RallyIQ

Game plan

Jelle Sels v Hugo Gaston

Every number combines what Jelle Sels does well with what Hugo Gaston allows, each measured against the tour average and shrunk toward it when the sample is thin. Flip perspective

Forecast

Jelle Sels wins, best of 3 45%90%: 13%–80% · best of 5: 43%
Serve points won 65.3% / 66.4% Jelle / Hugo · tour 65.7%
Strengths only, no similarity priors 45%serve 65.3% / 66.4%

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 At least one of them is no longer active or has too little charted in the last three seasons, so both are compared on their careers.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

CareerJelleHugo
Direction choice−0.18 ±0.19
better than 18%
−0.07 ±0.15
better than 39%
Shot selection−0.18 ±0.39
better than 31%
−0.41 ±0.24
better than 16%
Execution−2.18 ±0.42
better than 2%
−0.58 ±0.52
better than 42%
Points left on the table2.84 ±0.25
lower than 28%
3.11 ±0.27
lower than 15%

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.

Jelle Sels serving

Deuce court

1st serveNowJelle winsv HugoMatchupOptimal
Wide40%63%68%58.5%±10.538% ▼
Body12%65%54%55.9%±15.80% ▼
T49%64%75%63.7%±10.462% ▲

Optimal v Hugo Gaston: +0.4±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +3.0 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowJelle winsv HugoMatchupOptimal
Wide64%70%79%75.9%±8.562% ▼
Body11%60%60%56.9%±15.90% ▼
T25%71%73%72.2%±11.138% ▲

Optimal v Hugo Gaston: +0.6±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +3.1 per 100 first serves in before the returner adjusts.

Hugo Gaston serving

Deuce court

1st serveNowHugo winsv JelleMatchupOptimal
Wide41%69%76%72.7%±10.554% ▲
Body16%66%68%70.6%±12.816%
T43%67%72%63.8%±9.930% ▼

Optimal v Jelle Sels: +0.2±1.0 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving wide every time would read +4.2 per 100 first serves in before the returner adjusts.

Ad court

1st serveNowHugo winsv JelleMatchupOptimal
Wide67%72%73%72.0%±8.461% ▼
Body7%66%63%65.6%±15.80% ▼
T26%75%72%74.5%±11.739% ▲

Optimal v Jelle Sels: +0.3±0.9 per 100 first serves (faults included) over the current mix, inside the 90% margin. Serving T every time would read +2.3 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.

Jelle Sels returning

1st serve to the forehand

ReturnNowTourOwnv HugoValue
FH through the middle32%+4.3−1.2−1.9+1.2±2.9
FH slice through the middle32%−4.2−0.5+0.4−4.3±2.0
FH down the line26%+1.7−0.5−3.4−2.3±4.0
FH crosscourt11%+5.5−0.6−1.0+3.9±3.7

Lean FH through the middle: +2.4±2.4 per 100 returns v the current mix (57 returns charted, inside the 90% margin)

1st serve to the backhand

ReturnNowTourOwnv HugoValue
BH through the middle28%+6.4−1.0+2.1+7.5±2.7
BH slice through the middle28%−4.2−0.9+0.6−4.6±2.4
BH slice crosscourt17%+0.5+0.4+1.5+2.5±2.7
BH crosscourt10%+8.8+1.5−1.3+9.0±3.3
BH down the line9%+4.2−1.7±0.0+2.5±4.2

Lean BH crosscourt: +7.2±3.2 per 100 returns v the current mix (144 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv HugoValue
FH through the middle35%−2.9±0.0−0.5−3.4±2.3
FH inside-out29%+1.0−3.1+1.3−0.8±3.4
BH through the middle22%−2.9−1.1−0.1−4.1±2.3
BH crosscourt15%+1.0−1.8−0.5−1.3±2.8

Lean FH inside-out: +1.7±2.6 per 100 returns v the current mix (55 returns charted, inside the 90% margin)

