The field for the 147th British Open is set at the historic Carnoustie Golf Links. The Golf Engine modeled over 1,500 statistics tracked by the PGA Tour for every tournament dating back to 2004. We looked at how each stat contributes to what we can expect from players on this stage, at this tournament. It’s a complex web of information that can only be properly analyzed by a machine, yet yields some objectively surprising results.

This year’s British Open is no exception as the model is calling for Webb Simpson (125/1 odds) to make a run into the top 10 at least.

Some surprises:

Back-to-back U.S. Open winner Brooks Koepka (22/1) inside the top 5.

Webb Simpson (125/1) and Phil Mickelson (66/1) inside the top 10.

Emiliano Grillo (100/1) inside the top 15.

Kevin Na (175/1), Luke List (125/1), and Ryan Moore (150/1) inside top the 25.

Perhaps just as surprising are the golfers that may under-perform this week. Rory McIlroy and Tommy Fleetwood don’t make the top 10 cutoff. Alex Noren, Francesco Molinari who finished T2 at TPC Deere Run last week, and Sergio Garcia are all projected outside of our top 25.

Notable left-outs:

Rory McIlroy (16/1) and Tommy Fleetwood (20/1) finishing outside the top 10.

Alex Noren (30/1), Francesco Molinari (33//1), and Sergio Garcia (28/1) all finishing outside the top 25.

A few more points of note:

Top 5

It’s fascinating that Dustin Johnson gets the call for top dawg from both the oddsmakers and the model. No question he is the best player in the world right now, but it’s been a few years since DJ really contended (2011) in this tournament — and at a different course — Royal St George’s. He does have a pair of Top 10’s in 2012 and 2016 and has made the cut every year since 2009 (his first Open).

Justin Rose, not that his name doesn’t come up every year for this tournament, just that his style of play is generally considered to be different than the players on either side of him (Johnson and Koepka).

Speaking of Koepka, few are calling for him to win at Carnoustie though he does shows up inside the top 5 here…

Jordan Spieth, although winning this tournament last year – has not put up the best numbers of his already memorable career the past few months. Frankly I’m a little surprised the numbers bear this out…

Perhaps the third least surprising name to see on this list (aside from Johnson and Rose) is Rickie Fowler, aka: Mr. Consistency, aka: the Perennial Contender, aka: always the Bridesmaid. Rickie almost always brings his A-game, and the data suggests it suits this course well. Curious to see if this is the year his major championship drought comes to an end.

Top 10

Webb Simpson might be the most surprising pick on this list. Clearly the model likes something about his game this year and the way he is set up for this tournament. A career-low 61 to open at The Greenbrier (his last start), T10 at the U.S. Open a month ago and earning his 5th career victory at The PLAYERS were each separated by missed cuts.

Top 25

For a guy with short odds, Rory McIlroy to be projected outside of the top 10, which really speaks to the consistency (or lack thereof) of his game this season.

Other notables:

No love from the model for Matt Kuchar, Scotsman Russel Knox, Adam Scott, Ian Poulter, or Louis Oosthuizen.

View the projected finish of the entire 2018 British Open Field.

How the Golf Engine makes its picks

In golf, a pro matches up as much with the golf-course as another competitor. Which is why any attempt to predict the outcome of a golf tournament, must take into account the nuances of the course. Beyond conjecture made by the golf pundits, analyzing past and present data through the use of math can more accurately project future performance.

In this model, we use machine learning to evaluate 1,500 different statistics for every golfer on the PGA Tour over each tournament since 2004. The analysis of this massive dataset allows gives us an opportunity to predict players that are sitting on low round scores.

The machine learns how these statistics can become a unique strength or glaring weakness for each golfer by comparing tens of thousands of different combinations and separating the patterns from the noise. The resulting ‘model’ is able to ‘deep dive’ and determine when to expect low rounds from a pro, given their unique style of play. These calculations are next to impossible to do quickly and certainly without personal and subjective biases, until now.

Learn more about the author, Pat Ross.