Thursday, January 08, 2009
Draft Manifesto
Posted by Michael Lerra at 2:51amIf the Sports Guy can release his playoff gambling manifesto and not worry about it being used against him, perhaps I can do the same with my fantasy baseball draft manifesto. Here goes.
1) Don't draft a Utility guy like Travis Hafner or David Ortiz. Not only do these guys tend to be older and have ever-worsening contact skills and playing time, but they also keep you from taking advantage of some draft bargains. How many times have you been in a draft where a player is hanging around for 20 or 30 picks longer than you anticipated? I'm not talking the consensus 10th pick still around in the 4th round, but maybe a guy around 90 falling to 120 or 125. And you pass him by because you already have his position slot and your Utility slot is full? The Utility slot should be reserved for this type of occasion. In addition, if you're not attached to your Utility player, you can keep churning through free agents and waiver wire pickups until someone drops a player they really shouldn't have. Then, no matter the position he plays, you have a spot on your starting lineup for him.
2) Don't draft a catcher in the top 100. These elite catchers just never seem to perform to their level. If Brian McCann is ranked 33rd preseason, he could have a solid season and still only be the 66th best player by the end of the year. Picking him 33rd is a terribly inefficient pick. It's a brutal position on a player's knees, and I'd bet catchers break down at almost the same rate as starting pitchers. I tend to go for catchers ranked somewhere between 100 and 200. Take a gamble on a catcher, don't go for an established star. Let someone pick McCann, Joe Mauer, Russell Martin, and Victor Martinez 30 spots higher than their eventual end of season rank.
3) Don't pick Carl Crawford. In the preseason, he always seems to be ranked in the top 10 or 12, and always seems to end up ranked 20th by the end of the year. I have no proof of this, it just seems like it.
4) Spread out your steals. Don't count on a guy like Eric Byrnes or Brian Roberts for 50-plus, because a slight injury or change in philosophy could cut that number in half. Instead, find a bunch of guys that get 10 or 12 steals. A lot of times, opposing drafters won't consider those steals as part of the value of a player, but having them will reduce the variance in your team's output, and they can certainly add up.
5) Don't worry so much about batting average and ERA in head-to-head leagues. As I showed in a previous column, being good in those categories doesn't give you much of an advantage each week. On the other hand, if your team is truly excellent in runs, you'll be rewarded with consistent head-to-head wins.
6) Use two basic principles to your advantage: regression to the mean, and aging. Almost every fantasy owner who mis-values a player will do so due to forgetting about those two concepts. Young players tend to get better, old players tend to get worse. Sounds simple when you say it, but how many people are going to draft Manny Ramirez as though his 2008 age 36 season is exactly what they should expect for 2009? And along a similar vein ... don't forget about regression to the mean. You have the tools on the stats section of this site to take a closer look at fantasy statistics. Be a critic, be skeptical, and stick to the null hypothesis: a career season from a player in his late 20s or anywhere in his 30s does not indicate a new true talent level, unless you have peripheral stats to back it up.
Mike is located in Cambridge, MA, working in the search engine marketing field, and waiting for fantasy baseball to get as big as poker so he can "go pro". Feedback on all pieces is welcome and appreciated!
Dude, pardon my french, but you are really fucking my #### right now. Please let me explain…
I clicked the link to your previous post, and found that it was excellent (your post was made during my December dark period for keeping up with baseball, so I missed it when you posted it).
I have actually done a similar analysis in my league for the past three seasons. I used a different methodology than yours, and would like to discuss this with you. I hope none of my leaguemates are reading this…
I will summarize how I came up with my category weightings. I have taken everyones year end ranking in every category, and sorted the teams from highest to lowest (Thus, the top team shows 903 home runs on the season, the second highest shows 875, etc). Then I calculate everyones winning percentage in that category over the season, using the formula Yahoo uses to calculate overall team winning percentage (thus, the team with the highest HR total actually had a 80% winning percentage in HR). I then calculate the correlation between these two categories. The correlation between these two data sets is what I use. I have this data for three years, and use an average of all three years to try to get a smooth number. This has given me a large advantage over my league mates when assessing player value. I was somewhat displeased to see someone else writing about this, but now that you have would like to discuss our methods and results.
Here is how your numbers compare to mine, with your numbers first:
Runs: 82…83
HR: 87…76
RBI:75…66
SB:93…89
Ave:68…70
Three of the categories are almost exactly the same, R, SB, Ave. Concerning HR, My data for 2006 and 2007 average to 81, still below your number, but my correlation for 2008 was only 66%. Concerning RBI, my correlation averages to 70% for 2007 and 2008, but 2006 showed only 60%. If I squint my eyes enough, I can see that we both rank SB the most consistent, with R and HR the next two, and RBI and Ave as the least consistent.
For pitching…
W:86…76
K:91….81
Sv:93…91
Era:66…81
Whip:76…74
Only two of our categories match up, Sv and Whip. For wins, my correlations are 76, 60, 93 for 2006/07/08. For K, I have 85,82,76, so all of my numbers here are lower than yours. Era…86,86,71, so I show consistently more consistency in era than you do. If I squint my eyes, I can see that we both have Sv as the most consistent, and K as the next most.
I an curious to know your thoughts about my methodology and results.
Also, I would like to discuss a more time consuming method which I have not done. It would be interesting to see what everyones winning percentage would be if they had to play everyone every week, instead of just playing your single head-to-head opponent in a given week, and being subject to the luck of their week. By this, I mean not gauging weather your record in HR in week 1 was 1-0 or 0-1, but what would your record in HR in week 1 have been if you had played every team that week. In this analysis, while your actual record in HR in week 1 might have been 0-1, your record in home runs in week 1 when matched up against every team in the league might have actually been 7-4. I thought about doing an analysis like this for every stat category, for all teams over the entire 22 week schedule, but this was a little too cumbersome. I do think that this would give a clearer picture, as managers can change the appearance or strength of their teams over the course of the season, and this would more fully capture that.