Paul vs Bonzi Prediction: Grand Prix Auvergne-Rhone-Alpes 2026 Round of 16
Paul's unbeaten head-to-head deserves supporting weight, but his current hard-court serve and return numbers provide the stronger reason to favor him.
Benjamin Bonzi's winless record against Tommy Paul deserves weight, but its age limits its value for their Grand Prix Auvergne-Rhone-Alpes round of 16 match. Court Shark's model gives Paul a 76% chance, with current hard-court performance also supporting him.
Paul's unbeaten record is relevant, but old
On June 14, 2023, Benjamin Bonzi lost to Tommy Paul in Stuttgart, their most recent meeting. Paul won without dropping a set, continuing a pattern that matters here even though that match was on grass rather than hard courts. The history favors Paul.
Their meeting in Lyon on Wednesday puts a quarterfinal place at the Grand Prix Auvergne-Rhone-Alpes within reach. For Bonzi, it is a chance to turn a fresh tournament win into a deeper run; Paul enters after losing his last match in Shanghai.
Bonzi's head-to-head record stood at 0-3 overall and 0-2 on hard courts. Paul also won their Miami and Adelaide meetings in straight sets in two thousand twenty-two, although Adelaide included a tiebreak. Those results establish a consistent advantage, not a recent test: several seasons have passed without either player having to solve this particular opponent.
Head-to-head by surface
Article snapshot, Oct 20, 2026 · Not live
Benjamin Bonzi and Tommy Paul have met 3 times. Tommy Paul leads 3-0.
| Surface | Benjamin Bonzi | Tommy Paul |
|---|---|---|
| All surfaces | 0 | 3 |
| Hard | 0 | 2 |
| Grass | 0 | 1 |
Current hard-court numbers support the history
The stronger reason to retain Paul as the favorite is that his recent hard-court service record points in the same direction as those older results. Over the past year, Bonzi held 83% of his service games, while Paul held 86%. Both protected serve effectively. Paul's advantage suggests Bonzi may have fewer openings than his own solid serving would initially imply.
On return, Bonzi broke in 21% of games and Paul in 23% over the same period. That gives Paul an edge on both sides of the matchup, rather than leaving the argument dependent on meetings from earlier seasons. The percentages describe separate schedules, however, not what either player necessarily produces against this opponent. My reading is that the old record deserves supporting weight because the current surface figures broadly agree with it. It should not carry the prediction by itself, and the service gap is hardly evidence that Bonzi cannot keep sets close.
Bonzi's serve can keep this close
Recent results offer Bonzi a firmer counterargument than the head-to-head does. Both players went 6-4 across their last 10 matches, and their recent hard-court records were identical as well. There is no form landslide. If Bonzi maintains his usual service protection, that parity leaves room for a match decided by a small number of return opportunities rather than a repeat of earlier results.
Bonzi also arrived at this round after beating Cameron Norrie in three sets in Lyon, while Paul had four days since his last match. That gives Bonzi immediate tournament experience, though the extra work could also become a disadvantage if this match extends. Neither consequence is established by the schedule alone. The concrete route to an upset is for Bonzi to hold consistently enough to deny Paul repeated return chances, then improve on his own recent breaking record. His latest win supplies evidence that he can finish a deciding set here.
The prediction
Court Shark's model favors Paul with a 76% win probability, compared with the market consensus of 72%. Both favor the same player. The difference is modest, and neither estimate turns the unbeaten head-to-head into a promise that the next meeting follows the same pattern.
Court Shark's AI analyst, which reads the matchup without the market, also picks Paul and agrees with the model. The tennis case for that choice is his current advantage on serve and return, supported by his previous results against Bonzi rather than resting entirely on them. The forecast's median total is 22 games, consistent with a competitive match that need not reach a deciding set.
Paul in straight sets is the model's likeliest single result, with the middle half of forecast outcomes spanning 18 to 28 games. Bonzi's task is specific: make his service games secure enough that Paul's better return record does not translate into a break in each set.
