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Strategy for DFS Fantasy Baseball
Daily fantasy sports (DFS) have been rapidly gaining popularity over the last few years. Most likely, more people will participate in daily MLB contests this season than in any previous one. We live in a culture obsessed with instant gratification. If you play in any free standard fantasy baseball leagues, you’ll probably notice that a sizeable portion of the league participants will end up neglecting their team for large chunks of the season. Most casual fantasy players aren’t interested in committing to their team for six months of their lives, especially when they fall out of contention. However, it’s much easier for someone to commit to setting their lineup for one day, and the potential to “win” something at the end of that day dramatically increases the appeal of DFS to casual fantasy fans.
Long story short, DFS and daily fantasy baseball is here to stay for the intermediate future. As more “casual” fans begin participating in the game, it’ll be easier for knowledgeable players to win daily contests (i.e. win cash-money). Your “edge” against the field in these daily contests will increase as the knowledge gap between you and your opponents widens. Essentially, there are two possible ways to increase your expected performance in these contests: 1) play against less-skilled opponents or 2) become more skilled. Anyone can become better by continuing to collect more information on succeeding in daily contests and this is where RotoBaller comes in.
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How to Select your DFS Lineup
When you enter a DFS contest, your goal is to create a lineup that will produce the maximum number of points within the contest’s salary cap constraint. The salary cap will prevent you from selecting the best players at every position. Thus, you must strike an appropriate balance between your players’ “cost” and their expected production.
You should try to uncover and exploit any “market inefficiencies.” A market is inefficient when the “price” of its asset differs from their actual value. Similarly, the DFS market is inefficient when the players’ salaries inaccurately reflect their expected production.
My next few articles will introduce my recommended approach for selecting hitters and pitchers and explain important considerations for finding “bargain” players. First, let’s take a look at how most players fill out their DFS rosters and why the process is greatly flawed.
The Common Haphazard Approach of Casual Players
Aside from salary, most casual players look at two primary factors to evaluate players: 1) Points Per Game (PPG) and 2) matchups.
The Value of PPG
PPG can provide a solid starting point to your player analysis in many instances. However, a multitude of factors can create deceptive PPGs. This is especially true at the beginning of the season. The phrase “small sample size” has become pervasive throughout baseball, especially in the advanced analytics and sabermetrics communities, but it’s an extremely relevant consideration when constructing a team. Players’ PPG will have little predictive value in the first couple of months of the season. It’s much more useful to look at a player’s historical numbers (such as their previous three-year average) than their performance over 15 to 20 games. Consider the cautionary tale of Chris Shelton: he hit 9 homeruns in the first 13 games of the season for the Tigers in 2006, but he was shipped to Triple-A in July of that year. This is an extreme example, but it illustrates how any player can look like a stud over a short period of time.
Assessing Matchups
The most common way for casual players to evaluate a hitter’s match-up involves looking at the opposing starter’s ERA. Like PPG, this is an okay starting point to your analysis, but you should dig deeper. ERA is often deemed a flawed stat because there is a large “luck” component for pitchers (“luck” is an all-encompassing term for any factors beyond the pitcher’s “control”). Because of the “luck” factor, ERA often does not accurately reflect the pitcher’s performance. The reliability of ERA and the use of other ERA predictors will be discussed in later articles as well, but just like PPG, the utility of the statistic is a function of the sample size. Additionally, ERA (also like PPG) will include factors not directly relevant to the match-up you are analyzing.
Wouldn't it be more beneficial to only account for the most applicable information? Of course. Accordingly, it’s useful to attempt to isolate the most relevant data. Aside from quality of opponent, here are three other matchup factors that deserve your attention: 1) splits by handedness, 2) park factors, and 3) home/road splits. I believe home/road splits and park factors are strongly interrelated; so I’ll just briefly discuss “park factors” here.
Splits by Handedness
For example, if you’re evaluating a hitter who’s facing Bronson Arroyo and his respectable 3.79 ERA in 2013, the handedness of the hitter is a crucial consideration. Left-handed hitters (LHH) have been significantly more successful against Arroyo throughout his career:
| AVG | OBP | SLG | HR/9 | |
| LHH | .285 | .341 | .490 | 1.60 |
| RHH | .231 | .287 | .378 | .92 |
Consequently, Arroyo’s 3.79 ERA actually suggests a fairly difficult matchup for RHHs and a quite favorable match-up for LHHs.
This information is also useful if you’re considering adding Arroyo to your own squad. If he’s facing an average offensive team with eight RHHs in their starting lineup, he’s probably a relative “bargain” for his salary. Here, Arroyo would be expected to allow fewer earned runs than he would against an average offense with only five RHHs. Moreover, if Arroyo allows less earned runs, he’s likely to pitch more innings and increase his probability of earning a “win.” Preventing earned runs, accumulating IP, and getting a W are key ingredients for a pitcher to be successful on Fanduel or DraftStreet.
A word of caution about platoon splits: splits by handedness can vary greatly from year to year due to small sample sizes (plate appearances). Accordingly, you shouldn't assign nearly as much meaning to the splits of a first or second year player as you would to a veteran. When in doubt, simply remember that pitchers benefit a bit from facing a batter of the same handedness while batters benefit from facing an opposite-handed pitcher.
Park Factors
When considering the “matchup,” you should look at more than just the opposing players. Park factors often influence the expected value of both hitters’ and pitchers’ performances in a meaningful way.
Let’s stick with Bronson Arroyo. He is a flyball pitcher who is prone to giving up homeruns. Naturally, a hitter facing Arroyo in a homer-friendly park (like Citizen’s Bank Park in Philadelphia) would be a much more attractive option than the same batter facing Arroyo in a homerun-suppressing stadium (like AT&T Park in San Francisco). Later in this series, we will look at the most pitcher-friendly and hitter-friendly parks. Whether you’re evaluating a hitter or a pitcher, you should make adjustments based on the relevant venue.
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Conclusion
I wish I could provide you all with a simple, mechanical system for creating an optimal DFS roster. Unfortunately, the analysis is highly contextual. This means that it’s borderline impossible to construct the perfect roster on a regular basis. But you don’t need the perfect lineup to be successful. You just need better lineups than most of your opponents. Over my next few articles, I’ll identify some more common pitfalls to avoid. I’ll also discuss some of the most often overlooked and valuable factors in building a successful team. The next few articles should be much more focused and less abstract. I’ll be on the RotoBaller chat quite a bit so don’t hesitate to shoot me a question. Feel free to recommend any potential future article topics that interest you.
Craig’s Cliff Notes (TL;DR)
- DFS are increasing in popularity and more casual fans are regularly entering these contests. This will weaken the competition and increase your odds of success.
- The salary cap requires you to balance players’ expected production with their costs; thus, it’s important to roster “undervalued” players.
- Don’t assume that a player’s average PPG is predictive of their future performance, especially early in the season.
- A pitcher’s ERA does not always indicate the favorability of a hitter’s matchup, but there is some correlation.
- Look at platoon splits when evaluating a pitcher or a hitter. As a rule of thumb, remember that generally pitcher’s benefit from facing batters of the same handedness, while hitters benefit from facing an opposite-handed pitcher.
- Park factors should be considered during your roster evaluation.
Just remember that PPG provides little-to-no value in the first month or two of the season. You should be especially suspicious of players who are comfortably outperforming their previous years’ numbers.
