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GPP Stacking w/ Park Factors MLB

GPP Stacking with Park Factors

GPP Stacking with Park Factors
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GPP Stacking with Park Factors

Welcome DailyRoto members to Park Factors: Week 2. I’m your host, Logan Hitchcock. If you were not able to catch my first piece of this segment, you can check it out here. For those of you who are just tuning in and are unwilling to go back and read it, I’ll begrudgingly provide a brief synopsis.

Each week this season, I’ll be partaking in a MLB DFS experiment centered on park factors. Unlike the other major DFS sports, the venue in which a major league baseball game is played has a large impact on the type of game; whether a slugfest or a pitcher’s duel, the ballpark has a significant influence.

To capture the significance of ballparks on both batter and pitcher performance, someone much smarter than I created park factors, a system designated to provide us with information in regards to player performance in a certain ballpark.

During each week, I’ll be using the park factors to create lineups in DraftKings GPPs and discussing both the impact the park has on lineup building as well as my performance as a player.

Week 2

Last week to get started, I used a general sense of park factors provided by ESPN. Sorting the ESPN park factor ratings for runs, I prepared teams from both the best and worst hitting venues.

This week however, my aim was at getting a bit more technical. Instead of using the generic ESPN park factor rankings, I moved up to the park factor big leagues. By using FanGraphs park factors sorted by handedness, I was able to create my own formula for a much more balanced park factor rating.

I’ve attached the table below, which includes the FanGraphs park factor ratings by handedness and some of my own mathematical calculations.

None of what I have shared above is any secret, so I’ll explain to you how I got to the “final column,” the column I used to determine the overall park factor rating for this week.

First, I knew I had to come up with some sort of average in order to incorporate all of the offensive statistics into the final category. To do so, I first averaged combined all non-homerun stats and took the average. Because homeruns are such a large part of Daily Fantasy baseball, I wanted the homerun ratings to carry a more significant weight than a ball park that caters towards singles or doubles.

After averaging the non-homeruns, I then averaged the homerun ratings. After averaging both, I put the averages together, and then took another average. Yes, I love averages. Now all the non-home run park factors combined have a 50 percent weight and homeruns by themselves have a 50 percent weight.

Finally, after all of the averaging, I simply used a conditional formatting tool to color code my results. The colors range from red, orange, yellow and green. Red being the worst, orange is the next best, followed by yellow and green. You’ll notice that Coors Field has a really nice green color, as we would have expected.

When it was all said and done, it was time to finally get to work on building teams for this week.

Below I’ve plugged in an example from Monday, April 13th.




On Monday, using the park factors that I had created by manipulating the FanGraphs handedness rankings, I was able to single out AT&T Park and Fenway Park as the worst and best hitting scenarios, respectively. Note: This was a short, early slate.

After determining which ballparks to use, I created teams solely isolating their respective ballparks, and entered them in the $1 GPP on DraftKings.

The first team, which finished 15th out of 191 teams was primarily a Red Sox stack with Bryce Harper mixed in. Due to the fact that it was a short slate, most “good” hitters carried a pretty significant ownership percentage. However, when comparing most of the Red Sox ownership to those from the Kansas City Royals who were facing an inferior pitcher in Trevor May, their ownership from the Fenway Park game was significantly less.

Although the Red Sox were playing in a better park, since they were facing a better pitcher, Jordan Zimmerman, less players used them in their lineups.

This is an important trend I hope to be able to track for the majority of the season. How frequently do we disregard park factors when a top pitcher is on the mound? It is not always the case that Clayton Kershaw is going to be incredibly dominant, so does stacking against him while he is at Coors Field make sense?

That will have to carry the “to be continued tag,” as we haven’t run into enough scenarios of the good pitcher vs. bad park situation.

Despite facing the better pitcher, the Red Sox exploded for nine runs on the back of David Ortiz and Mookie Betts (both approximately 11% owned – low for such a short slate), carrying my team to 125.80 points and a 15th place finish.

The other team, although made up of a potent Rockies offense, floundered in the spacious AT&T Park. The game ended 2-0, and about half of my total points game from my pitchers. Despite two subpar pitchers squaring off (Eddie Butler and Chris Heston) neither of these offenses could muster up much offensively and my team score supports that.

This is what I expected. Bad parks quickly kill DFS teams, even if there are runs scored, because typically, those runs aren’t coming via the homerun. If we’re looking to maximize our upside in GPPs we want to take advantage of players that are in good situations to hit homeruns and produce a higher fantasy point totals. Games in AT&T Park are not good for this. As a reminder though, I’m stacking teams in pitcher’s park to see if there is any sort of edge given the expected low ownership levels that could counteract the fact that we expect this stack to hit at a much lower rate than the hitter’s park stack.

While the games of the week overall went as I expected, I wanted to make note of one of the very important things that is changing as the season goes on.

DraftKings is fluctuating their prices on a daily basis to counter-attack the park shifts, opponent handedness and overall strength of the opposing pitcher. On given days this week, Mike Trout had an extreme park shift from his home park to Rangers Ballpark in Arlington. His price reflected this change and soared to over $6,000.

This is something to keep an eye on throughout the season, especially in the extreme cases. When teams flock to Coors Field, players typically want to target the hitters because of their exposure to a run scoring environment. However, DraftKings is continually going to make it harder and harder to put these guys in our lineup and nearly impossible to stack a full game. As a result of this, I might have to tinker the rules of my roster creations just a tad as the season progresses.

Overall, week two was a success for a variety of reasons. I was able to experience and evaluate the change in ownership levels based on the pitcher on the mound and compare it to the ball park, something that I’ll be monitoring all year, and also I gained experience in using hitters from the best parks, despite their increasingly rising salaries.

Below I’ve listed a table with the updated ROI for both week 2 and the total for the year.

Week Best Park ROI Worst Park ROI Total
Week 1 124% 1300% 433%
Week 2 567% -100% 207%

Thoughts on Logan’s experiment or have one of your own that you’d like to share?


GPP Stacking w/ Park Factors MLB

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