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ps - yes, my mother was an English teacher
Structurally, the sentence has the 3 doing the Missouri shuffle, with Moss specifically going from St. Loo to KC.
Linder 'wins' 4 of 6 categories but Villar 'wins' overall?
Very interesting article.
This hasn't been bugging me for years, but last week I decided that what jnossal has stated is true - control may indicate the ability to throw strikes, but command as it is currently defined is just better control.
However, I think CSAA may be a way at actually getting at command.
I really would like a better description though of how it is measured. First you say that looking at catcher movement is flawed, but then in the next paragraph it sounds like you are measuring catcher movement ?
Another aspect of command that CSAA misses is the issue that you are getting at with your graphic of best-worst - and I think this is one of jnossal's points:
Pitchers with command are getting pitches to move reliably, whether to the edges of the strike zone or darting out of it. This would seem to be part of command, and then whiffs outside of the strike zone should also be part of its calculation. (Envision <span class="playerdef"><a href="http://www.baseballprospectus.com/card/card.php?id=49617">Andrew Miller</a></span> in the playoffs, or vintage Mariano)
(Although this might be problematic because overpowering fastballs might be counted here as well).
You have "July into July" in there. If you need the typo at least add an "r" so it's adultishly funny.
"I’m interested in knowing what a player is worth at the auction or draft table, not what he is worth in November when the season is done."
I confess to being confused about your distinction between "placing bets" and "prediction".
Surely in fantasy baseball, your initial valuation of a player at the time of the auction is largely predicated on your expectation of their earnings over the course of the season. Thus your "bet" is a direct reflection of a "prediction" of performance.
For example, if you diverge from orthodoxy and predict Villar to have a breakout season, then you are willing to pay more ("at the auction") for him than other drafters, in the expectation that you will recoup or exceed your investment ("when the season is done").
Given the higher fragility of pitchers, opt-out clauses may actually be more likely to be favorable for pitchers than hitters.
Take Melancon and <span class="playerdef"><a href="http://www.baseballprospectus.com/card/card.php?id=47493">Dexter Fowler</a></span> as examples. About the same age, let's posit that Fowler also receives the same 4 year contract and opt-out clause.
Let's further posit that both put up very good seasons in their second year.
Both, reasonably, exercise their opt-out clause. Which of the two is more likely to fall off the cliff in year 3, a 33 yr-old OF or a 33-yr old pitcher?
I presume that the data are available so that this is not just a rhetorical question.
Second graph - "Major-league starters with 200-plus innings pitched (2002-2016)"
is a copy of the first showing <span class="statdef"><a href="http://www.baseballprospectus.com/glossary/index.php?search=ERA" onmouseover="doTooltip(event, jpfl_getStat('ERA'))" onmouseout="hideTip()">ERA</span></a> trends
Excellent overview !
Will we get a similar view of how the Indians built their WS team?
Thanks Rian for this thoughtful piece
I agree, runs is runs.
But, sheer speculation - if the homer came later in a very tight game, maybe there is a negative psychological effect on the pitcher's team ...
Striking difference in your table between Hamels and everyone else - he gave up 11 homers in those 10 games
No <span class="playerdef"><a href="http://www.baseballprospectus.com/card/card.php?id=56957">Tony Watson</a></span>?
"Highest available expected value" does not incorporate variation in categories. If I've covered <span class="statdef"><a href="http://www.baseballprospectus.com/glossary/index.php?search=OBP" onmouseover="doTooltip(event, jpfl_getStat('OBP'))" onmouseout="hideTip()">OBP</span></a>, runs and <span class="statdef"><a href="http://www.baseballprospectus.com/glossary/index.php?search=RBI" onmouseover="doTooltip(event, jpfl_getStat('RBI'))" onmouseout="hideTip()">RBI</span></a> and desperately need a player to contribute Batting average, overall value may not be the best choice.
Of course, you could follow the axiom and hope to trade for BA later. My league however, has a relatively low trade volume, which creates a downside to depending on a trade.
I feel like I'm missing something here.
Isn't it simpler to just remove the kept players from the pool and recalculate the values for the remaining players using the $1200 budget?
Isn't it the value of those players relative to one another that is important?
<span class="statdef"><a href="http://www.baseballprospectus.com/glossary/index.php?search=4C" onmouseover="doTooltip(event, jpfl_getStat('4C'))" onmouseout="hideTip()">4C</span></a> = four corners
Stanton is ridiculous !
