Punting categories is a fun topic to discuss in the fantasy baseball community. Of course, it sounds great on the surface! And when you can tell a friend that you punted a category and finished in the money because of it, that makes you feel like a pretty cool dude.
Why doesn’t everyone just punt categories if it’s so successful?
Well, think about ‘punting’ from the real life football perspective. There are situations where you know you shouldn’t punt: 1st, 2nd, and 3rd down. Then, when it comes to fourth down, lots of variables go into whether or not you should punt. Those can vary from field position, distance to gain, and game flow.
In fantasy baseball, we want to know which categories are the ‘fourth down’ type of categories. Then, from there, we want to determine whether or not it would be a situation where we should punt or go for it. However, what differs here is that punting is the conservative thing to do in football.
On that note, I want to preface this by saying that this is not an opinionated article. Instead, it’s one to be taken in an informative manner. I’m simply providing the details outlining what I would do if I were to punt a category. So don’t blame me if you punted a category and didn’t have success!
Without further delay, let’s hop into this case study, shall we?
I decided to use the Depth Charts projections for 2017 to create an Excel workbook with one tab for offense and another for pitching. It’s an imperfect strategy and if I had more time I would use stats from like the past five years or something. However, I figured it would be nice to go with the projections for this season considering it’s a much different league now than in 2010.
The R-statistic helps us correlate two categories to each other. This tells us how much of an impact one stat will have on another stat. For example, we expect HR to have a bigger impact on RBI than on runs because the maximum amount of runs you can get from a HR is 1. Easy enough, right? Each correlation coefficient is less than 1. The closer the coefficient is to 1, the more related the two stats are.
When all of the coefficients are found for each combination of categories, add them together to find total categorical coefficients. What I also wanted to do was show how those total coefficients change when removing a category that one may consider punting.
If the summation of the coefficients is larger with four categories than the full five, then it is a worthy category to punt.
Results – Offense
I narrowed down the projections to the top 250 fantasy-relevant players for the 2017 season. I mainly wanted to include players who are expected to play 75+% of the time.
These relations shouldn’t be shocking to the average baseball fan. RBIs and homers show strong correlation, which points to three-, four-, and five-hole hitters. Average has its highest relationship with runs, which is what you want your leadoff and second-batter to possess. Stolen bases are the obvious outlier in this chart.
How does the chart look if we exclude steals…
The total correlation coefficient increased by 0.64, which supports the theory that steals is a good category to punt. Notice that the increase in correlation between HR and RBI far outweighs the downgrade in runs and AVG.
Not Your Average Category
Some may consider average a category to punt. Drafting the Billy Hamilton’s and Chris Carter’s of the baseball world could lead to easy counting stats, right? On the surface, I must admit that it does sound like a decent method.
However, after further reflection, I can’t recommend this strategy. For the sake of argument, let’s say that you are a contending team halfway through the season. Usually, the bottom two or three teams realize that they have no shot and give less effort. Their lineups end up having players that are hurt or losing playing time in some fashion. Ultimately, they are losing volume, which leads to lower counting stats. This lack of awareness by the owner does not change his team’s batting average.
So while the conceding teams are falling down the rotisserie rankings, it’s not because of their batting average. Therefore, I argue that it’s harder to catch up to these teams if you are chasing their average instead of their counting stats. It’s the only ratio in the offensive categories – don’t screw it up!
Results – Pitching
I took the top 140 starters and 35 relievers together based on ability and relevance. So yes, I had to include closers that are just awful (looking at you, Brandon Kintzler). Note that if your league has designated SP and RP spots, the pitching side of this study is not as important. This applies to the leagues that have generic pitching slots that allow you to mix and match starters and relievers.
Again, the connections here make plenty of sense. Wins and strikeouts are highly related because the starters who are getting high volume strikeouts are more likely to win games than relievers. ERA and WHIP are best buds – limiting baserunners leads to limiting chances for runs, plain and simple. Saves are the largest outliers here since they negatively correlate with each of the other categories.
