2.5±4.4−2.8+0.2
FH to their backhand · return−3.4±4.7−5.0+1.6

Avoid

ShotEdgeOwnTheirs
FH to their backhand · return−3.4±4.7−5.0+1.6
FH to their forehand · rally−2.5±4.4−2.8+0.2
BH to the middle · return−1.4±3.2−2.8+1.3
BH to their backhand · rally−0.9±3.4−3.8+2.8
FH to their backhand · rally+4.0±4.0+0.7+3.3

Against Mario Ancic-like opponents

Brad Gilbert vMatchesServe pts wonReturn pts won
All charted opponents–55.4%33.6%
Players most similar to Mario Ancic1 57.4%27.6%

Similar by tactical fingerprint: Jan Lennard Struff, Jo Wilfried Tsonga, Tomas Berdych, Andy Roddick, James Blake, Nicolas Kiefer, Yevgeny Kafelnikov, Todd Martin, Cedric Pioline. When two players have rarely met, their records against these lookalikes fill the gap.