THE BOOK--Playing The Percentages In Baseball

“The inflection point where the WAR tends to level off also seems to be around the end of the first round of the draft”

Is there such thing as an inflection point with this graph?  I don’t mean to be a pain here - this is actually a question that came up at work yesterday, and as I’m the “stats guy” in my office, I should know this.

I guess my question is… given a graph like the first one on the linked page, is there anything we can actually say about where things “level out”?  My thought is that you can’t, as it’s a curve, not a bunch of lines with angles you can measure.

If there is the possibility of finding the point at which things “level out”, is there some mathematical way to derive that?

I think an inflection point is defined as the point where the slope changes sign - like at the peak of a parabola. So technically that graph has no inflection point since all the slopes are negative.

I think the leveling out point is arbitrary (not mathematical) - although not unreasonable as a judgement call.

Good catch Mike.  The inflection point of a curve is where it changes from concave up to concave down (or vice versa).  Since the whole thing is concave up, there’s no inflection point.  My bad.

Where the curvature changes sign (not the slope).

Interesting.  In the past, how common was it for a top talent to fall because of signability reasons?  I would think that the Rick Porcellos of the world could throw this study off a bit, when a #27 pick isn’t really a #27 pick.  I’d like to see WAR plotted against something like relative signing bonus, if possible.  I don’t know if that data is available anywhere, though I believe Nate Silver incorporated it into PECOTA at one point.

In the past, how common was it for a top talent to fall because of signability reasons?

It has not been very common.  The biggest one that I know of - and it’s because it’s smack dab in the middle of the period that I’ve studied - is Jon Olerud.  He slipped to 3rd rd - around #77 - due to medical and signability issues.  He ended up with a bonus nearly as large at the #1 pick.  Even in the rolling averages that I’ve done Olerud had a big enough career to make a noticable bump there in the 70s.

There was an uptick in signability guys in the late 90s, but Ankiel and his star crossed career has probably been the best.  There’s been another uptick in the last few years, but those weren’t even part of the story.  So not much of an effect in this study.

I’ve been slowly redoing my draft databases into WAR so I’m pretty familiar with some of these issues. 

I think Sky over sold his conclusion about college hitters at least in terms of how relevent it is today.  Looking at James’ study of 1965-1985 and my studies of the late 1980s and most of the 1990s, it’s pretty clear that college players dominated from 1965-1989, but that things have been much more balanced in the 90s.

So when Sky looks at his data from 1965-2001 and shows that college hitters were the best picks and implies that may still be true, I don’t think that’s quite right.  The college advantage from pre-1990 is just so great that it swamps some of the evening out that occurred in the 1990s.  Someone in the comments mentioned Rany’s similar results to that effect.

While we’re on the topic of WAR based draft studies here’s some quick prelimary stuff from the 1987-1994 drafts.

- very productive drafts total 800+ WAR whereas weak drafts can be in the 500s

- strong years see 20-23 players exceed 10 WAR for their careers whereas some of the weak ones may be in the 15-16 range

- most players who make the majors from a draft class have 0 or negative WAR careers.  Strong drafts may see only 70 out 160, but weak ones may be more like 90.

Tango estimated that half of WAR may be pre-FA.  My recollection when I looked really closely at WARP data was that it was closer to 2/3.  That may change though as the WARP baseline distorted so much.

Sky has part 2:
http://baseballanalysts.com/archives/2009/06/the_draft_and_w.php

Philly, talk about a lucky guess:

As it turns out, a player’s pre-free agency WAR is almost exactly half of their career WAR.

And this interesting tidbit:

This indicates that teams are now drafting more efficiently - high picks have a higher WAR than in years past, while low picks have a lower WAR than in years past.

Though I wonder if having more jobs available (but more competition) somehow makes it easier to get more WAR?

As for the college/HS, I presume more HS players are going to college than going to MLB’s minor leagues?  There is a selection issue to contend with here. 

it appears highly drafting pitchers is an even riskier proposition today than when the draft began.

Fascinating.

As you can see the #1 overall selection has about a 2 in 3 chance of making a positive impact on a major league club. The probability for a decent impact of 10 WAR is 54%. The probability of a 30 WAR career, which is a career which probably includes a couple of All-Star appearances and several solid seasons is 29%

If you want this summarized:
chance of 0 (or less) WAR equals
chance of 1-29 WAR equals
chance of 30+ WAR

And this is for the #1 overall pick!

That is, the chance of getting absolutely nothing from your #1 overall pick is about the same as he’ll have a modest all-star career (I dunno, say David Wells?).

If you go down to the #10 or worse pick, it gets far worse.

Great research by Sky.

I don’t have access right now to my stuff to do a quick comparison.  Most of the conclusions seem right on to me.

A couple things that jumped out - the assumptions for first 6 years are too low.  At 130 AB and 50 IP, he’s catching a decent number of partial seasons as full seasons and as a result including a partial transition season in lieu of a 7th season of more established performance.  For a modern example, he’s counting Weiters as 2009-2014 when the O’s will actually get all of 2009-2015.  I’m not sure it matters that much, but it will under sell some players.

The other thing I like to see in these studies is more acknowledgement of the difficult interplay between scouting/drafting and player development.  Every conclusion here is in terms of teams drafting more efficiently.  I do beleive that is true, but some of this effect is that teams now do a better job of developing elite amateur talent.  That’s real inside baseball and probably impossible to quantify though.  But I’ve long beleived that HS players would continue to gain ground on college players largely because the gains in player development would have more dramatic effects on the younger players.  I do think that is part of the reason that HS players are closing the gap.

I’d also point out that the current signability craze is acting against the increasing efficiency model (at least as determined by draft slot location).  That attests to the importance of knowing bonus data as the drafts from the 2000s start to become part of the usable data set for draft studies.

Thanks for the updated link Tango.  Philly, you make some good points.  Absolutely I would believe that part of the reason for more recent players racking up additional WAR is that teams do a better job of developing their players, keeping them healthy, etc.

The signability issue definitely poses a problem as time goes on.  Although the problem is minor now, if signability dramatically alters the order of picks in the future, that will surely have to be accounted for in studies of future years.

Rany did some work as well:

http://www.baseballprospectus.com/article.php?articleid=15295

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I also proposed a different scheme a while back:

http://www.insidethebook.com/ee/index.php/site/comments/value_of_an_nhl_draft_pick/#3

My best fit is:
7/(pick + 6)

So, a #1 pick is at 100%, a #8 pick is at 50%.  A #3/#4 pick is at 75%.  A #22 pick is at 25%.

It should also be noted that Rickey Henderson, Johnny Bench, Robin Yount, Ken Griffey Jr, Gary Sheffield, and Eddie Murray are part of the youngest group.

If players like Rickey Henderson, Johnny Bench, Robin Yount, Ken Griffey Jr, Gary Sheffield, and Eddie Murray had decided to do an Albert Pujols and go to JuCo for a year how much would that have changed the study?