Razzball is hosting the Roundtable this week.¬† I figured that we’re known as the class clowns so I’d surprise them all with a statty question.¬† Here it goes…
What sabermetric or alternative statistic (e.g., Ground Ball ratio, Contact Rate, etc.) do you find to be highly over or undervalued for fantasy baseball player valuation purposes?
Brett Greenfield – Fantasy Phenoms
I think that BABIP is a highly overvalued statistic for analyzing a pitcher and I’ll tell you why.
Certain pitchers tend to consistently have low BABIP’s, such as Chris Young of the Padres.¬† This is primarily because he is one of the biggest fly ball pitchers in the major leagues.¬† In 2006, Chris Young led the majors in fly ball rate.¬† In 2006 he also led the league with the lowest BABIP.¬† In 2007, Chris Young led the majors in fly ball rate.¬† Again, in 2007 he led the league with the lowest BABIP.¬† Pitching in Petco Park strongly favors pitchers in general, but it also favors fly ball pitchers, since the outfield is so big.
BABIP, in general, is a stat that favors the fly ball pitcher, too.¬† Let’s take two equal pitchers, where one of them induces 70% groundballs and the other induces 70% fly balls.¬† The pitcher who induces 70% fly balls is far more likely to have a lower BABIP than the pitcher who induces 70% ground balls.¬† This is because a ground ball has a much better chance of going for a base hit than a fly ball does.
In fact, in looking at the 20 pitchers with the lowest BABIP’s from 2008, 90% of them were pitchers who favored the fly ball.
The 10% that were in the top 20 that induced more ground balls than fly balls, yet still had a low BABIP, should be considered lucky.¬† Most tend to consider every pitcher in top 20 (or those with BABIP’s below .265) as having been lucky and predict that their ERA and WHIP will regress the following year.¬† Sure, the top 20,¬† regardless of fly ball or ground ball tendency, could very well see their BABIP deviate closer to the norm the following year.¬† But if they are strong fly ball pitchers, their BABIP may not go up enough to make a noticeable difference in their ERA or WHIP, rendering BABIP as a useless statistic when evaluating them.¬† Several pitchers tend to have low BABIP’s year in and out such as Matt Cain, Ted Lilly and Chris Young.
BABIP can be useful when combined with other statistics, but when used by itself, can be deceiving.¬†
Patrick Cain – timesunion.com Fantasy Baseball blog
My often-cited stat problem is summed up in two words: Spring Training. But to be more specific, in a few weeks many of us will crunch the numbers to see what players saw a 200 pt increase in slugging percentage during ST. It’s alleged that three-quarters of players that hit this mark, have better than normal years.
I have a few problems with this.
1. Define “better.” If Player A hits a lifetime of .700 OPS and now is .710‚Ä¶so what. That’s not a breakout.
2. Many guys who do improve aren’t a surprise. They’re young players who got a year old and a year wiser.
3. Most of all, the data sets are small for each player.
Here’s a list I found from late in ’08’s Spring Training. The group certainly has a few gems (Josh Hamilton) but also a number of flops.
Chris Synder, Mike Morse, Ivan Rodriquez,Melvin Mora, Grady Sizemore ,Brian Anderson, Chris Burke, Rafael Fucal, B.J. Upton, Mike Cameron, Yorvit Torrealba, rick Aybar, Torii Hunter, Curtis Granderson, Placido Polanco, Billy Butler, Gerald Laird, Tony Gwynn Jr., Craig Consell, Josh Hamilton, Ryan Shealy, Andre Ethier, Robison Cano, Ray Durham
It’s a small data set, but the list wasn’t too impressive. That being said‚Ä¶I’ll still take note of it when I draft.
Tim Dierkes – RotoAuthority.com
Most people who read this are well aware of BABIP (batting average on balls in play) and its uses for pitchers.¬† However, in a more general sense, I still find that most fantasy baseball players are unaware of or choose not to look at this statistic.¬† It is a pretty easy concept but it still has not hit the mainstream.¬† I don’t think it’s really close to hitting the mainstream.¬† On baseball broadcasts we are still given the misleading impression that a low opponent’s batting average is an entirely controllable skill.