The difference between #1 & #2 is >4mph
The difference between #2 and #20 is <2mph
I must admit to being a bit confused by the conclusion regarding Fig 1: "those pitches that follow the general trend of the line, albeit with random scatter about the line. These pitches are of type FA, SI, CH, and FS" ...
Wouldn't independent regressions of these pitches actually produce relationships that are nothing like the 1:1 line? Both fastballs and sinkers look to have a much higher slope.
To consider them as part of the same "family" of pitches shouldn't they at least have slopes that don't differ significantly from each other? And to consider them to have no gyrospin, neither their slopes nor their intercepts should deviate from 1:1.
When you separate pitches below the line, you are talking about differences in intercept - these pitch groups may or may not have slopes that deviate from 1:1.
But … will 12 more days of work at the minor league level actually be adequate additional "development time"?
I don't accept your presumption that offense and defense are equally valued.
An advantage of the 4 star hitters lineup could be that the GM would then focus on getting plus-plus defenders as the scrub hitters at the bottom of the lineup.
Of course that advantage might be neutralized at the top if the star hitters are one-dimensional.
St. Louis also has the Missouri Botanical Garden, a jewel in its tarnished crown.
I think this is fascinating, but I do wonder about the effect that absolute age has on the other end of the career.
If we posit that players tend to hit the wall at age X on average, then players who start their careers at X - 15 will on average have longer careers than those who start at X - 10.
I realize that age X is not an absolute absorbing barrier, but intuitively it seems like a potential factor.
Your table of PECOTA projected batting losers has some calculation errors in the DIFF column
The 2014 shot seemed to come off the bat even more quickly than the one in 2010.
Any measure of ball speed off the bat?
Are there enough data to compare teams' performances?
J-sub-T might also be significant in cases where a team needs to make a 'statement' to its fans, e.g., Granderson & the Mets might represent such a case
In the Schwartz vs Carey pitchers table, someone has rounded the 'decimals' of overall draft position
In going over the PECOTA forecasts I discovered an interesting aberration, namely ALL NL relievers are projected to win more games than they lose.
Our league uses Wins - Losses as part of its stats ensemble, and because relievers all are better than average in this category, they float to the top of the projected pitcher performances.
Using the Depth Chart page, Arizona's starters are projected to win 51 games and lose 66. Their relievers Win 28 games and lose 19.
Why is PECOTA conservative for starters but thinks all relievers are net winners?
It's always nice to read old Nate again, but what good is an old article on projections if it doesn't actually compare those projections with reality?
It would be nice if a link to the actual WARs (for these players in this period) were provided.
Is it possible that pitchers for a team with a weak offense would tend toward higher leverage scores over the course of a season?
What I'm thinking is that if the team's average margin of victory is small relative to the league average, then pitchers on that team will tend to pitch in higher leverage situations.
Although this would likely be balanced by lower leverages due to larger margins of defeat.
From the chatter from my league (auction, NL only, heading into 33rd year !) during the WS, Wacha seems likely to go high. Where did he go in your draft?
For a top 10, I'd give a vote to "Cooperstown", a made-for-TV TBS production starring Alan Arkin and Graham Greene. Good story about two players who have a falling out, with Arkin p.o.-ed when Greene gets into the Hall.
Also loved "Bang the Drum Slowly" but the book (by Mark Harris) was better
I decided to test this in response to evo34's comment above.
For pitchers with 100 or more IP in both 2010 and 2009, the correlation of FLAKE between years was r=0.08 (n=94).
For 2008 and 2009, r=0.17 (n=88).
Correlations between years for the top 32 flakiest were somewhat higher,
r= 0.175 between '09 and '10, and r = 0.44 for '08 and '09.
So, although the flakiest may have a tendency to stay flaky,
I think evo is probably right that steadiness doesn't seem to have any predictability.
I've never considered 'quality start' a particularly useful concept.
However, it does seem to say something about keeping your team in the game. I'm sure BP has the probabilities associated with eventually winning a ballgame if your opponent has scored 3 runs or fewer in 6 innings.
A robot pitcher who could be counted on to give up 3 runs in 6 innings every time he got the start would be far more valuable (i.e., a 4.50 ERA and a 0 Flake rating), than a Flake-star like Joe Saunders (overall ERA of 4.47, Flake ~.29), who had 10 starts in which he had an in-game ERA of 7.5 or better.
But Peter ... you're still here, thus violating the Pizza Parlor Rule
Repost Table with spacers
....................BA... OBP... SLG
delta(PEC-actual)-0.006 -0.012 -0.025
Just did a quick analysis of the data (dropping Jackson & Delgado).