Ways to win
Article snapshot, Oct 20, 2026 · Not live
Every way the match can finish. The likeliest single result is Tommy Paul in straight sets (54%).
| Result | Chance |
|---|---|
| Benjamin Bonzi wins 2-0 | 12% |
| Benjamin Bonzi wins 2-1 | 12% |
| Tommy Paul wins 2-1 | 22% |
| Tommy Paul wins 2-0 | 54% |
Explore this matchup
Compare both players side by side: recent results, surfaces, serve and return.
Player comparison
Article snapshot, Oct 20, 2026 · Not live
Each measure on the same scale: recent wins, wins on this surface, head-to-head wins and the model's chance.
| Measure | Benjamin Bonzi | Tommy Paul |
|---|---|---|
| Wins, last 10 matches | 60% (6-4) | 60% (6-4) |
| Wins, last 10 on hard | 60% (6-4) | 60% (6-4) |
| Head-to-head wins | 0% (0-3) | 100% (3-0) |
| Model win probability | 24% | 76% |
Recent form
Article snapshot, Oct 20, 2026 · Not live
Each player's most recent completed matches, up to 10, oldest on the left.
| Player | Date | Result | Opponent | Score | Event |
|---|---|---|---|---|---|
| Benjamin Bonzi | Aug 26, 2026 | W | Rinky Hijikata | 6-1 6-1 | Winston-Salem |
| Benjamin Bonzi | Aug 27, 2026 | W | Botic Van De Zandschulp | 7-6(5) 6-4 | Winston-Salem |
| Benjamin Bonzi | Aug 28, 2026 | L | Ignacio Buse | 2-6 6-4 1-6 | Winston-Salem |
| Benjamin Bonzi | Sep 1, 2026 | W | Alex Molcan | 6-4 3-6 6-3 6-2 | US Open |
| Benjamin Bonzi | Sep 3, 2026 | W | Ignacio Buse | 6-2 7-6(4) 6-0 | US Open |
| Benjamin Bonzi | Sep 5, 2026 | L | Karen Khachanov | 3-6 2-6 4-6 | US Open |
| Benjamin Bonzi | Sep 30, 2026 | L | August Holmgren | 3-6 4-6 | Porto Monte Aventino CH |
| Benjamin Bonzi | Oct 12, 2026 | W | Hugo Grenier | 6-7(5) 6-1 6-3 | Roanne CH |
| Benjamin Bonzi | Oct 14, 2026 | L | Mika Brunold | 2-6 6-2 4-6 | Roanne CH |
| Benjamin Bonzi | Oct 20, 2026 | W | Cameron Norrie | 6-3 3-6 6-3 | Lyon |
| Tommy Paul | Aug 20, 2026 | L | Flavio Cobolli | 6-2 3-6 4-6 | Cincinnati Masters |
| Tommy Paul | Aug 30, 2026 | W | Coleman Wong | 6-7(3) 6-1 6-3 6-3 | US Open |
| Tommy Paul | Sep 2, 2026 | W | Dino Prizmic | 6-2 6-3 5-7 6-4 | US Open |
| Tommy Paul | Sep 4, 2026 | W | Alexander Bublik | 6-4 3-6 6-7(4) 6-1 6-3 | US Open |
| Tommy Paul | Sep 6, 2026 | L | Carlos Alcaraz | 4-6 3-6 4-6 | US Open |
| Tommy Paul | Sep 30, 2026 | L | Alejandro Tabilo | 1-6 2-6 | Tokyo |
| Tommy Paul | Oct 10, 2026 | W | Adolfo Daniel Vallejo | 6-2 6-2 | Shanghai Masters |
| Tommy Paul | Oct 12, 2026 | W | Valentin Vacherot | 6-4 6-2 | Shanghai Masters |
| Tommy Paul | Oct 14, 2026 | W | Zizou Bergs | 7-6(5) 6-4 | Shanghai Masters |
| Tommy Paul | Oct 16, 2026 | L | Daniil Medvedev | 3-6 6-1 3-6 | Shanghai Masters |
Win rate by surface
Article snapshot, Oct 20, 2026 · Not live
Share of matches won on each surface across each player's last 50 matches with full statistics.
| Surface | Benjamin Bonzi | Tommy Paul |
|---|---|---|
| Hard | 59% (19-13) | 63% (19-11) |
| Clay | 44% (4-5) | 75% (9-3) |
| Grass | 67% (6-3) | 75% (6-2) |
Serve and return on hard courts
Article snapshot, Oct 20, 2026 · Not live
How often each player held serve and broke serve on hard over their last 50 matches with full statistics, against the tour's all-years average on the surface.
