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I'm not sure how you concluded that. The methodology and results are more nuanced than your statement suggests.
I think you might have missed the point here. This column is looking at his MVP credentials without regard to the PED story, and is concluding that he is not likely to be the MVP winner.
Did you read the link to Mike Fast's article on the challenges of technology included above? I would not assume anything is easy.
One point that isn't being made in the dicussion above is with regard to allocation of resources. If a team has a specific budget for player projection, how much of that is being spent on accumulating enough scouting opinions to distill out meaningful conclusions. Is there a more optimal allocation that moves some of those resources into longer term technology development, even if it means less scouting data today?
On the other hand, scouting can be done at 1000's of amateur ballparks around the world. How many of the tools used to generate precisely "measured" data are available at all of those parks? I think your points about precision vs accuracy are spot on here... a skilled scout should be able to deliver accurate, if imprecise, information from any place on earth that a player throws a ball, swings a bat, etc. Is improving the precision of those data worth what it would cost?
If the return date meant anything, sorting by it makes sense. A quick scan of them shows that many are wrong or misleading.
Also, the update on Huff at the top is nice, but would have been hard to update the comment on his specific entry as well?
I really like the potential of the format, and look forward to seeing it as the database gets stronger.
A game is not just a short streak, it is a really, really short streak. Perhaps a way to do it would be to look at a histogram of AB's between homers. Conceptually, hitting them in streaks would show up as bi-modal... a cluster around the streak, and a cluster around the typical non-streak. You could normalize each player by his average AB's between homers, and test for a trend among all players.
Only if a "few" opportunities is enough to distinguish successful from unsuccessful.
There are likely add-ins to your browser that would block the ads, if it bothers you that much.
Collateral Damage Daily is a beautiful thing. Thanks for all the hard work!
sometimes, i wish i could hit the +1 more than once.
Since the next article below this one is from the previous day, I have kind of assumed that the chronological sequence of articles is from the bottom up. In that case, the article on top would be the last of the day, and a silly place for the "First Take".
Seeing that Brett Myers gets paid almost a billion dollars ($989,391,252) per WARP can't make the Houston fans out there too happy. Better for him to lose another .1 or so and fall out of the calculation completely.
I think you are barking up the wrong tree. Since you seem to blindly oppose anything published by a current BP employee, perhaps Matt's words (copied below) on Fangraphs will convince you that park effects are not the holy grail to improving an estimator, and in particular, do not significantly handicap SIERA relative to other estimators.
"Park effects themselves come with a bit of noise, though, and the effect of park-adjusting the batted-ball data didn’t help the predictions. The gain simply wasn’t large enough: The standard deviations of the difference between actual and park-adjusted fly ball and ground-ball rates was only 1.4% and 1.5%, respectively, and the park factors themselves were always between 95.2 and 103.9 (the average park factor is set to 100).
There were only 16 other pitchers with ERA changes more than .05 in either direction.
As a result, very few people saw major changes to their SIERAs, and the combined effect was a weaker prediction."
CBS seems to think it is Bobby Parnell. Who else would even have a chance... Izzy?
I'm not sure i'd ever be able to find it, but I remember that a previous article here on BP had also found that HBP were controlled by the hitter. I had commented at the time because I was surprised by the result... is there a way for me to search for article's I've commented on?
The point is that if you've successfully separated the 3rd baseman from the ball, you won't be tagged out or forced out at all.
This is just as poor an argument *for* the streak mattering as the article's argument *against* it. There just aren't enough data points to point at something that has or has not happened once and call it correlated to winning the world series (or making the playoffs, etc). Sky's point is that there is predictive value in the timing of the streak, and that happens often enough to be significant.
Ageed. Cherry picking one team for which a streak to start the season was not predictive is hardly an argument to ignore the predictiveness of opening with a streak. Getting ~90 wins in a 162 game schedule is hard enough. Getting it in 156 games is harder.
Thank you for posting this. Timing of the streak does matter.
I think that getting a 28 year old hitting his stride is an excellent idea. I'm not sure what that has to do with Carlos Quentin.
There's got to be a difference in the chance of injury between playing basketball and using tongs at the salad bar.
In the real world, organizations like OSHA exist to reduce the chance of injury in a workplace... eliminating it completely is a loft goal but not really attainable. It shouldn't be unreasonable to ask professional baseplayers to make choices in their personal life that reduce the risk to their performance.
Isn't the horizontal shift here consistent with the scouts' observations? I don't know what a horizontal shift in release point looks like on a real arm and shoulder, but in 132 characters or less, could it be that "arm angle dropping" is a quick and dirty way to describe it?
I'm not sure this article was about how the make Brett Gardner a better baseball player. I think it was more about how to value Brett Gardner as a fantasy baseball player, based on the recent trends in his batting approach.
correction... range upper control limit of 5.1%, which says that over any consecutive three year period you should see less variation than that.
Is anyone else reading this familiar with Xbar and R control charts? A pretty good description is here:
If the data from 1951 to 2007 are subgrouped in non-overlapping sets of three, 53.9% is the average with an upper control limit of 55.9%, a lower control limit of 51.9%, and a range upper control limit of 2.0%.
