RallyIQ

Game plan

Tomas Machac v Ricardas Berankis

Every number combines what Tomas Machac does well with what Ricardas Berankis allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Tomas Machac wins, best of 3 74%90%: 50%–90% · best of 5: 79%
Serve points won 64.2% / 59.1% Tomas / Ricardas · tour 63.8%
Strengths only, no similarity priors 74%serve 64.2% / 59.1%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerTomasRicardas
Direction choice+0.12 ±0.07
better than 83%
−0.04 ±0.13
better than 47%
Shot selection+0.08 ±0.15
better than 63%
+0.30 ±0.24
better than 79%
Execution+0.15 ±0.51
better than 75%
−1.82 ±0.66
better than 6%

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.

Tomas Machac serving

Deuce court

1st serveNowTomas winsv RicardasMatchupOptimal
Wide44%67%73%67.0%±8.638% ▼
Body6%62%66%64.9%±13.20% ▼
T49%74%75%73.7%±8.362% ▲

Optimal v Ricardas Berankis: +0.6±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.6 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowTomas winsv RicardasMatchupOptimal
Wide46%70%71%67.4%±8.633% ▼
Body8%64%74%74.8%±11.88%
T46%72%70%70.2%±8.459% ▲

Optimal v Ricardas Berankis: +0.7±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving body every time would read +5.6 per 100 first serves in before the returner adjusts.

Ricardas Berankis serving

Deuce court

1st serveNowRicardas winsv TomasMatchupOptimal
Wide31%64%74%65.7%±9.331%
Body15%59%66%61.3%±13.42% ▼
T54%70%78%73.3%±7.567% ▲

Optimal v Tomas Machac: +0.5±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRicardas winsv TomasMatchupOptimal
Wide40%63%71%61.0%±9.753% ▲
Body10%52%60%48.5%±15.60% ▼
T50%68%68%63.3%±8.947% ▼

Optimal v Tomas Machac: +0.5±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.5 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.

Tomas Machac returning

1st serve to the forehand

ReturnNowTourOwnv RicardasValue
FH through the middle48%+4.3+2.7+0.9+7.8±2.8
FH down the line27%+1.7+1.7+1.7+5.1±4.3
FH crosscourt17%+5.5+3.2+0.9+9.6±4.1
FH slice through the middle6%−4.2−1.2−0.1−5.5±2.2
FH slice down the line3%−4.3+1.3−0.5−3.4±2.3

Lean FH crosscourt: +3.3±3.8 per 100 returns v the current mix (465 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv RicardasValue
BH through the middle37%+6.4+1.1+1.8+9.3±2.6
BH crosscourt31%+8.8+3.1±0.0+11.9±3.3
BH slice through the middle13%−4.2+2.1+0.3−1.9±2.4
BH down the line9%+4.2+2.2+1.6+8.0±4.2
BH slice crosscourt6%+0.5−0.5+0.9+0.9±2.6

Lean BH crosscourt: +4.7±2.5 per 100 returns v the current mix (508 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv RicardasValue
FH through the middle39%−3.5+1.7+1.4−0.4±2.9
FH down the line33%−1.8−0.2+0.3−1.7±4.6
FH crosscourt24%−0.2+2.3+1.1+3.2±4.0
FH slice through the middle4%−12.7−0.5±0.0−13.2±1.1

Lean FH crosscourt: +3.6±3.6 per 100 returns v the current mix (163 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv RicardasValue
BH crosscourt51%+1.0+1.0−0.1+1.9±3.0
BH through the middle37%−2.9+0.5+1.8−0.6±2.5
BH down the line9%−0.2−1.1−0.2−1.6±4.8
FH through the middle3%−2.9+0.4+1.4−1.1±2.1

Lean BH crosscourt: +1.3±1.8 per 100 returns v the current mix (339 returns charted, inside the 90% margin)

Ricardas Berankis returning

1st serve to the forehand

ReturnNowTourOwnv TomasValue
FH through the middle55%+4.3−3.8+1.3+1.7±2.7
FH crosscourt28%+5.5+0.6+4.9+11.0±4.2
FH down the line17%+1.7+0.8+2.9+5.3±4.1

Lean FH crosscourt: +6.1±3.4 per 100 returns v the current mix (114 returns charted)

1st serve to the backhand

ReturnNowTourOwnv TomasValue
BH through the middle36%+6.4−0.1+1.8+8.1±2.5
BH slice through the middle28%−4.2−1.0±0.0−5.2±2.4
BH crosscourt21%+8.8−0.5+2.2+10.5±3.3
BH slice crosscourt10%+0.5−1.4+0.3−0.6±2.7
BH down the line5%+4.2−2.9±0.0+1.3±3.8

Lean BH crosscourt: +6.8±2.8 per 100 returns v the current mix (111 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv TomasValue
BH through the middle49%−2.9−0.7−1.2−4.8±2.2
BH crosscourt30%+1.0+0.5+1.4+2.9±2.7
BH down the line21%−0.2+0.3+2.0+2.2±4.4

Lean BH crosscourt: +3.9±2.4 per 100 returns v the current mix (53 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.

Tomas Machac

Favour

ShotEdgeOwnTheirs
FH to the middle · return+4.4±3.3+2.9+1.5
BH to their backhand · rally+4.2±2.9+0.5+3.6
BH to the middle · return+3.2±2.8−0.1+3.3
FH to their backhand · return+1.4±5.3−0.6+2.0
BH to their backhand · return+1.4±3.9+2.0−0.6
BH to the middle · rally−0.4±2.8−0.6+0.2

Avoid

ShotEdgeOwnTheirs
FH to their forehand · rally−3.3±4.0−1.5−1.8
FH to the middle · rally−3.2±3.1−0.5−2.7
FH to their backhand · rally−2.9±3.9−0.8−2.0
BH to the middle · rally−0.4±2.8−0.6+0.2
BH to their backhand · return+1.4±3.9+2.0−0.6

Ricardas Berankis

Favour

ShotEdgeOwnTheirs
FH to their backhand · serve +1+9.4±4.6+4.6+4.8
FH to their forehand · return+4.6±5.8+0.8+3.8
FH to their forehand · rally+4.0±4.0+2.9+1.1
BH to their forehand · rally+3.7±5.4−0.7+4.4
FH to their forehand · serve +1+2.3±4.9+1.2+1.1
BH to their backhand · rally+0.3±3.1−0.4+0.7

Avoid

ShotEdgeOwnTheirs
BH to their backhand · serve +1−5.5±4.1−6.6+1.1
FH to the middle · rally−3.4±3.2−2.7−0.7
FH to the middle · return−2.5±3.3−3.8+1.3
FH to their backhand · rally−2.3±3.8−1.7−0.6
BH to the middle · return−1.3±3.0−1.5+0.3

Against Ricardas Berankis-like opponents

Tomas Machac vMatchesServe pts wonReturn pts won
All charted opponents–62.8%35.7%

Similar by tactical fingerprint: Zhizhen Zhang, Ethan Quinn, Benjamin Bonzi, Fabio Fognini, Lucas Pouille, Peter Gojowczyk, Kevin Anderson, Denis Kudla, Martin Klizan. When two players have rarely met, their records against these lookalikes fill the gap.