Hugo Gaston returning

1st serve to the forehand

ReturnNowTourOwnv JelleValue
FH through the middle43%+4.3+0.5+1.6+6.3±3.1
FH crosscourt19%+5.5−4.2−3.4−2.0±3.8
FH slice through the middle17%−4.2−0.5+1.2−3.5±2.1
FH down the line16%+1.7−2.1+2.3+2.0±4.1
FH slice crosscourt5%−4.3−0.1±0.0−4.4±1.4

Lean FH through the middle: +4.5±2.0 per 100 returns v the current mix (152 returns charted)

1st serve to the backhand

ReturnNowTourOwnv JelleValue
BH through the middle39%+6.4−1.1+0.1+5.5±2.9
BH crosscourt34%+8.8−3.4−2.3+3.0±3.5
BH slice through the middle13%−4.2−1.4−1.2−6.8±2.3
BH down the line9%+4.2−1.4−0.7+2.1±4.3
BH slice crosscourt4%+0.5−1.4±0.0−0.8±1.4

Lean BH through the middle: +3.0±2.2 per 100 returns v the current mix (180 returns charted)

2nd serve to the forehand

ReturnNowTourOwnv JelleValue
FH through the middle44%−3.5+0.4+0.6−2.5±2.9
FH crosscourt37%−0.2+0.1+1.5+1.3±4.3
FH down the line13%−1.8−1.2−0.4−3.4±3.6
FH slice crosscourt6%−12.5±0.0±0.0−12.5±1.3

Lean FH crosscourt: +3.1±3.1 per 100 returns v the current mix (84 returns charted)

2nd serve to the backhand

ReturnNowTourOwnv JelleValue
BH through the middle55%−2.9−1.4+0.8−3.5±2.6
BH crosscourt38%+1.0−0.8−1.3−1.1±2.8
BH down the line8%−0.2−1.0−0.9−2.1±4.0

Lean BH crosscourt: +1.4±2.3 per 100 returns v the current mix (80 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.

Jelle Sels

Favour

ShotEdgeOwnTheirs
BH to the middle · return+1.1±3.1−1.1+2.2
BH to the middle · rally+0.6±2.4+1.2−0.6
FH to the middle · rally−0.3±2.6−0.3−0.1
FH to their backhand · return +1−2.1±4.0−1.5−0.5
BH to their backhand · rally−2.3±3.0−1.6−0.7
FH to their forehand · rally−3.3±4.2−1.1−2.2

Avoid

ShotEdgeOwnTheirs
FH to their backhand · rally−7.1±3.8−2.0−5.1
FH to their forehand · serve +1−5.8±4.9−3.1−2.6
FH to the middle · return−4.5±2.8−1.5−3.0
FH to their backhand · serve +1−3.9±3.5−2.7−1.1
FH to their forehand · rally−3.3±4.2−1.1−2.2

Hugo Gaston

Favour

ShotEdgeOwnTheirs
FH to their backhand · rally+3.5±3.9+3.7−0.2
FH to their backhand · serve +1+2.6±3.7+1.8+0.7
FH to their forehand · serve +1+1.9±5.0+1.7+0.2
FH to the middle · return+0.9±3.4−0.2+1.1
BH to the middle · return+0.4±2.5−0.3+0.8
FH to the middle · rally+0.4±2.5+1.1−0.8

Avoid

ShotEdgeOwnTheirs
BH to their forehand · rally−6.9±4.2−0.5−6.4
BH to their backhand · rally−5.9±2.9−3.3−2.6
BH to the middle · rally−1.2±2.3−1.1−0.1
FH to their forehand · rally−0.9±3.6+2.5−3.5
FH to the middle · rally+0.4±2.5+1.1−0.8

Against Hugo Gaston-like opponents

Jelle Sels vMatchesServe pts wonReturn pts won
All charted opponents–60.5%35.2%

Similar by tactical fingerprint: Carlos Alcaraz, Alexander Bublik, Luciano Darderi, Pedro Martinez, Yannick Hanfmann, Mattia Bellucci, Benoit Paire, Marco Cecchinato, Gustavo Kuerten, Gaston Gaudio. When two players have rarely met, their records against these lookalikes fill the gap.