RallyIQ

Game plan

Monica Puig v Alexandra Eala

Every number combines what Monica Puig does well with what Alexandra Eala allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Monica Puig wins, best of 3 15%90%: 1%–58% · best of 5: 10%
Serve points won 52.1% / 59.8% Monica / Alexandra · tour 58.1%
Strengths only, no similarity priors 15%serve 52.1% / 59.8%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerMonicaAlexandra
Direction choice−0.25 ±0.10
better than 10%
−0.02 ±0.07
better than 50%
Shot selection+0.21 ±0.30
better than 69%
+0.35 ±0.15
better than 83%
Execution−1.94 ±0.79
better than 4%
+0.51 ±0.45
better than 79%

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.

Monica Puig serving

Deuce court

1st serveNowMonica winsv AlexandraMatchupOptimal
Wide27%60%61%54.7%±10.231% ▲
Body19%58%59%59.2%±11.44% ▼
T54%60%73%66.2%±8.765% ▲

Optimal v Alexandra Eala: +0.2±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +4.5 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMonica winsv AlexandraMatchupOptimal
Wide40%65%64%63.6%±9.550% ▲
Body16%55%51%49.8%±12.61% ▼
T44%59%59%52.9%±9.449% ▲

Optimal v Alexandra Eala: +0.2±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +6.9 per 100 first serves in before the returner adjusts.

Alexandra Eala serving

Deuce court

1st serveNowAlexandra winsv MonicaMatchupOptimal
Wide30%66%69%68.6%±9.245% ▲
Body29%56%59%58.3%±11.014% ▼
T41%55%80%70.2%±10.141%

Optimal v Monica Puig: +0.7±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.9 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowAlexandra winsv MonicaMatchupOptimal
Wide39%61%74%69.7%±9.154% ▲
Body26%55%57%56.1%±12.211% ▼
T35%62%70%68.1%±10.335%

Optimal v Monica Puig: +0.6±1.1 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.1 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.

Monica Puig returning

1st serve to the forehand

ReturnNowTourOwnv AlexandraValue
FH through the middle62%+4.2−1.3−2.1+0.8±2.8
FH crosscourt23%+5.3−1.2+1.3+5.4±3.9
FH down the line15%+1.5−2.2+0.6±0.0±4.2

Lean FH crosscourt: +3.7±3.5 per 100 returns v the current mix (87 returns charted)

1st serve to the backhand

ReturnNowTourOwnv AlexandraValue
BH through the middle55%+6.0−1.2+2.9+7.8±2.6
BH crosscourt29%+7.7−2.9+5.8+10.6±3.2
BH down the line17%+2.2−2.7+1.4+0.9±4.1

Lean BH crosscourt: +3.2±2.8 per 100 returns v the current mix (66 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv AlexandraValue
BH through the middle44%−2.6+0.9+1.2−0.5±2.6
BH crosscourt41%+1.5+1.4−0.8+2.1±3.4
BH down the line15%−0.5+1.7+0.7+1.9±4.5

Lean BH crosscourt: +1.2±2.4 per 100 returns v the current mix (54 returns charted, inside the 90% margin)

Alexandra Eala returning

1st serve to the forehand

ReturnNowTourOwnv MonicaValue
FH through the middle44%+4.2+1.5−1.6+4.1±3.0
FH crosscourt36%+5.3+2.3+0.8+8.4±4.0
FH down the line11%+1.5+1.0+1.6+4.1±4.6
FH slice crosscourt4%−6.6−0.4±0.0−7.0±1.6
FH slice through the middle3%−6.7−0.5−0.2−7.4±2.0

Lean FH crosscourt: +4.0±2.9 per 100 returns v the current mix (342 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MonicaValue
BH through the middle48%+6.0+1.3−1.0+6.4±2.6
BH crosscourt37%+7.7+1.3−2.2+6.9±3.3
BH down the line7%+2.2+3.2−0.4+5.0±4.6
BH slice through the middle5%−6.2+2.3+0.8−3.1±2.2
BH slice crosscourt3%−4.2−0.3+0.6−3.9±2.1

Lean BH crosscourt: +1.4±2.4 per 100 returns v the current mix (436 returns charted, inside the 90% margin)

2nd serve to the forehand

ReturnNowTourOwnv MonicaValue
FH through the middle37%−3.2+2.3+0.7−0.2±3.0
FH down the line33%−0.6+0.3+1.2+1.0±5.1
FH crosscourt30%+0.5+1.6+1.3+3.5±4.1

Lean FH crosscourt: +2.2±3.5 per 100 returns v the current mix (134 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MonicaValue
BH crosscourt48%+1.5+1.7−1.0+2.2±3.3
BH through the middle38%−2.6+0.9+2.8+1.1±2.7
BH down the line10%−0.5+0.5+0.6+0.6±5.1
BH slice crosscourt3%−7.5−1.9±0.0−9.4±1.4

Lean BH crosscourt: +1.0±2.1 per 100 returns v the current mix (222 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.

Monica Puig

Favour

ShotEdgeOwnTheirs
FH to the middle · rally+4.0±3.1−0.2+4.2
BH to the middle · return+3.9±3.1−1.0+4.8
FH to their forehand · rally+3.2±5.0−2.3+5.5
FH to their backhand · serve +1+2.1±5.0−0.3+2.4
BH to their backhand · rally+1.1±3.1−1.9+2.9
FH to their backhand · rally+0.1±5.4−3.4+3.6

Avoid

ShotEdgeOwnTheirs
FH to the middle · return−2.5±3.4−1.3−1.2
BH to the middle · rally−2.0±2.8±0.0−2.1
BH to the middle · serve +1−1.3±3.0−2.8+1.6
BH to their forehand · rally±0.0±5.4−0.5+0.5
FH to their backhand · rally+0.1±5.4−3.4+3.6

Alexandra Eala

Favour

ShotEdgeOwnTheirs
BH to the middle · return+5.3±3.7+4.0+1.3
BH to their backhand · rally+4.3±3.9+1.3+3.0
FH to their forehand · rally+3.0±4.4+2.8+0.1
FH to the middle · return+3.0±3.5+3.9−0.9
FH to the middle · rally+1.7±3.1+1.4+0.3
BH to their backhand · return+0.4±3.6+0.3+0.1

Avoid

ShotEdgeOwnTheirs
FH to their backhand · rally−0.8±4.7−2.2+1.4
BH to the middle · rally−0.6±2.9±0.0−0.6
BH to their backhand · return+0.4±3.6+0.3+0.1
FH to the middle · rally+1.7±3.1+1.4+0.3
FH to the middle · return+3.0±3.5+3.9−0.9

Against Alexandra Eala-like opponents

Monica Puig vMatchesServe pts wonReturn pts won
All charted opponents–52.0%36.3%

Similar by tactical fingerprint: Diana Shnaider, Anna Blinkova, Marta Kostyuk, Iga Swiatek, Jasmine Paolini, Maya Joint, Jaqueline Cristian, Nao Hibino, Eugenie Bouchard, Dominika Cibulkova. When two players have rarely met, their records against these lookalikes fill the gap.