RallyIQ

Game plan

Max Purcell v Brandon Nakashima

Every number combines what Max Purcell does well with what Brandon Nakashima allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Max Purcell wins, best of 3 39%90%: 18%–63% · best of 5: 36%
Serve points won 68.9% / 71.4% Max / Brandon · tour 63.8%
Strengths only, no similarity priors 36%serve 68.1% / 71.1%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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 Max Purcell's record against Brandon Nakashima's tactical lookalikes and in their charted head-to-heads (lookalikes: +9.1 on serve, −3.6 on return vs expectation (335 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

CareerMaxBrandon
Direction choice+0.07 ±0.11
better than 77%
−0.01 ±0.07
better than 54%
Shot selection−0.99 ±0.83
better than 3%
−0.11 ±0.14
better than 38%
Execution−0.38 ±0.69
better than 49%
+0.79 ±0.43
better than 91%
Points left on the table2.73 ±0.17
lower than 38%
2.50 ±0.10
lower than 60%

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.

Max Purcell serving

Deuce court

1st serveNowMax winsv BrandonMatchupOptimal
Wide55%68%74%69.5%±6.751% ▼
Body9%63%66%66.0%±12.20% ▼
T36%75%79%78.3%±6.949% ▲

Optimal v Brandon Nakashima: +0.8±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +6.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowMax winsv BrandonMatchupOptimal
Wide45%77%75%79.4%±6.658% ▲
Body11%65%67%68.8%±11.70% ▼
T43%69%74%71.6%±7.142% ▼

Optimal v Brandon Nakashima: +0.7±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.6 per 100 first serves in before the returner adjusts.

Brandon Nakashima serving

Deuce court

1st serveNowBrandon winsv MaxMatchupOptimal
Wide52%73%79%79.0%±6.044% ▼
Body5%64%62%62.3%±12.40% ▼
T43%78%73%75.5%±6.656% ▲

Optimal v Max Purcell: +0.3±0.7 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +2.3 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowBrandon winsv MaxMatchupOptimal
Wide54%72%80%79.9%±6.267% ▲
Body9%69%63%69.2%±11.10% ▼
T37%72%78%77.8%±6.433% ▼

Optimal v Max Purcell: +0.7±0.8 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +1.7 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.

Max Purcell returning

1st serve to the forehand

ReturnNowTourOwnv BrandonValue
FH through the middle37%+4.3−0.9+1.7+5.1±2.6
FH crosscourt21%+5.5−2.2+3.4+6.7±4.1
FH down the line19%+1.7+1.0−1.2+1.5±4.2
FH slice through the middle16%−4.2+1.4−0.4−3.2±2.3
FH slice down the line4%−4.3−1.2+0.5−5.0±2.7

Lean FH crosscourt: +4.1±3.5 per 100 returns v the current mix (189 returns charted)

1st serve to the backhand

ReturnNowTourOwnv BrandonValue
BH through the middle47%+6.4+1.3−0.3+7.4±2.4
BH crosscourt24%+8.8−1.4+0.4+7.8±3.2
BH slice through the middle16%−4.2−2.4+0.4−6.2±2.4
BH down the line9%+4.2−3.7−0.3+0.1±4.0
BH slice crosscourt3%+0.5−0.5+2.1+2.1±2.5

Lean BH crosscourt: +3.3±2.7 per 100 returns v the current mix (148 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv BrandonValue
BH through the middle51%−2.9+2.4+2.3+1.8±2.2
BH crosscourt35%+1.0−0.5−0.2+0.4±2.9
BH down the line14%−0.2+4.2+1.4+5.5±4.2

Lean BH through the middle: ±0.0±1.6 per 100 returns v the current mix (88 returns charted, inside the 90% margin)

Brandon Nakashima returning

1st serve to the forehand

ReturnNowTourOwnv MaxValue
FH through the middle48%+4.3−1.1+0.1+3.3±2.6
FH down the line19%+1.7−1.5+1.5+1.6±4.1
FH slice through the middle14%−4.2+1.0−0.9−4.1±2.3
FH crosscourt11%+5.5+0.6+0.3+6.4±4.3
FH slice down the line4%−4.3+0.9−0.3−3.8±2.7

