This article is part of our Umpire Analysis series.
In August of 2011, ESPN's Buster Olney was having a discussion on Twitter regarding which stats general managers use to make decisions when contemplating potential investments. At one point, Olney quoted an anonymous GM, who told him:
"I don't need stats that tell me what happened; I already know that. I need stats that tell me what's going to happen."
As the general managers of our daily fantasy teams, I feel that this is something we should take to heart. That's not to say we should completely discount what has already happened, but that we should look to combine a variety of methods in order to build a lineup that consists of the best players possible. In this week's article, we'll examine two metrics that forecast player performance in order to cultivate a method of selecting those who will be able to produce down the stretch in 2014.
Pitching:
xFIP (Expected Fielding Independent Pitching) is a statistic that attempts to measure elements that are within the pitcher's control, namely: walks, strikeouts, and home runs. The differentiating factor between this metric and FIP is that, here, we are attempting to neutralize the fluctuations of HR/FB ratio by taking the league average and multiplying it by a pitcher's flyball rate in order to get a handle on how many home runs he should give up going forward.
xFIP will not paint an accurate picture of every pitcher, as some guys seem to consistently give up or limit more than their fair share of homers. In general, however, this metric correlates very closely with future ERA, so when searching for that coveted value play, or trying to decide which starter to build a stack against, it may be a good idea to take a peak at those pitchers whose xFIPs and ERAs contain the biggest disparities. Conveniently, xFIP operates on the same scale as ERA, so knowing which players are ripe for the picking is as easy as knowing that Clayton Kershaw has been a dominating force this season.
For those brave souls who want to do their own calculations, here is the complete formula as derived by its creator, Dave Studeman of The Hardball Times:
xFIP = ((13*(Flyballs * League-average HR/FB rate))+(3*(BB+HBP))-(2*K))/IP + constant ((league-average FIP))-((League-average ERA))
Offense:
In daily fantasy play, lineup construction is almost entirely structured around players who can hit for power. The rationale for this is pretty simple: batters who can hit for extra-bases deliver the best promise of high point totals.
It is for this reason a stat such as ISO (isolated power) can be a useful tool when navigating the waters of DFS. When looking at ISO, we are seeing a picture of a hitter's pure power. This number can be arrived at easily enough, as its calculation is a matter of subtracting slugging percentage from batting average. By letting us know who is doing the most damage when they make contact, ISO allows us to see which players may be in line for a surge.
Interestingly, a study by Bill Petti for Beyond the Box Score found that ISO is actually more predictive than slugging percentage, the preferred metric used to measure power, on a year-to-year basis. It's also worth noting that ISO takes a while to stabilize in-season, but with everyday players closing in on 500 plate appearances for the year, now is an ideal time to start incorporating this data into team building. ISO operates a bit differently than some other stats we may be familiar with, as any number at or above .200 is a good indication you have a real slugger on your hands.
Using predictive metrics can be a great way to gain an edge on opponents when playing daily fantasy games, as the most commonly employed methods of research still include the surface stats we've come to regard as second nature. While there is no doubt that such stats remain useful for all players, taking a look at numbers that have predictive power as well can help us more accurately determine which players will perform as we head into the final two months of the season.
