With Opening Day now out of the way – the Tigers beat the White Sox 6-3 this afternoon to make up yesterday’s rainout and wrap up each team’s first game of the season – and the majority of Tuesday’s games taking place right now as I type, now seems like a pretty good time to discuss what you, as both seasonal and daily players, should be looking for with regard to stats and trends as the season progresses over the next couple of weeks.
The most common phrase you’ll hear from fantasy pundits over the next month will be “sample size.” Baseball is a game steeped in statistics and the larger the sample size, the more accurate the data. It’s really as simple as that. If you hear a guy is batting .533 in the month of April, the first thing you do is see that he only has 15 at-bats. He’s not sustaining that pace. No one is. Give the guy 250 at-bats and if he’s still hitting .533, well that’s a different story. He’s obviously the reincarnate of Ted Williams
Conversely, the same thing can be said about a guy hitting .063 over those same 15 at-bats. A player can certainly open the season ice-cold, but the law of averages says that the numbers will regress to the mean and with more at-bats under his belt, his batting average will normalize. If it doesn’t, then drop him like a hot rock because this guy totally sucks.
With all of that said, you need to start looking at what is “the mean” for your players in a number of statistical categories to determine whether he is on pace for his usual numbers or if he is playing far above or below his expected rate of production. I’m a big fan of using three-year averages, obviously calculating the player’s last three years, but keep in mind, if you’re dealing with an injury-prone player, you may have to include a fourth or fifth year to get a true look at what is average for him.
Now that may sound like a lot of work, but in truth, you can pretty much eyeball it if you’re looking at a player’s career statistics. The hardcore mathematicians may want to slap me across the face for such blasphemy, but not everyone has the time, the patience or the acumen to figure out the exact numbers. If a guy is batting .162 in the month of April but has hit somewhere between .275 and .295 in each of his last three seasons, guess what…? Get him! Buy low! Do it! Unless he just flat-out forgot to play a game he’s being paid millions of dollars a year for, he’s about to go on quite the hot streak. You don’t need to be a genius to figure that out.
I’m only using batting average as an example here, though. Yes, it’s a statistic used in fantasy leagues, but it’s really not a strong indicator of a player’s performance. There are a number of stats which will serve you a lot better if you follow the trends and use that as a determining factor of whether to buy, sell or hold a player. Again, you don’t have to know exactly how these stats are calculated. You just need to know what you are looking for with respect to league averages and individual player trends.
Here’s what I like to use:
Batting Average on Balls in Play (BABIP)
It calculates how often a non-home run batted ball falls in for a hit and reads just like batting average. League-average is right around .300 so you’re obviously looking for players who hit well-above that mark. If you look at a player’s BABIP over the last three years and see it hovers around .320, you know that an April BABIP of .385 indicates that he is playing above his level. You can probably expect that number to come down which means a cold streak is coming. The opposite rings true if his BABIP is .235 for the first month of the season. You can also use this as an indicator for pitchers. If the BABIP for a pitcher is normally around .290 and here in April it’s .345, you can assume that he’s been extremely unlucky and too many balls are falling in for hits. If his defense is usually solid, you can surmise he’s been unlucky and expect the balls to bounce in his favor a lot more often moving forward.
Weighted On-Base Average (wOBA)
This is the granddaddy of all stats for me. It’s the premier measuring stick for a hitter as it encompasses all the aspects of batting average, on-base percentage and slugging percentage. Again, the calculations are beastly, so don’t sweat it too much. Just know that league average sits somewhere around .320 and you are looking for guys with a mark that is higher than that. Again, look at the last few seasons to get an idea if he is playing above or below his normal rate and follow the same advice I laid out above with regard to BABIP. This number is also used as an “against” number for pitchers, so if we’re talking DFS, if lefties have .412 wOBA against a particular pitcher, you know to stack a bunch of them in your lineup. Just make sure that the .412 mark is legit, so look at the pitcher’s three-year trends before you bet the farm against him.
Line drive, ground ball and fly ball rates (LD%/GB%/FB%)
Batted ball statistics are fantastic for both hitters and pitchers. Strong line drive rates are great for a hitter, but bad for a pitcher as most line drives tend to fall in for hits. Somewhere around 21-percent is league average, so you know what you’re looking for here without me having to explain it, right? Groundball rates, on the other hand, are fantastic for pitchers, but not so hot for hitters. If you’re looking at a pitcher with a 50-percent or higher ground ball rate, he should be a solid choice should the defense behind him remain strong. Hitters with a high ground ball rate (anything above 45-percent) aren’t who you want, unless they have blinding speed to leg them out. As for fly balls, you also have to factor in the ballpark dimensions and whether the guy is a true home run hitter. Big mashers tend to have a high fly ball rate which is why so many people have questioned Christian Yelich’s power potential. His fly-ball rate stinks. For pitchers, a high fly ball rate is risky, obviously. Overall, I tend to use LD% and GB% more when I’m looking for developing trends and making comparisons to three-year averages. With regard to home run hitters, you have to look at their HR/FB rate as well to get a better idea.
These are the main ones I use to determine whether a player is expected to break out or fall apart. There are a ton of other metrics I like to use such as weighted runs created plus (wRC+), isolated power (ISO), strikeout rates, walk rates and even a variety of swing rates. Again, I’m less interested in how exactly the numbers are calculated and more concerned with how this year’s numbers match up with last year’s. Once we have a few more weeks under our belts here, we’ll be able to cite specific players and their trends. Until then, enjoy the first week and don’t freak out just yet. We’ve got a ton of baseball ahead of us.