Expectation and reality part company at the U.S. Open
Each June, the U.S. Open arrives as a test not merely of skill but of humility — a reminder that the game's most demanding stage has a way of reordering expectation. At Shinnecock Hills in 2026, Scottie Scheffler pursues the last major that would complete his legacy, while a predictive model built on seventeen correctly forecast championships quietly suggests the leaderboard will look nothing like the oddsmakers imagine. In the tension between human ambition and algorithmic probability, the course itself remains the final arbiter.
- Scheffler carries the weight of a Career Grand Slam on his shoulders at plus-550, making him both the favorite and the most scrutinized player in the field.
- Jon Rahm, third in the betting market and a former champion at this very event, is flagged as a fade — his major record since 2021 offering the model too little to trust.
- Cameron Young, a 72-to-1 longshot with no major title to his name, is projected as a genuine top-five contender based on driving metrics that suit Shinnecock Hills' demands.
- A model that has correctly called seventeen majors ran ten thousand simulations and found a tournament likely to diverge sharply from public expectation — with at least one 75-to-1 shock pick lurking in the full projection.
The 2026 U.S. Open opens Thursday at Shinnecock Hills in Southampton, New York, with a field carrying fresh momentum: Rory McIlroy won the Masters, Aaron Rai took the PGA Championship, and Brooks Koepka — who conquered this same course in 2018 — is back. Defending champion J.J. Spaun is also in the field. The stage is loaded.
Scottie Scheffler enters as the favorite at plus-550, one major win away from completing his Career Grand Slam. McIlroy sits at plus-1200, chasing his first U.S. Open title in fifteen years. Jon Rahm, the 2021 champion, is third at plus-1300. Further down the board, Cameron Young sits at plus-2200 — a number that, on the surface, reflects his lack of major victories.
A predictive model built by DFS professional Mike McClure has correctly forecast seventeen major championships, including five consecutive Masters and the two most recent majors. After running ten thousand simulations of this week's field, its conclusions diverge meaningfully from the market. Rahm, despite his pedigree at this event, is projected to finish outside the top five — his U.S. Open record since 2021 offering little to justify confidence, even with a recent top-five at the PGA Championship.
More striking is the model's embrace of Cameron Young. His driving profile aligns well with what Shinnecock Hills historically rewards, and his 2026 season — two wins, six top-tens, a tied-third at the Masters — suggests a player in form. The model recommends him across win bets, top-five wagers, and fantasy lineups alike. At least one 75-to-1 longshot also appears in the full projection, a quiet signal that this Open may once again remind the field, and the bettors, that the course tends to have the last word.
The 2026 U.S. Open arrives Thursday morning at Shinnecock Hills in Southampton, New York, carrying the weight of history and the hunger of a field that includes two of this year's major winners. Rory McIlroy claimed the Masters. Aaron Rai took the PGA Championship. Both are here. So is J.J. Spaun, defending his title, and Brooks Koepka, who won this very course in 2018 at one over par. The stage is set for another chapter in one of golf's most demanding narratives.
Scottie Scheffler enters as the betting favorite at plus-550 odds, chasing the one prize that would complete his Career Grand Slam. McIlroy, seeking his first U.S. Open in fifteen years, sits at plus-1200. Jon Rahm, the 2021 champion, is third at plus-1300. Behind them, the field stretches out in descending order of expectation: Xander Schauffele at plus-1600, Tommy Fleetwood at plus-1800, Matt Fitzpatrick at plus-2000, and Cameron Young at plus-2200.
But expectation and reality have a way of parting company at the U.S. Open. A computer model built by DFS professional Mike McClure has spent the past several years proving this point with remarkable consistency. The model has correctly predicted seventeen major championships entering the weekend—five consecutive Masters tournaments, last year's PGA Championship, last year's Open Championship, and the 2026 Masters just weeks ago. Anyone who followed its picks has seen substantial returns. Now, with the 2026 field finalized, McClure's model ran ten thousand simulations of this week's tournament. The results contain surprises.
The model suggests that Rahm, despite his favorable odds and his history at this event, will stumble. It projects him to finish outside the top five. Since his 2021 victory, Rahm has not finished better than tied for seventh at the U.S. Open. His recent form includes a tied-for-second finish at last month's PGA Championship, but that marks his first top-five in a major since 2023. The model sees insufficient evidence to back him as a winner this week.
Meanwhile, Cameron Young emerges as a top-five contender in the model's projected leaderboard—a striking call given his plus-2200 odds and the fact that he has never won a major championship. Young has recorded two victories and six top-ten finishes this season, including a tied-for-third at the Masters. His driving metrics, the model reasons, align well with what Shinnecock Hills demands. He is a golfer to back in win bets, top-five bets, and daily fantasy lineups.
The model has also identified several longshots worth considering, including one shocking pick sitting around seventy-five-to-one odds. The full leaderboard projection and complete betting recommendations remain available through the model's platform. What emerges from ten thousand simulations is a tournament that may not unfold as the odds suggest—a reminder that golf's major championships have a way of humbling conventional wisdom, and that the courses themselves often have the final word.
Notable Quotes
The model simulated the tournament 10,000 times, and the results were surprising— SportsLine reporting on the predictive model's findings
The Hearth Conversation Another angle on the story
Why does a model that's been right seventeen times suddenly matter more than the odds themselves?
Because the odds reflect what people are betting, not what's likely to happen. The model reflects what actually happens when you run the math ten thousand times.
But Jon Rahm won this event five years ago. Why would he fade now?
Because he hasn't finished in the top five at a major since 2023. One good result doesn't erase a pattern. The model sees the pattern.
And Cameron Young—he's never won a major. Why would the model trust him here?
His driving is elite, and Shinnecock Hills punishes poor driving. Sometimes the course itself tells you who can win, if you listen to the right metrics.
So the model is saying the favorites are wrong?
Not wrong. Just incomplete. Favorites are built on reputation and recent form. The model is built on what actually happens when you simulate every possible outcome.
What happens to Scheffler in these ten thousand simulations?
That's the question everyone's asking. The model keeps its answer close.