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British Open Projections

The field for the 147th British Open is set at the historic Carnoustie Golf Links in Angus Scotland. We’ve modeled over 1500 statistics tracked by the PGA, for every tournament dating back to 2004 and 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 Ten at least. Some surprises: Back-to-back US 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 golfers that may underperform 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 show 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 US 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. About the Author Pat Ross - Contributor to National Football Post & sports nut with training in statistics, machine learning, and data analysis from Galvanize - Seattle campus. Alumni of University of Colorado and University of Washington. Occasional boater, skier, and golfer. The Golf Engine Description 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.
Projected Rank Player Odds
1 Dustin Johnson 12/1
2 Justin Rose 16/1
3 Brooks Koepka 22/1
4 Jordan Spieth 20/1
5 Rickie Fowler 16/1
6 Webb Simpson 125/1
7 Justin Thomas 22/1
8 Jason Day 33/1
9 Phil Mickelson 66/1
10 Jon Rahm 20/1
11 Henrik Stenson 28/1
12 Emiliano Grillo 100/1
13 Paul Casey 40/1
14 Patrick Reed 35/1
15 Rory McIlroy 16/1
16 Tommy Fleetwood 20/1
17 Bubba Watson 80/1
18 Tiger Woods 22/1
19 Kevin Na 175/1
20 Hideki Matsuyama 50/1
21 Bryson DeChambeau 125/1
22 Luke List 125/1
23 Ryan Moore 150/1
24 Tony Finau 100/1
25 Charles Howell III 500/1
26 Patrick Cantlay 100/1
27 Marc Leishman 45/1
28 Zach Johnson 100/1
29 Francesco Molinari 33/1
30 Brian Harman 150/1
31 Branden Grace 40/1
32 Pat Perez 250/1
33 Brandt Snedeker 150/1
34 Matt Kuchar 80/1
35 Chez Reavie 500/1
36 Jimmy Walker 250/1
37 Chesson Hadley 500/1
38 Rafa Cabrera Bello 125/1
39 Gary Woodland 250/1
40 Kevin Chappell 400/1
41 Xander Schauffele 150/1
42 Patton Kizzire 1000/1
43 Charley Hoffman 150/1
44 Brendan Steele 500/1
45 Byeong Hun An 200/1
46 Cameron Smith 200/1
47 Louis Oosthuizen 80/1
48 Ian Poulter 66/1
49 Charl Schwartzel 200/1
50 Adam Scott 125/1
51 Andrew Landry 500/1
52 Peter Uihlein 250/1
53 Kiradech Aphibarnrat 200/1
54 Tyrrell Hatton 40/1
55 Thomas Pieters 75/1
56 Bronson Burgoon 500/1
57 Satoshi Kodaira 1000/1
58 Kevin Kisner 400/1
59 Matt Jones 500/1
60 Retief Goosen 300/1
61 Russell Knox 66/1
62 Russell Henley 200/1
63 Jhonattan Vegas 750/1
64 Paul Dunne 150/1
65 Jason Dufner 250/1
66 Stewart Cink 250/1
67 Padraig Harrington 200/1
68 Anirban Lahiri 400/1
69 Jason Kokrak 1000/1
70 Austin Cook 500/1
71 Beau Hossler 250/1
72 Ernie Els 750/1
73 Keegan Bradley 300/1
74 Adam Hadwin 500/1
75 Daniel Berger 200/1
76 Abraham Ancer 1000/1
77 Matthew Fitzpatrick 60/1
78 Kyle Stanley 200/1
79 Dylan Frittelli 200/1
80 Jonas Blixt 500/1
81 Julian Suri 250/1
82 Kelly Kraft 1000/1
83 Michael Kim 300/1
84 Shane Lowry 150/1
85 Sergio Garcia 28/1
86 Ryan Armour 400/1
87 Shubhankar Sharma 500/1
88 Ryan Fox 125/1
89 Jazz Janewattananond 500/1
90 Alexander Levy 300/1
91 Matt Wallace 400/1
92 Ross Fisher 200/1
93 Matthew Southgate 125/1
94 Fabrizio Zanotti 1000/1
95 Danny Willett 150/1
96 Yuta Ikeda 1000/1
97 Martin Kaymer 200/1
98 Bernhard Langer 750/1
99 Cameron Davis 300/1
100 Lee Westwood 125/1
Data courtesy of Bovada.
Pat Ross
Contributor to National Football Post & sports nut with training in statistics, machine learning, and data analysis from Galvanize - Seattle campus. Alumni of University of Colorado and University of Washington. Occasional boater, skier, and golfer.

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