What happens if we punt saves…
The total coefficient increases substantially. This is largely due to the volume that starting pitchers have more strongly affecting the other four categories.
However, be careful here! ERA and WHIP have higher coefficients without saves in the equation, but that doesn’t necessarily lead to better ratios! Having to start the 8th and 9th best pitchers on your roster in lieu of two relievers could lead to more volatility. You may be forced to start a fringe guy in a tough matchup, leading to blowups and directly impacting your ratios in a horrendous way. That’s a great segue into my next topic…
The Andrew Miller Theory
Miller went in the 8th round of the FSTA Experts Draft in January and it baffled me. He was the sixth reliever selected and the 28th pitcher taken overall. I immediately thought ‘well, if he isn’t closing or starting, how much can he really contribute to ERA/WHIP/K to be helpful?’
Drafting Miller is very intriguing if you are punting saves. While most teams are deploying two closers a week to keep up with the crowd, you can get away with throwing a guy like Miller in your 9th pitching slot.
He is so damn good that he affects your ERA and WHIP more positively than a 3.50 ERA starter that has a bad matchup. As a quick example, Miller had just 44 less strikeouts on the season than Jerad Eickhoff in 123 less innings (!) in 2016. Coincidentally, he was only one win off Eickhoff’s season total too, which attests to Miller’s ability to pitch multiple innings and accrue wins himself.
Having Miller as an every week stalwart in your P9 spot is defintiely a viable option at the right price on draft day. If you are shopping for the Great Value brand of long relievers, check out Chris Devenski, Matt Andriese, and Brad Hand.
If you are punting categories, no matter if it’s an H2H or rotisserie format, you must dominate in the other categories. That’s fine in H2H, as you are competing in the other nine categories against just one person each week. Your odds of wining five or more categories of those nine are excellent if you drafted well and are diligent in waiver adds.
It’s a little different in rotisserie formats. Hypothetically, let’s say the season long total you shoot for is 95 to win your 12-team league. Divide that by 10 categories and you get a 9.5 average, essentially shooting for third or fourth in every category when drafting. If you are punting a category, you will post a 1 in that column, leaving you with 94 points to gain in nine categories. That leaves a 10.4 average, essentially forcing you to finish second or third in all your remaining stats.
It’s doable if you kill your draft, but it’s not ideal to leave yourself with a 1-spot. Make sure you have an exact plan in your draft like the Andrew Miller Theory. Even then, you need almost everything to go right between the other nine categories to ensure success.
Better Punting Option – Steals or Saves?
Well, this is an entirely new case study in itself. I will give you the Cliffs Notes version of my research.
I analyzed NFBC ADP and added up how many steals and saves per round based on Depth Charts projections. Then, I graphed the two together and showed trend lines to see the general trends followed in a draft. The chart on the right displays the results (open in new tab to enlarge).
Following the chart, here’s what happens if you punt stolen bases:
- You attack starting pitching and power hitting in the first five rounds.
- You will be ready to draft an elite closer or two above average closers in rounds 6 through 10. However, steals drop off, so the rest of the owners will be looking to draft a closer too.
- There are 10 closers you target, but with 12 owners looking at that same pool, you probably don’t get two of your targets unless you reach.
On the other hand, if you punt saves:
- You start your draft with starting pitching and all-around players in the first five rounds. Perhaps you target a Starling Marte or Jonathan Villar type of player to get a head start in steals.
- Steals drop off and all the owners are ready to draft closers. However, you use these rounds to ensure your HR-RBI stats are on schedule and continue to build starting pitching.
- You draft extra targets for stolen bases later on like Kevin Kiermaier or Rajai Davis to build speed.
As you can probably tell, if you are dead set on punting one, I am an advocate for punting saves instead of stolen bases. Not only do the correlation charts support it, but the draft trends give it the thumbs up too.