RallyIQ

Game plan

Irina Camelia Begu v Leylah Fernandez

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

Forecast

Irina Camelia Begu wins, best of 3 10%90%: 1%–38% · best of 5: 6%
Serve points won 49.9% / 59.4% Irina / Leylah · tour 55.0%
Strengths only, no similarity priors 10%serve 49.9% / 59.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Irina Camelia Begu's record against Leylah Fernandez'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

CareerIrinaLeylah
Direction choice−0.31 ±0.08
better than 6%
−0.17 ±0.06
better than 23%
Shot selection−0.15 ±0.15
better than 31%
+0.22 ±0.11
better than 69%
Execution−1.73 ±0.43
better than 7%
+0.34 ±0.42
better than 74%
Points left on the table2.91 ±0.10
lower than 15%
3.33 ±0.10
lower than 3%

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.

Irina Camelia Begu serving

Deuce court

1st serveNowIrina winsv LeylahMatchupOptimal
Wide42%66%67%67.1%±7.257% ▲
Body17%56%58%56.6%±9.910% ▼
T40%54%69%55.5%±8.633% ▼

Optimal v Leylah Fernandez: +0.5±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +6.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowIrina winsv LeylahMatchupOptimal
Wide43%52%69%56.5%±7.948% ▲
Body22%56%53%52.2%±10.36% ▼
T36%64%66%66.0%±7.946% ▲

Optimal v Leylah Fernandez: +0.7±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +7.0 per 100 first serves in before the returner adjusts.

Leylah Fernandez serving

Deuce court

1st serveNowLeylah winsv IrinaMatchupOptimal
Wide35%69%71%74.1%±7.635%
Body19%57%61%60.0%±9.34% ▼
T45%64%74%71.3%±7.761% ▲

Optimal v Irina Camelia Begu: +0.6±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowLeylah winsv IrinaMatchupOptimal
Wide54%69%76%78.9%±7.169% ▲
Body16%55%57%55.4%±10.81% ▼
T30%71%64%70.6%±7.830%

Optimal v Irina Camelia Begu: +1.3±1.1 per 100 first serves (faults included) over the current mix. Serving wide every time would read +6.3 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.

Irina Camelia Begu returning

1st serve to the forehand

ReturnNowTourOwnv LeylahValue
FH through the middle47%+4.2−1.9±0.0+2.2±2.7
FH down the line22%+1.5+1.7−1.5+1.7±4.4
FH crosscourt19%+5.3−0.8+0.9+5.4±4.0
FH slice through the middle9%−6.7−0.3−0.5−7.5±2.4
FH slice down the line3%−10.5+0.5−1.2−11.2±2.5

Lean FH crosscourt: +4.0±3.6 per 100 returns v the current mix (155 returns charted)

1st serve to the backhand

ReturnNowTourOwnv LeylahValue
BH through the middle53%+6.0−3.0+1.2+4.2±2.4
BH down the line26%+2.2−1.6−3.0−2.4±4.3
BH crosscourt13%+7.7−2.6+2.6+7.8±3.0
BH slice through the middle7%−6.2+0.5−1.7−7.4±2.2

Lean BH crosscourt: +5.7±3.1 per 100 returns v the current mix (126 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv LeylahValue
BH through the middle57%−2.6−3.0+1.7−3.9±2.4
BH down the line24%−0.5−0.6−2.0−3.2±4.9
BH crosscourt19%+1.5−0.9−2.1−1.5±3.2

Lean BH crosscourt: +1.7±3.2 per 100 returns v the current mix (91 returns charted, inside the 90% margin)

Leylah Fernandez returning

1st serve to the forehand

ReturnNowTourOwnv IrinaValue
FH through the middle48%+4.2+2.6+1.4+8.2±2.5
FH crosscourt29%+5.3+1.3+0.5+7.1±3.9
FH down the line20%+1.5−3.0−2.3−3.8±4.5
FH slice through the middle2%−6.7−0.4−0.9−8.1±2.1
FH slice down the line1%−10.5−1.0+0.2−11.3±2.1

Lean FH through the middle: +3.2±1.9 per 100 returns v the current mix (626 returns charted)

1st serve to the backhand

ReturnNowTourOwnv IrinaValue
BH through the middle45%+6.0−1.6+2.5+6.9±2.3
BH crosscourt24%+7.7+0.7+2.8+11.3±3.2
BH down the line11%+2.2−1.0−0.4+0.8±4.6
BH slice through the middle10%−6.2−0.3+1.0−5.5±2.3
BH slice crosscourt6%−4.2−1.9±0.0−6.0±2.2

Lean BH crosscourt: +7.1±2.7 per 100 returns v the current mix (845 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv IrinaValue
FH crosscourt44%+0.5±0.0−2.7−2.2±4.3
FH through the middle39%−3.2+3.1−1.9−2.0±3.0
FH down the line17%−0.6+0.6+1.9+2.0±5.2

Lean FH down the line: +3.4±4.8 per 100 returns v the current mix (186 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv IrinaValue
BH through the middle45%−2.6+1.0−0.3−1.9±2.6
BH crosscourt34%+1.5±0.0−0.6+0.9±3.1
BH down the line15%−0.5+1.5−1.1−0.2±5.2
FH through the middle3%−2.7+0.1−1.9−4.5±2.3
BH slice through the middle1%−11.7−0.9±0.0−12.6±1.1

Lean BH crosscourt: +1.8±2.5 per 100 returns v the current mix (406 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 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.

Irina Camelia Begu

Favour

ShotEdgeOwnTheirs
BH to their backhand · serve +1+2.6±4.9+2.6±0.0
BH to the middle · serve +1+2.2±3.3+0.2+2.0
FH to the middle · rally+1.9±3.1−0.2+2.1
FH to their forehand · serve +1+1.9±5.2−0.7+2.6
BH to their forehand · serve +1+1.8±6.3+0.2+1.6
FH to their forehand · return +1+1.5±5.3+1.4+0.1

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−9.3±5.7−10.5+1.2
BH to the middle · rally−4.3±3.0−2.9−1.4
BH to their forehand · return−3.9±5.6−5.0+1.1
BH to the middle · return−3.6±3.2−3.2−0.4
FH to the middle · return +1−1.4±3.5−0.8−0.6

Leylah Fernandez

Favour

ShotEdgeOwnTheirs
FH to the middle · serve +1+3.5±3.3+1.8+1.7
FH to their backhand · serve +1+3.1±5.0+3.4−0.3
FH to their forehand · rally+2.4±4.5−0.6+3.0
FH to the middle · rally+2.3±3.1+0.9+1.4
FH to their forehand · return +1+2.0±5.3+2.2−0.2
BH to the middle · return+1.8±3.2−1.0+2.8

Avoid

ShotEdgeOwnTheirs
BH to their backhand · serve +1−5.6±5.0−0.6−5.0
BH to their backhand · return +1−3.9±4.8−3.5−0.4
BH to the middle · rally−3.1±3.0−4.0+0.9
BH to their backhand · rally−2.4±4.2−3.0+0.6
BH to their backhand · return−2.0±4.5−1.9−0.2

Against Leylah Fernandez-like opponents

Irina Camelia Begu vMatchesServe pts wonReturn pts won
All charted opponents–50.2%39.0%

Similar by tactical fingerprint: Cristina Bucsa, Alexandra Eala, Diana Shnaider, Karolina Muchova, Marta Kostyuk, Sorana Cirstea, Olga Danilovic, Kaja Juvan, Victoria Azarenka. When two players have rarely met, their records against these lookalikes fill the gap.