Saturday, February 24, 2018

What's The Common Thread Among League Winners?


Fantasy baseball is a difficult puzzle to solve. In theory, you have roughly an 8% chance of winning your league each season, assuming an even distribution of owner talent in a 12-team league. Even if you want to quibble with that back-of-the-envelope math -- whether it due to keepers, differing owner talent, etc. -- bump that number by 2x and you're still left with 16-17% odds. In other words, you're 5x more likely not to win your league than to win it. But, then again, I'm not telling you anything you don't know. And yet, doesn't it seem like the same set of teams are in contention each year? That thought provoked another similar line of questioning: among the top three finishing teams, what are the common threads or denominators among them? Is there anything structural or repeatable to employ into our own strategy and approach?

APPROACH

 To try and answer these questions, the first place I started was at the standings level. Are there certain categories that correlate stronger with total points than others? Specifically, I thought starting at the batting versus pitching level made more sense than correlating each category to total points. After all, your total points are a function of the batting and pitching points you accumulate. Through this process, I found batting points had an r-squared of 0.484 to total points, while pitching was 0.524. To me, this didn't appear to be anything ground-breaking, but did suggest there was a slightly stronger relationship between pitching success and overall success. What does that mean in terms of draft-day and in-season strategy tactics? Perhaps it doesn't change anything other than remind you that, despite the fairly typical 67/33 hitter/pitcher draft split, pitching still accounts for 50% of your success (perhaps more). Perhaps it suggests that you can differentiate your team through a stronger pitching approach. Let's get deeper into the numbers to see what specific categories tended to correlate more strongly with batting and pitching points, respectively.

BATTING POINTS

Starting on the batting side, RBI (0.416), runs (0.405), and batting average (0.365) correlated the strongest with batting points. Somewhat surprisingly, at bats (0.273) correlated stronger to batting points than stolen bases (0.198) and home runs (0.116). Based on these numbers, I'd argue that HR and SB are somewhat overrated going into drafts, and volume and batting average are slightly undervalued. Perhaps we should be paying more attention to likely batting orders and players who will be hitting 1-5, particularly on projected top 10 offenses. Health obviously contributes to racking up volume and ABs, but you could say that across all of this analysis. Lastly, SB and HR are categories and thus necessary evils, so to speak, but maybe we should pull back our obsession with them. Often player analysis begins with "he's projected to get you X SB + HR," but that conversation should arguably start with, of course, abilities of that hitter but then batting order position and the offense they play in.

PITCHING POINTS

On the pitching side, it's all about the ratios -- WHIP (0.761) and ERA (0.691). Pure innings volume (0.001) had almost zero relationship with pitching points as a whole. Of course, you still need saves (0.302), strikeouts (0.300), and wins (0.185), but different from hitting, it appears it's all about accumulating high-quality innings. There are a few more tactical takeaways here, as well. Saves had just as strong of a relationship with pitching points as strikeouts, and given that WHIP and ERA are so important, this may suggest that paying for good closers is a good strategy. You can't leave your draft without a plan to compete in saves. Wins are much dicier, and conventional wisdom may have this one right -- don't plan around wins. Given they're still a category and have a meaningful relationship to total pitching points, you can't ignore them, but I'll take better pitchers on worse teams if they're coming at a discount. Having said that, you need to be mining for the next 2016 Rick Porcello as well -- an inexpensive pitcher on a good team that could outperform expectations and accumulate a fair amount of wins. It's a balancing act here, but one thing is clear: you won't find me looking to grab inning eater "low floor" pitchers simply to grab volume -- in the deepest of "only" leagues, maybe, but not in deep mixers. Sign me up for high-end per-inning injury-risk guys like James Paxton and Lance McCullers all day long rather than inning accumulator types like Ervin Santana, assuming their price is right.

BRINGING IT TOGETHER

Looking at the top three teams across the last three years, the above seems to be fairly consistent with actual results. These teams on average finished 4-5th and 3rd-4th in batting and pitching points, respectively. The average finishes on the batting side are a little more confounding with the above regressions analysis, but still show the importance of balance across the categories:

Top 3, Batting Points, 2015-2017
AB BA HR Runs RBI SB
7 8 9 8 9 10

On the pitching side, it again appears that WHIP and ERA are kings, saves next, wins and K's to follow, and then innings last:

Top 3, Pitching Points, 2015-2017

ERA Innings K's Saves Wins WHIP
10 7 8 9 8 10
NEXT TIME

Hopefully this information is helpful on a more macro level. Through the next couple of pieces, I'd like to continue this analysis in a few additional dimensions:
  • Draft Structure: How do these top teams structure their benches? Do they take more chances on hitters or pitchers? Prospects?
  • Draft Equity: Are there certain positions and rank ranges that tend to have better ROI and lower bust rates? What is the relationship between draft equity and total points?
  • Keepers: Are these teams better with freezes/keepers and how are they getting them?
  • In-Season Management: What does their trade and waiver wire activity look like? 

Let me know additional key questions that could be insightful, I may just look into them.


Aaron Sauceda Web Developer

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