MLB Mobile Sports Betting Toolkit
Welcome to the second installment of Making Sense of MLB Stats. One of the hardest parts of MLB DFS is identifying which pitchers to select on a given slate. Some of the most common factors you may read are: K/9, K%, HR/FB, xFIP and many more. However, one very simple statistic that you can begin your daily research with is innings pitched.
I can hear the questions now, after talking about all the advanced stats we use, I bring up the importance of innings pitched. Before you close the article, note that I will discuss the advanced pitching metrics in another article but this will bring a new light into how you target and find incorrectly priced pitchers, or value.
Below, I will include three different graphs and explain the meaning and importance of each one. This should give you a solid baseline that will help you identify pitchers before you hone in on advanced stats.
This should come as no surprise to you – the more innings a pitcher throws the more strikeouts he will receive throughout the season. At the very basis, this seems like common knowledge, however, how many times do you ask yourself when you are selecting a pitcher how much sustainability or “innings pitched" does he have in him?
There is no arguing that there is a complete, positive correlation between innings pitched and total strikeouts. That means that innings pitched equals more strikeouts, and in DFS that means more fantasy points.
When you are targeting a pitcher, the easiest first step is to look historically at how many innings he pitches across the course of the season. This is an indicator of strength, talent and a predictor of more strikeouts.
This graph doesn't depict the complete obvious that the graph above does. Instead, this graph looks at a pitcher's historic amount of innings pitched versus the amount of strikeouts they record per game.
As you can see, innings pitched aren't only an indicator of season long strikeouts but also strikeouts per game. Having a statistic that essentially tells us which pitcher should record more strikeouts per game is an essential baseline to our DFS research. Note that I am not stating this is the only part of your research, I am stating that when selecting pitchers, looking at total innings pitched can help point you in a direction that leads to more strikeouts per game.
Before reading on, take some time to re-read and understand what this graph entails. It compares the amount of earned runs per inning pitched versus the amount of innings pitched a pitcher completes per game.
As graphed above, it isn't as correlated as the above graphs but it does show us a downward trend that promotes safety from pitchers who pitch more innings per game. This means that, not only do you gain more strikeouts long term by targeting pitchers who pitch more innings, but they also give up fewer runs in the innings they do pitch.
This is all makes sense when you look at it in this sense, but very rarely do we do so. Very rarely do we consciously target pitchers who pitch more innings per game or in the season. This is all done subconsciously, as these pitchers are typically our studs.
How Can We Use This Information
One of the best ways to utilize this information is in conjunction with the opposing team statistics. By targeting teams with low ISO or wOBA scores versus the handedness of the pitcher, we can then target which of our arms who pitch deep into games we will select.
Before you get into any of the advanced pitcher research such as K/9, K%, xFIP, batted ball profile or BABIP I suggest you do the following for pitcher research:
- Look at each pitcher's average IP/GM
- Look at the Vegas money line and total
- Look at opposing team's batted ball profile, ISO and wOBA versus handedness of pitcher.
This will establish a solid baseline for you to dig deeper into to truly understand the expected output, opportunity and risk associated with each of your pitchers.
In a future Making Sense Of MLB Stats article, we will target and explain how we use the advanced pitching metrics with what we have explained above.