I am not saying that a pitcher with an abnormally low BABIP should be dismissed.¬† More that if a pitcher’s brief successful run is clearly leaning on a low rate of hits allowed, he is probably a fluke.¬† Even casual fantasy players should be glancing at a guy’s last five starts and if he’s succeeded because the hits did not drop in they should know to pass.
Jon Williams: RotoExperts
There are two distinct groups of fantasy owners -‚Äď those that use advanced statistics, and those that do not. I do not think that I am taking a huge leap to suggest that those that do not use them are primarily those that do not understand them. Because if they did understand them how could they not use them? The problem is many owners who use them (and many writers who write about them) do not truly understand how to utilize these statistics. There are many examples of this but I will just point out a very common one.
BABIP is an excellent statistical tool that measures the number of batted balls that safely fall in the field of play for a hit. The typical batter is able to average between .290-.310 on the balls they put in play. The uninformed owner will assume that if a batter has a BABIP of less than .300 in any given period that he was unlucky. And he assumes that if a batter averages greater than .300, that the batter was lucky. In both cases, this owner will assume that the batter will regress to a ‚Äúnormal‚ÄĚ .300 BABIP or thereabouts. This is too many assumptions and we all know what happens when we assume.
In reality, every batter and every pitcher has a different level of skill. For example, players who excel at utilizing their speed out of the batter‚Äôs box tend to have higher BABIPs. There are also batters (even some with speed) whose skill level leaves them with a BABIP below the .300 average. If an owner truly wants to utilize these stats to advance their game, they need to read more than the basic definition of the stats and examine their use. An easy way to do that is to read the work of those that truly understand. The writers at HardballTimes.com and Fangraphs.com are very good places to start.
Patrick DiCaprio – FantasyPros911.com
In my mind it is clearly ground ball ratio. The percentage of groundballs is simply ignored by most fantasy owners, who instead focus on K, BB and K/BB. Valuable though these things are the fact is that everyone knows them, and they do not represent value. The most undervalued pitchers in baseball are those with middling control but huge groundball rates and good strikeouts. How did Ubaldo Jimenez do last year?
The second most ignored group are those with good groundball rates and weaker strikeouts, at least in deep ‚Äúonly‚ÄĚ leagues. If you take a list of guys with the same K rates (in theory) but group A has good control and group B has high groundball rates, group A will probably do better but group B will have a lot more value.
Derek Carty – THT Fantasy Focus
This is a topic I could talk all day about.¬† There are so many stats that either shouldn’t be used or are used incorrectly.¬† I won’t single out any person or site individually, but I’ll list a few stats that I don’t like.¬† The first one I don’t imagine will be on anyone else’s list, and it’s one I imagine some of you thought was a good one to use.
K/BB: It seems like everyone is using K/BB ratio these days, and on the surface it makes sense.¬† DIPS Theory says that we should focus on events that a pitcher has control over.¬† Strikeouts and walks are the two most important of these events, so capturing their effect in one stat makes sense.¬† There are two problems, though:
1) A strikeout is not worth the same as a walk, so weighting them equally is flawed thinking.¬† I found here that it’s better to have lots of strikeouts and lots of walks as opposed to few strikeouts and few walks, even if the K/BB ratio is exactly the same.¬† I then took it a step further and created a stat that properly combines the two.
2) Ratio stats are almost never a good idea.¬† Say a pitcher has 10 K and 5 BB.¬† That makes a 2.0 K/BB.¬† But it also makes an 0.5 BB/K.¬† Using K/BB shows double the impact of using BB/K, yet they are measuring the same thing (and which we use is completely arbitrary).¬† If you’re set on weighting the two equally, at the very least do K minus BB (divided by IP or TBF or something like that).
BABIP: This isn’t a bad stat, it’s just that so many people use it incorrectly.¬† And quite honestly, I have no idea why.¬† It’s very simple.¬† Most pitchers regress toward the league average BABIP of around .300 or .305 (some sites don’t even get this right, saying that league average is some different figure, or saying that it’s different for batters and pitchers.¬† It’s not!). Very few pitchers can repeatedly do better or worse than this, so we say that pitchers have very little control over BABIP.¬† Batters, on the other hand, can have a substantial amount of control over BABIP.¬†, for example, has a .356 career BABIP. Hitters do not regress toward league average, rather, they each regress toward their own, unique number.¬† Despite this, we’ll still inevitably hear people continue to use it incorrectly.
