Ryder Cup: Head to Head Picks by the Golf Engine
We take a break from football to bring you a golf engine which uses 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 provides an opportunity to predict players that are due to go low.
The engine looks at how each statistical set 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 math engine, yet yields some objectively surprising results.
The United States carries a heavy advantage in the 2018 Ryder Cup as seen by the Las Vegas Odds. This is neither surprising nor out of the ordinary going into this event. The majority of the best players in the world, its professional tournaments and money in the sport come from the US.
The Europeans do however carry a lot of pride for inventing the game. And, tend to enjoy embarrassing the US on a semi-annual basis, regardless of how stacked the odds always seem against them.
We suspect this year will be no different, and in the end, it will be a very close and exciting tournament even though the US should walk-away cleanly with the Cup (spoiler alert - they won't, drama inevitably to ensue).
Should make for a fun weekend regardless as this is so-much-more than a golf tournament and there a nearly unlimited possibilities for prop-bets out there.
Head to Head Picks
Use the drop-down menu to select the individual US and European player and see the projected head to head match-up winner.
How the Golf Engine makes its picks
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 due to go low.
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.