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Thursday, May 02, 2013
The Daily Grind provides daily match-up advice for tinkerers and daily fantasy players. I welcome advice to help make this column more effective, including notice of impending weather events, new injuries, and changes to platoon situations. Ownership rates are from Yahoo!
The daily picks are a mixture of Daily League specific advice and information for the more typical fantasy owner.
Pitcher (to start): Yesterday I recommended Roberto Hernandez and Ervin Santana for today. Rain and wind will make that game interesting to say the least. Predictable outcomes are out the door.
Despite Dillon Gee failing me again, I love almost anybody starting against the Marlins. Today that is Kyle Kendrick, who is probably worth owning outright. Lefties (like Lucas Duda) can still take advantage, but he seems to have made legitimate improvements last season that have carried over to 2013.
Justin Grimm is also on that fringe of guys who can be rostered outright. I never saw through his 9.00 ERA last year to the solid peripherals, but he generates a good number of whiffs and rarely walks anybody. In a small sample this year, he's not getting mashed. In last season's mini-sample, he gave up a 29 percent line drive rate and .438 BABIP compared to this season's more sane rates of 19 percent line drives and .288 BABIP.
Pitcher (bum): I'm suppressing the urge to make a Joe Blanton fat joke, which is a shame for you because I had a good one loaded up. Anyway, start Orioles.
What's the over/under on runs scored in a Rick Porcello versus Jordan Lyles match-up? 15?
Dan Haren has lovely peripherals. The question is, do his .386 BABIP against, near 16 percent HR/FB ratio, and continued decline in whiff rate tell us that he's serving them up? I'm betting the Braves have a feast.
Hitter (power): Scott Hairston sees a lefty. Which is one of Dr. Seuss' most conventional stories.
Jonny Gomes and Daniel Nava also see a lefty.
Juan Francisco sees a righty. He's different.
Hitter (speed): Chris Denorfia sees...a lefty! But you knew that as soon as I wrote Denorfia—he doesn't play otherwise.
Pitcher (to start): Jonathan Pettibone faces Ricky Nolasco and the Marlins. Have I mentioned that this is a near auto-start?
The Yankees' fairy tale has to end sometime, right? A.J. Griffin is down to 32 percent owned. He's a solid pitcher with a solid match-up. He does oppose C.C. Sabathia, so he shouldn't be choice 1A.
Felix Doubront has a fringy match-up in Arlington. I'm not sure that goes well with his penchant for home runs allowed.
Barry Zito is a wild card. I'm a fool for associating with him, but I don't much respect the Dodgers offense at the moment.
Pitcher (bum): Jason Marquis has been good this season, but I'm betting on the Diamondbacks' offense.
The Rays will be the latest team to prey on lefty Jeff Francis.
Poor Shaun Marcum has a tough game ahead of him against the Braves.
Hitter (power): Marcum starting equals Francisco in the fantasy lineup.
Ryan Raburn looks like he's on one of those hot streaks he used to supply once a year. And he'll have the platoon advantage.
Another lefty for Gomes and Nava.
Hitter (speed): Try Nate Schierholtz against Mike Leake.
It's a Craig Gentry start day.
Also try Gerardo Parra.
A windy, rainy game is expected in Kansas City between the Rays and Royals. Games hosted by the Rangers and Cubs could also see a spate here or there.
Posted by Brad Johnson at 5:54am
Counting statistics are relatively easy to compare to one another. With an idea of how many fantasy points they are worth, how many it will take to typically earn a specific number of roto points, and how many will be available in all of baseball in a season, you can compare counting stats to each other with appropriate context.
Rate statistics are more difficult to handle because they are really two stats in one, the first a standard counting stat and the second the opportunities for that counting stat. For example, batting average is a rate statistic comprised of hits, a counting statistic, and the opportunity for hits, which is at bats.
As with other counting stats, hits can be more or less valuable for your team depending on their context. If you are one hit away from tying another team’s total on the last day of the season, then one hit is tremendously valuable. If you are far away from both the closest leader and trailer of you, then one hit will be less valuable. However, every hit is a positive event.
In contrast, the opportunity event is always a negative event, a fact that requires a bit of framing to understand. Yes, a .300 average is more valuable over 600 at bats than over 300 at bats, assuming a .300 average will increase your team average. However, the reason that is the case is because of the additional hits, not because of the additional at bats.
I could calculate both hits and at bats as a percentage of league totals, as I did with the counting stats. The problem is that a hit is a positive event that does not equal the negative event of one at bat. A batter that produces one hit per three at bats is among the best in baseball.
I can, however, still calculate the league average, and then use it as a benchmark for comparison. Here is the batting average of all non-pitchers over the last three seasons:
In recent years, league average has declined slightly. In 2012, it was .258. I also included the standard deviation of the batting averages of players with at least 300 at bats in those seasons, which has been close to 30 points in each season.
With the league average and standard deviations, I can calculate the Z-score of a specific player’s batting average. A Z-score is a simple expression of how much better or worse a sample statistic is compared to the mean on a scale of its standard deviation. A Z-score of 1 is one standard deviation above the mean while a Z-score of -1 is one standard deviation below the mean.
Here are the Z-scores of the batters that were closest to each whole deviation in 2012:
A player with a high Z-score will have a correspondingly high average. The reason Z-score is a useful statistic is that it allows you to compare different statistics on different scales. Jeffrey Gross explains it well in his article from a few years ago on his auction-pricing model. I’ll hit on a lot of those same points in the coming weeks, and I will try to apply some of those principles of draft preparation to in-season strategy.
Posted by Scott Spratt at 3:54am
Up until this fantasy baseball season, I solely played the game in the traditional formats. While I was never a rotisserie purist, submitting myself to the variance (and fun) of head to head leagues, I just never had interest in creating a new team on a daily basis—to me, a lot of the fun in fantasy comes from managing a team as you would a real one throughout the ups and downs of the season.
This year though, that changed. After my 2012 fantasy season debacle of being an owner or co-owner in 13 separate leagues, and subsequently not having the time necessary to manage any of them to their full potential, I cut back to only five teams for 2013. To fill the void left by shedding those eight leagues, this season I have traversed into the murky, but opportunity-filled, waters of daily fantasy gaming. And I have to say I’ve loved it.
Although there’s something ideologically nice about having the same team and sticking with it all season long, the most entertaining part of fantasy to me is definitely drafting. And that’s essentially all daily gaming is: drafting a team, just for one day, at any point throughout the season.
There are many strategies for success in daily fantasy gaming, and they often mirror strategies that work in full-season leagues as well. However, because the season has already started and statistical results have started to flood in, there is more opportunity to subvert the norm and go against the grain in daily games because the public is overly inclined to change their opinion on a player in early season small samples. So, here are five rules to follow to help you win more consistently (or perhaps lose less consistently) in daily fantasy baseball games.