Adding 2008-2010 as the next group of 3 does not violate any of the control limits, and are unremarkable in that context.
Someone smarter than I will have to explain why a Student's T-test shows the last three years as significant, while Shewart's control chart scheme does not.
This should be required reading for anyone who has ever yelled at an ump from the couch.
I strongly disagree here too. Wouldn't the range for a guys like Adam Dunn, or Ichiro, be significantly smaller that the range for a guy like Aubrey Huff? As a fantasy player, you want to make decisions based on risk-reward, and there are times where you might seek more mediocre, reliable performance than going for all or nothing.
I would think that publishing the numbers with a ± interval is systemically wrong. You say that not all things are symmetrical... I would image that very few really are. The assumption of normality that is also implied to when you start using "standard deviation" is also a big leap. Publishing percentile data shows at least a rough outline of what each players probability distribution looks like, which then allows factors like "breakout" or "collapse" to be included in the model based on the comps.
Count me among the people who are excited by the prospect of change. Will's columns have been great, and I'm looking forward to seeing how injuries will be treated on BP through the playoffs, off-season, and into next year. A fresh voice and ideas may help take the conversation to an even higher level.
Strikeout and walk rates are affected by park? Really?
It probably depends on what you want to do with the projections. If you are playing fantasy baseball, it is probably fair... I believe that relative performance between players is what matters most, not the absolute level at which they collectively perform.
How does TAv translate from AA to AAA? What kind of line in AA would he have had to put up to be equivalent to the .314 International League TAv he has put up since the promotion?
+ for point 2, - for point 4 = no rating.
Also, it would be hard to believe that Wright is seeing substantially better pitchers than his teammates... late inning bullpen usage by the opposition might affect the stat, but not drive it.
The story is Wright's K's, not the Mets as a team.
A new stat... OP-S?
"sometimes, seemingly easily avoidable accidents happen."
although this statement is full of truth, rarely does declaring it end well. just imagine if you worked for the other BP...
Thanks for reporting back on it! I was struck by the lack of 100's in the data in the article, but it is clear that a larger data set fills it in better. I always like reading about the reliability of the source data that is used in so many of the advanced metrics, and this was a nice look at the way errors are scored.
Not to get all nit-picky on you, but the standard deviation you quoted applies to data that is normally distributed. The data you've posted here is a small set, but actually looks bi-modal. Anyone want to take a stab at what that might mean?
You think the player would be OK with giving up their paycheck for 50 games, as well as risk harsher penalties in the future and the less tangible hit to the reputation? I don't.
Tangentially... what drives the batter's 62.2% portion of the HBP outcome? Where he stands in the batter's box?
If I understand correctly, for batters:
A high line drive rate is better than
a high ground ball rate, which is better than
a high fly ball rate, which is better than
a high pop-up rate.
However, as SIERA shows, "run prevention improves as groundball rate increases".
For groundballs to be beneficial to both the hitter and the pitcher feels like a paradox. Is there an easy way out of that?
Seeing that there are just two separation points is extremely useful to me. With tiers, you are basically seeing that the prediction error bars overwhelm the differences between many individual players. If players #4 through #8 are all basically the same, seeing individual rankings within that group may lead you to false conclusions about the projections for each of those players.
17.2 million, because it isn't taken yet
My co-workers would notice if I started playing with blocks during lunch. The Week in Quotes is always a fun read, and less likely to result in some kind of counseling.
Thanks for the response! For me, the article definitely works as a hook... even if I'm not sure I agree with where you are trying to take these numbers, there is enough substance to have a conversation about it. Other popular fantasy authors who focus on the game "by the numbers" could learn from that. Your willingness to engage your readers in the comments section is a big plus.
Good luck, and hopefully we will all get a chance to learn alongside you about ways of improving projections between levels.
I finished the article feeling confused. I understand there are three possible outcomes at each PA... a K, a BB, or contact. I guess I'll echo the "what's the thesis?" feedback. Is it this?
Higher strike % = Lower walk %
Higher contact % = Lower walk %
Is that real insight? Is there any relationship (or perhaps 2nd order interaction) between str% and con%?
Perhaps the point is more to introduce another set of statistics that may be useful for projections, without drawing any conclusions yet on what the relationships might be. I guess that is ok, but some kind of tip of the hat to the work that has already been done would be nice. Back in January, Eric Seidman showed some analysis on Oliver Perez demonstrating the importance of contact rate on pitches thrown in the zone vs those out of the zone. Shouldn't contact rate in Brian's article be broken down into "in zone" and "out of zone contact", or at least some acknowledgement be made that it could? (see http://www.baseballprospectus.com/article.php?articleid=8452)
I get a similar feeling from the unfiltered post... why just post Oliver projections, when posting the Pecota numbers alongside could be equally as instructive and more familiar to readers here. Introducing new concepts is ok, but not if it is presented with tunnel vision to what others before have done.
I found BP because of fantasy baseball, but as other sites complete with their own take on the statistical analysis, articles like this are why I hit the renew button.
The comments feature has exposed the narrow focus of the current generation of fantasy sports fans... i hope you are able to commecially maintain this kind of breadth in your coverage.