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One thing you never need to do when playing DFS is depend on too small of a sample size. Or do you?

If you’re entirely unwilling to position any faith in a small sample size, you’re prone to be left within the dust if what individuals are seeing is real. Furthermore, we don’t have time to attend to look if it’s real or not, as in baseball hitters are in the market each day and pitchers every fifth day. If the newly performing player goes to be nearly as good as he’s flashed, you’d better get in now before his price rises and your opponents catch on. Or if the old veteran ace is showing signs he could also be struggling, it behooves you to let everyone else continue to make use of him as he puts up ugly numbers.

But how can we differentiate between flukes and trends? And which numbers are we able to trust in small samples to assist us make that differentiation? Well those are the important thing questions that deserve exploring.

Differentiating between flukes and trends this early within the MLB season is naturally slightly tricky. Many odd things can happen in one month of baseball, so putting stock into everything you’re seeing is a huge no no. However, when you know which stats to seem for, you'll be able to possibly gain some insight into which early season trends is also signs of something to expect going forward.

Take Felix Hernandez, for example. After yesterday’s nightmare outing against the Oakland A’s his ERA jumped to 2.21. Before the outing, his ERA was within the 1s. Knowing that, you’d think he was a hot commodity in DFS. Not so fast. Most good DFS players or baseball handicappers are well aware that something is up with Felix Hernandez. Nearly each peripheral stat you take a look at paints the image of a man who's struggling mightily. His xFIP is at a career high 4.30. His K/9 is at a career low 7.12. The rate is a career low 89.7 average miles per hour on his fastball. The 8.4% swinging strike rate is a career low. So while he was sporting the ERA within the 1s, all of those other indicators aligned to turn a man who was in a decline phase or possibly isn’t fully healthy.

The same process can also be done when hitters. Recently, I wrote about Colby Rasmus and the way his approach seemingly did a 180 degree turn on the plate. Thus far this year he’s walking far more and striking out way lower than his career norms. His performance have been amazing. That’s the type of change you'll put some stock into. If a man is sporting a .437 batting average and has a .397 batting average on balls in play and his strikeout and walk rates remain as they’ve always been, who cares? We all know that he’s more likely to regress to the mean some and will rightfully just take that with a grain of salt like we should.

This is how one can use small sample sizes on your advantage in DFS. It's a must to look beyond the most obvious numbers like batting average and ERA and take a look at to get a feel for what the performance has looked like, not what the effects have been.

To relate it to poker, everyone knows that any two cards can win any given hand. That doesn’t make playing bad hands in suboptimal situations correct. It simply highlights the randomness involved. Sports are the similar way. Randomness abounds. Guys get hot. Guys get cold.

To predict what's going to happen successfully, we need to dig deeper and discover if what we’re seeing is real, or simply randomness happening. Sometimes a small sample size means nothing. Other times it may be the brand new normal.

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Thanks for reading. Find me on Twitter @IanJ300 with any questions.

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