| Measure | Benjamin Bonzi | Tommy Paul | Tour average, all years |
|---|---|---|---|
| Service games held | 83% | 84% | 77% |
| Return games broken | 23% | 22% | 23% |
| Matches in sample | 32 | 30 |
Model and market on Benjamin Bonzi
Article snapshot, Oct 20, 2026 · Not live
Benjamin Bonzi's chance as the market consensus priced it from the opening line, next to the Court Shark model.
| Reading | Benjamin Bonzi | Tommy Paul |
|---|---|---|
| Opening consensus | 28% | 72% |
| Latest consensus | 28% | 72% |
| Court Shark model | 24% | 76% |
Model win probability
Article snapshot, Oct 20, 2026 · Not live
The Court Shark model's chance for each player to win this match.
| Player | Win probability | Recent form (last 10) |
|---|---|---|
| Benjamin Bonzi | 24% | 6-4 |
| Tommy Paul | 76% | 6-4 |
How long it could go
Article snapshot, Oct 20, 2026 · Not live
A 58% chance the match lasts 18 to 28 games; 22 is the middle of the range.
| Total games | Chance |
|---|---|
| 13 | 0.5% |
| 14 | 1.4% |
| 15 | 3.3% |
| 16 | 5.2% |
| 17 | 7.8% |
| 18 | 8.3% |
| 19 | 8.7% |
| 20 | 8.0% |
| 21 | 5.4% |
| 22 | 7.8% |
| 23 | 5.7% |
| 24 | 1.1% |
| 25 | 3.1% |
| 26 | 4.2% |
| 27 | 2.7% |
| 28 | 3.2% |
| 29 | 3.4% |
| 30 | 3.4% |
| 31 | 3.9% |
| 32 | 3.8% |
| 33 | 2.4% |
| 34 | 1.7% |
| 35 | 2.3% |
| 36 | 1.4% |
| 38 | 0.5% |
| 39 | 0.4% |
Service games held: where they stand
Article snapshot, Oct 20, 2026 · Not live
Each dot is one of the ATP top 100 with enough matches in the last 52 weeks. Benjamin Bonzi ranks ahead of 32 of 94; Tommy Paul is 30th of 94.
| Player | Service games held | Place |
|---|---|---|
| Benjamin Bonzi | 79.8% | Ahead of 32 of 94 |
| Tommy Paul | 84.4% | 30th of 94 |
| Field median | 81.8% | |
| Field best (Jannik Sinner) | 94.6% | 1st |
Two years of form
Article snapshot, Oct 20, 2026 · Not live
Each player's pre-match Elo rating since Oct 23, 2024. Latest: Tommy Paul 2092 (Oct 16, 2026), Benjamin Bonzi 1888 (Oct 14, 2026).
| Player | Start of window | Two-year peak | Latest |
|---|---|---|---|
| Benjamin Bonzi | 1795 (Oct 23, 2024) | 1928 (Jan 18, 2025) | 1888 (Oct 14, 2026) |
| Tommy Paul | 2094 (Oct 23, 2024) | 2117 (Jun 3, 2025) | 2092 (Oct 16, 2026) |
Court Shark win probabilities are statistical estimates, not advice. No outcome is guaranteed.
Methodology and sources
How we build model estimates and where our information comes from.
Model estimates and observed results
The win probabilities come from the Court Shark match model, trained on completed ATP and WTA matches. A probability says how often a player in this position wins, not that one result will happen. The model's number for a match is recorded before play and never changed afterwards, so it can be checked against the result.
Sources and citations
Results, scores, rankings and serve statistics come from the Court Shark match database. The market consensus is the pre-match price for each player converted to a probability. Figures in this article are a snapshot taken when it was written.
Limitations
Serve and return rates count only matches with full serve statistics, which are sparser for Challenger and lower-level events, and the tour average they are compared with covers every year on record. Head-to-head records count every meeting with a recorded winner, walkovers and retirements included. Charts and tables are a snapshot and do not update after publication.
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