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Mears: Building an Optimal DFS Model for the 2019 WGC-FedEx St. Jude Invitational

Here at FantasyLabs, we have a Trends tool that allows you to query tons of situations and see how they’ve historically led to DFS value. For example, you can see how a golfer has done at specific events when coming in with awful recent form or having never played the course before.

Using all of that data — specifically the data points in our PGA Models — we can see which metrics have been the most valuable for the St. Jude Invitational and then use that data to optimize a model for this week.

To measure value, we use a propriety metric called Plus/Minus. It’s simple: We know based on history how many DraftKings points a golfer should score based on his salary, and then we can measure his predicted performance above or below that expectation.

Building an Optimal DFS Model for the 2019 WGC-FedEx St. Jude Invitational

To build this “optimal” model, I backtested all the metrics in our Trends tool and looked at which ones have best predicted performance. For example, golfers in the top 10 percent in Long-Term Adjusted Round Score have historically outperformed expectations by over five fantasy points. Using data for the highest-rated metrics, I compiled weights for a model. The metrics listed below are those that tested 3.0 fantasy points above expectations.

Here at FantasyLabs, we have a Trends tool that allows you to query tons of situations and see how they’ve historically led to DFS value. For example, you can see how a golfer has done at specific events when coming in with awful recent form or having never played the course before.

Using all of that data — specifically the data points in our PGA Models — we can see which metrics have been the most valuable for the St. Jude Invitational and then use that data to optimize a model for this week.

To measure value, we use a propriety metric called Plus/Minus. It’s simple: We know based on history how many DraftKings points a golfer should score based on his salary, and then we can measure his predicted performance above or below that expectation.

Building an Optimal DFS Model for the 2019 WGC-FedEx St. Jude Invitational

To build this “optimal” model, I backtested all the metrics in our Trends tool and looked at which ones have best predicted performance. For example, golfers in the top 10 percent in Long-Term Adjusted Round Score have historically outperformed expectations by over five fantasy points. Using data for the highest-rated metrics, I compiled weights for a model. The metrics listed below are those that tested 3.0 fantasy points above expectations.