A few other stats I dislike but don’t have the room to discuss (if you’re interested in an explanation for any of these, please feel free to e-mail me):
GB/FB (not to be mistaken with GB%, which is a good one), OPS, Linear Weighted Power, FIP, ERC, BB/K (for hitters), ISO, BAA, speed score to represent steals, H/9, HR/9, WHIP, Runs Created, Quality starts (QS), BB% to calculate anything other than times on base, LD% + .120 as xBABIP
My final point is this: if you’re reading a site that is using advanced metrics, or any metric that you aren’t 100% familiar with, make sure that this person/site truly knows what they’re talking about.¬† There are plenty out there that simply don’t, and relying on poor advice can be so detrimental to your fantasy season.
Adam Ronis – Newsday
I think BABIP is a good measure for hitters when used correctly. Too often people refer to an average BABIP of around .300 for a hitter, but it varies for each individual. Take Ichiro is the perfect example of how it varies for each individual. The BABIP for his career are: .371, .347, .333, .401, .319. .350, .390 and .337.as an example. His BABIP was .326, .348, .317, .318, .325, .375 from 2002-2007. It was .294 last season, so you can expect his average to improve this season.¬†
Many guys with elite speed will have higher BABIP, such as. His BABIP since 2003 is .329, .326, .328, .332, .375 and just .301 last season, so you can expect Crawford to hit for a higher average. BABIP is a good tool to use, but it has to be examined on an individual basis.
Rudy Gamble – Razzball
I figured I’d wait to see how everyone else responded before taking a crack at my own question.¬† Looks like I don’t have to cover BABIP!
Undervalued:¬† Batted Ball Statistics for hitters (Fly Balls/Ground Balls/Line Drives). I believe these were first identified by Ron Shandler.¬† Line Drive % is generally good for predicting high average hitters but I tend to ignore it as I trust projection systems like Marcel, CHONE, and ZiPS for batting averages.¬† I find the % of Fly Balls is crucial for understanding a player’s HR potential.¬† For instance, let’s look at three players that seem to have 30/30 potential – Grady Sizemore, BJ Upton, and Matt Kemp.¬† Based on watching these players play, they all seem like 30 HR possibilities.¬† But their 2008 GB / FB were:¬† Sizemore 34.9%/45.7% , Upton 50.5% / 30.6%, Kemp 45% / 32%.¬† Basically, Sizemore hits almost 50% more fly balls than these two and, thus, is a safer bet for 30+ HRs.¬† Unless Upton and Kemp greatly change their approach at the plate (not unprecedented but rare), their upside is likely 25 HRs and will likely end up at 20.
Overvalued:¬†¬† VORP (Value Over Replacement Player) – Okay, this stat isn’t probably overvalued by many but this is commonly used by those creating their own player rankings.¬† For fantasy purposes, It determines player value by comparing a player against the best undrafted player available at his position.¬† My problem with this is that this tends to overvalue players at 1B/3B/OF and undervalue 2B/SS/C.¬† The reason?¬† Focusing on the best undrafted player ignores the drafted players.¬† Let’s narrow the focus down to HRs.¬† Using 2009 projections, I’d estimate the VORP 1B to have about 14-15 HRs. ¬† This is James Loney/Casey Kotchman territory.¬† For 2B, this is at 10 HRs – say Orlando Hudson.¬† This would make a 30 HR 1B about the equivalent of a 25 HR 2B (+15 VORP).¬† The problem – there’s probably 6 1Bs who’ll reach that mark whereas only 1-2 2Bs will reach it.¬† How can they be equal?¬† Well, the average drafted 1B is at about 28 HRs.¬† The averaged drafted 2B is at 16 HRs.¬† Using the averages, you would find that a 30 HR 1B is closer to the equivalent of a 18 HR 2B.¬† I’d argue VORP is only useful for fantasy baseball purposes when valuing a trade where you’ll need to replace your end with a free agent.¬† But if you are ranking players, it is better to use a position average over the VORP.