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GPP Stacking w/ Park Factors

GPP Stacking with Park Factors

GPP Stacking with Park Factors
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GPP Stacking with Park Factors

Good morning DailyRoto members! Welcome to another installment of “GPP Stacking with Park Factors.”

If you are reading this for the first time or just want to refresh your memory on the previous installments, you can go back and read them by selecting the “Park Factors” subcategory from the “MLB FREE” drop down menu.

If you are too stubborn to look back, I’ll briefly explain it for you. Each week at DraftKings I stack teams in a GPP based on park factors. Park factors are a relative rating scale of major league baseball parks and their aptitude for offense, or the lack thereof. Each week I monitor the trends of the previous week and look to explore any inefficiencies or trends that appear.

From the park factors that I’ve included below based on a manipulation of the FanGraphs park factors with handedness, I’ve been creating teams from the best and worst parks on a given slate.

Also, to make it easier on you guys, in case you want to use the spreadsheet for your own research, I recopied the team name from the first column and pasted it along side the final rankings. This is way easier than scrolling all the way across all of the columns. I’m sorry, I should have done this 4 weeks ago.

In the last few weeks, I’ve been focused on making some minor adjustments to the teams I’ve created. I’ve been more conscious of the common sense matchups in a given game and I’ve also been mindful of the pitching matchups instead of just finding a decent arm with a fitting salary. I kept that in mind again this week in my team building.

As is customary, I’ve included a pair of my contrasting teams in one of the GPPs from this week.



Normally I would pick things about these two teams and focus on what went right, and what went wrong. This week however, I want to set my analysis in a slightly different direction, and even take a few steps back.

I’ve been so focused this season on producing the teams and waiting for the “payout,” that I’ve lost focus on an underlying theme that carries a lot of weight. Each week at the very bottom I include an updated ROI sheet for all of the respective categories, but I’ve never focused on “points scored.” I’ve frequently compared ownership percentages and ROI, but never points scored.

You might be saying, “well, isn’t points relative?” To that I would say, “yes, sort of.”

The point totals that are required to sneak inside the cash line do change from night to night, that is the beauty of DFS. However, after enough game play we can start to gauge a range of scores that a team needs to score in order to do so.

This week I want to focus on the discrepancies in the points I’ve been scoring, and comparing and contrasting the point totals of the worst ballpark and the best ballpark.

In the example above, the point differential isn’t much. The “worst park” team actually outscored the “best park” team by about 18 points. This largely hinged on the impact of the pitching that I selected. I picked two pitchers from poor offensive environments (I know this is ironic because that is actually a good thing for pitchers, but I’ve paired it with the “worst park” team) that had great nights and pushed the team into a minimum cash.

Because naturally we expect more from the “best park stack,” I was interested to go back and compare the scores I’ve been posting from the whole season, because obviously one night won’t do the trick.

Be aware though that we are still only six weeks into the season and on a given week I only get a chance to play three or four stacks (it varies based on my availability and the slate) so the sample size is still quite small as a whole.

Stack High Low Average
Best Park 158.8 53.05 108.16
Worst Park 161.15 38.15 98.87

Note: These averages are including games from April 20th on.

A few things stick out after scanning through the results. The best park is doing better, and doing so consistently, averaging nearly 10 points higher per game. If you throw out the extreme low of 38.15, the average jumps up to 118.19, a full 20 points higher than the worst park average.

I wanted to include the high and low scores to show the volatility of stacking. If things go right, you can end up punching through the field to the top, like I did when I put up a 161.15 in the worst park of the night. You can also get completely wiped up by the competition and fall flat on your face with a 38.15 from the best park.

This is what I expected and what I’ve hypothesized all season long. The best park is consistently producing higher scores, and as a result cashing more frequently – but interestingly with a lower ROI.

However, the worst park, while producing a lower average score, produces a larger ROI when you do hit the bigger score, thanks in part to the low ownership levels that are attributed to the players in bad ballparks on most nights.

I’ll be following and monitoring the points scored by the respective teams even closer in the coming weeks, and even comparing them to the cash line to see where we might need to improve, or if the GPP stacking is par for the course.

I’ve updated the ROI table below.

Here’s to next week!

Date Worst Park ROI Best Park ROI Total
Week 6 -100% -33.33% -66.67%
Year to Date 286.45% 242.42% 258.73%

GPP Stacking w/ Park Factors