RallyIQ

Game plan

Robin Montgomery v Irina Camelia Begu

Every number combines what Robin Montgomery does well with what Irina Camelia Begu allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Robin Montgomery wins, best of 3 87%90%: 54%–98% · best of 5: 92%
Serve points won 63.1% / 54.5% Robin / Irina · tour 58.1%
Strengths only, no similarity priors 85%serve 62.7% / 54.7%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Robin Montgomery's record against Irina Camelia Begu's tactical lookalikes and in their charted head-to-heads (lookalikes: +13.1 on serve, +4.8 on return vs expectation (100 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

CareerRobinIrina
Direction choice−0.38 ±0.19
better than 2%
−0.31 ±0.08
better than 6%
Shot selection+0.05 ±0.23
better than 50%
−0.15 ±0.15
better than 31%
Execution−1.17 ±1.25
better than 16%
−1.73 ±0.43
better than 7%

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.

Robin Montgomery serving

Deuce court

1st serveNowRobin winsv IrinaMatchupOptimal
Wide32%72%71%76.6%±9.932%
Body28%62%61%65.0%±11.313% ▼
T40%69%74%75.2%±9.355% ▲

Optimal v Irina Camelia Begu: +0.6±1.2 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.8 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowRobin winsv IrinaMatchupOptimal
Wide39%61%76%73.0%±10.254% ▲
Body21%60%57%60.5%±13.16% ▼
T40%73%64%72.9%±9.740%

Optimal v Irina Camelia Begu: +0.9±1.3 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.7 per 100 first serves in before the returner adjusts.

Irina Camelia Begu serving

Deuce court

1st serveNowIrina winsv RobinMatchupOptimal
Wide42%66%69%69.2%±9.457% ▲
Body17%56%61%59.3%±12.29% ▼
T40%54%74%61.0%±12.034% ▼

Optimal v Robin Montgomery: +0.3±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +5.1 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowIrina winsv RobinMatchupOptimal
Wide43%52%65%51.2%±11.158% ▲
Body22%56%43%43.1%±13.26% ▼
T36%64%63%62.5%±11.336%

Optimal v Robin Montgomery: +0.7±1.3 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +9.0 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.

Robin Montgomery returning

1st serve to the forehand

ReturnNowTourOwnv IrinaValue
FH through the middle65%+4.2+0.2+1.4+5.8±3.0
FH down the line20%+1.5−1.1−2.3−1.8±4.5
FH crosscourt14%+5.3±0.0+0.5+5.8±3.9

Lean FH through the middle: +1.6±1.5 per 100 returns v the current mix (98 returns charted)

1st serve to the backhand

ReturnNowTourOwnv IrinaValue
BH through the middle45%+6.0+0.1+2.5+8.6±2.8
BH crosscourt24%+7.7−0.2+2.8+10.4±3.5
BH slice through the middle14%−6.2−3.1+1.0−8.3±2.1
BH down the line13%+2.2−1.7−0.4±0.0±4.3
BH slice crosscourt5%−4.2−1.1±0.0−5.3±1.3

Lean BH crosscourt: +5.4±3.0 per 100 returns v the current mix (118 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv IrinaValue
BH through the middle59%−2.6+0.5−0.3−2.4±2.8
BH crosscourt22%+1.5−1.8−0.6−0.9±3.0
BH down the line19%−0.5−3.1−1.1−4.7±4.7

Lean BH through the middle: +0.1±1.6 per 100 returns v the current mix (63 returns charted, inside the 90% margin)

Irina Camelia Begu returning

1st serve to the forehand

ReturnNowTourOwnv RobinValue
FH through the middle47%+4.2−1.9+1.2+3.5±3.2
FH down the line22%+1.5+1.7−5.1−1.9±4.6
FH crosscourt19%+5.3−0.8−2.1+2.4±4.0
FH slice through the middle9%−6.7−0.3−0.6−7.5±2.2
FH slice down the line3%−10.5+0.5+0.1−9.9±2.4

Lean FH through the middle: +2.8±2.1 per 100 returns v the current mix (155 returns charted)

1st serve to the backhand

ReturnNowTourOwnv RobinValue
BH through the middle53%+6.0−3.0+1.4+4.5±2.9
BH down the line26%+2.2−1.6−3.4−2.8±4.5
BH crosscourt13%+7.7−2.6+1.7+6.9±3.4
BH slice through the middle7%−6.2+0.5−1.4−7.1±2.0

Lean BH crosscourt: +4.8±3.5 per 100 returns v the current mix (126 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv RobinValue
BH through the middle57%−2.6−3.0−0.1−5.6±2.8
BH down the line24%−0.5−0.6−2.3−3.4±4.2
BH crosscourt19%+1.5−0.9−0.1+0.5±3.4

Lean BH crosscourt: +4.5±3.4 per 100 returns v the current mix (91 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 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.

Robin Montgomery

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+5.4±4.8+1.3+4.1
BH to the middle · return+2.7±3.3+0.6+2.1
FH to their forehand · rally+1.5±4.5−2.0+3.5
FH to the middle · return+0.3±3.5−0.7+1.0
BH to the middle · rally−0.8±3.0−1.8+1.0
FH to the middle · rally−2.0±3.1−0.7−1.3

Avoid

ShotEdgeOwnTheirs
FH to their forehand · serve +1−5.4±4.9−3.1−2.3
FH to their forehand · return−2.7±4.6−2.3−0.4
FH to their backhand · serve +1−2.6±5.3−5.6+3.0
BH to their forehand · rally−2.1±5.6−0.3−1.7
FH to the middle · rally−2.0±3.1−0.7−1.3

Irina Camelia Begu

Favour

ShotEdgeOwnTheirs
FH to the middle · serve +1+0.6±3.3−0.8+1.4
FH to the middle · return−1.0±3.7−2.4+1.4
FH to their forehand · serve +1−1.2±5.3−0.1−1.0
FH to the middle · rally−1.8±3.1−2.1+0.3
BH to their forehand · return−2.4±5.5−3.3+0.9
FH to their backhand · serve +1−3.3±5.5−1.4−1.9

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−9.5±4.5−8.4−1.1
BH to the middle · return−9.1±3.3−9.4+0.3
FH to their backhand · rally−5.6±4.9−5.6±0.0
FH to their forehand · rally−4.8±4.5−3.5−1.4
BH to the middle · rally−3.8±2.9−5.0+1.3

Against Irina Camelia Begu-like opponents

Robin Montgomery vMatchesServe pts wonReturn pts won
All charted opponents–58.0%41.7%
Players most similar to Irina Camelia Begu1 71.7%48.1%

Similar by tactical fingerprint: Cristina Bucsa, Karolina Pliskova, Maya Joint, Jaqueline Cristian, Victoria Mboko, Nao Hibino, Shelby Rogers, Anett Kontaveit, Alison Riske Amritraj. When two players have rarely met, their records against these lookalikes fill the gap.