Here are PECOTA vs. actual correlations and deltas
BA OBP SLG
Correlation 0.72 0.82 0.73
delta(PEC-actual) -0.006 -0.012 -0.025
PECOTA did better predicting OBP than BA or SLG
PECOTA on average is conservative at predicting actual values
I would like to see a slightly longer list, as I participate in an NL only league.
Wouldn't mind seeing PECOTA and actual EQAs for players.
This data set seems more suited to an analysis of variance rather than correlation analysis. ANOVA will answer the question I think you are asking: Do some teams have statistically significantly larger or smaller HFA than average?
In the long run, if the effects actually come down to how individual players respond to home vs away conditions, then the actual makeup of individual teams will end up as a determining factor.
I can't make heads nor tails out of your explanation for #2:
"The simple equation is: (15-x)Va >= 15Vb"
Since a DL stint is always at least 15 days, x must be >= 15, and thus the left side of your equation is always <= the right side.
The only tactical reason I can see for waiting to DL a player is to have them available as a pinch-hitter.
If the club ends up not using the player, they typically backup the DL date to the day after he last played.
What am I missing here?
In the situation where a true 'ace' is available, it might be best to continue to employ them as such.
This would produce a modified SOMA: pair your ace with your best long-man; if the ace can go 6 or 7 on ~100 pitches, great.
Then pair-up your #2-5 starters to maximize match-ups, or better, to maximize switch-ups -- lefty & righty, fastballer & off-speed guy.
The ace could stay be on an every 4th or 5th day schedule, the paired starters could go every 4th day.
You would need a 4th pair or trio of SOMA guys about once a week.
Most of your other bullpen guys could become situational employees, able to go at least 2 innings.
I second this. All four of these guys have written some excellent analytical pieces. But I thought none of the 4 radio interviews were particularly good.
Perhaps this is BP's wave of the present, but I doubt that previous BP writers ever got hired or not based on live on-air performances.
Sorry, I missed his overall number, I got the -.076 from the Milwaukee team list.
I don't seem to have much time for fine print these days ;>} and besides he was projected to have 455 AB
I expected to see Jody Gerut's name on your underachiever list:
Projected EqA .304
Actual EqA -.076
What Richard actually said was: "The only real difference between a PED and a vitamin supplement is one is arbitrarily illegal and the other is arbitrarily legal."
And you went ballistic.
Yes, he was being somewhat provocative, but we know that A) humans produce anabolic steroids naturally (testosterone and androsterone), and B) there is variation among humans in the amounts that they produce.
So basically your argument boils down to this: your ethics leads you to believe that athletes should not supplement their natural anabolic steroid levels, because there is a perception that this gives them an unfair advantage.
But this was Richard's point: taking vitamins (or any other legal supplements) also amounts to increasing natural levels.
Since we have no real data on how either vitamin D or anabolic steroids affect baseball performance, the decision to ban one and not a wide range of others certainly seems arbitrary to me.
(Arbitrary: based on or determined by individual preference or convenience rather than by necessity or the intrinsic nature of something - an arbitrary standard)
BTW, our lawmakers seem to pull things out of their "friggen hats" all the time!!!
(asterisks just for you)
Yes Joe I did know that Vitamin D is a different class of steroid.
But you have been railing against 'steroids' and called Richard Bergstrom on the carpet for his suggestion that there is an arbitrary line between legal and illegal supplements.
Authorities have made arbitrary decisions about what substances are legal or not. Thus the points made by others about the arbitrariness of our current laws deciding which 'drugs' are legal or not: alcohol and tobacco - in, marijuana and heroin - out.
There will always be an arbitrary line drawn - this does not excuse those who knowingly cross it. But it doesn't make it any less arbitrary.
Your retort about vitamins versus steroids is just laughable!
Bet you didn't know that vitamin D is a steroid.
So much for your apples and oranges argument!
Well Will, this IS supposed to be the Fantasy week, and success in fantasy baseball requires that you be able to do two things: adequately project players performances and be able to evaluate the relative contributions of players (pitcher vs batter; SS vs 1B, etc) to your team.
Tim's contribution addresses the 2nd of these.
Many of us are always on the lookout for ways to place overall weighted values on players.
I've developed a number of Excel-based algorithms over the years to address issues just like the ones he raises.
Tim's approach seems quite useful to me and I give him the thumb!!