Lean FH crosscourt: +4.7±4.1 per 100 returns v the current mix (771 returns charted)

1st serve to the backhand

ReturnNowTourOwnv MaxValue
BH through the middle38%+6.4+0.2−1.5+5.1±2.5
BH crosscourt29%+8.8+1.2−1.4+8.6±3.2
BH slice through the middle12%−4.2+0.1−1.2−5.3±2.4
BH down the line10%+4.2−1.3+1.7+4.6±4.3
BH slice crosscourt8%+0.5−3.1−1.5−4.0±2.8

Lean BH crosscourt: +5.0±2.5 per 100 returns v the current mix (648 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv MaxValue
FH through the middle62%−3.5−1.0+2.9−1.6±2.6
FH crosscourt21%−0.2+3.2−0.8+2.2±4.0
FH down the line17%−1.8−0.7−1.7−4.1±4.1

Lean FH crosscourt: +3.4±3.6 per 100 returns v the current mix (228 returns charted, inside the 90% margin)

2nd serve to the backhand

ReturnNowTourOwnv MaxValue
BH through the middle50%−2.9−0.6+0.9−2.6±2.3
BH crosscourt34%+1.0+1.9+0.2+3.2±3.1
BH down the line11%−0.2+0.7−0.4+0.1±4.8
BH slice through the middle4%−11.3−1.2±0.0−12.5±1.5
BH slice crosscourt2%−4.0−0.1±0.0−4.1±1.2

Lean BH crosscourt: +3.9±2.4 per 100 returns v the current mix (387 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.

Max Purcell

Favour

ShotEdgeOwnTheirs
FH to their backhand · return+5.1±5.5+3.0+2.1
FH to their forehand · serve +1+4.9±5.1+0.8+4.1
BH slice to the middle · rally+3.9±3.1+4.6−0.7
BH slice to their forehand · rally+3.6±4.1+1.8+1.8
BH to their backhand · return+1.7±4.0+1.7±0.0
BH slice to their backhand · rally+1.6±3.1+0.8+0.8

Avoid

ShotEdgeOwnTheirs
FH to their forehand · rally−4.1±4.0−3.9−0.3
BH to the middle · rally−2.3±2.8−2.3±0.0
BH to their forehand · rally−2.0±5.3−1.1−0.9
FH to their backhand · rally−0.9±3.9−1.0+0.1
BH to their backhand · rally−0.1±3.2−0.8+0.7

Brandon Nakashima

Favour

ShotEdgeOwnTheirs
FH to their backhand · serve +1+6.3±4.4+3.8+2.5
BH to their forehand · rally+5.6±5.1+0.1+5.5
FH to the middle · serve +1+4.2±3.4+0.8+3.4
BH to the middle · serve +1+4.1±3.4+4.0+0.1
FH to their forehand · serve +1+3.6±4.8+4.5−0.9
FH to their backhand · rally+2.6±3.8−0.8+3.4

Avoid

ShotEdgeOwnTheirs
BH to the middle · rally−1.8±2.7−0.4−1.3
BH to the middle · return−1.0±2.8+0.5−1.4
FH to the middle · rally−0.9±3.0+0.7−1.6
BH to their backhand · rally−0.6±3.2−1.7+1.1
FH to the middle · return−0.3±3.2−1.7+1.4

Against Brandon Nakashima-like opponents

Max Purcell vMatchesServe pts wonReturn pts won
All charted opponents–63.3%32.5%
Players most similar to Brandon Nakashima1 71.3%27.4%

Similar by tactical fingerprint: Casper Ruud, Karen Khachanov, Marcos Giron, Jaume Munar, Roberto Bautista Agut, Pablo Carreno Busta, Taylor Fritz, Rinky Hijikata, Gregoire Barrere, Tennys Sandgren. When two players have rarely met, their records against these lookalikes fill the gap.