The Orioles' 2018 debacle has been a long time coming

[PaulFolk]

Thanks, all, for reading and enjoying. (Well, maybe "enjoying" isn't the right word when discussing the Orioles' complete organizational collapse.) Good discussion going on here.

[now]

5 hours ago, nadecir said:

Here is a good example of how analytics should work in regards to valuing a player, specifically Chris Davis at the time he was signing a new contract.  This was published in SI in Jan 2016, right after his new deal was signed.

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Orioles overspend with poor long-term investment in Chris Davis

By Cliff Corcoran

January 16, 2016

In reality, however, the Orioles likely lost regardless of whether or not Boras and Davis actually got them to increase the value of their offer. As I wrote a month ago, Davis is very simply a bad investment. Running Davis through our What Is He Really Worth? formula produced a projected value comparable to the contract Davis received ($157.8 million over seven years), but that projection was based on a typically gentle decline which I do not believe that Davis is likely to have. Again, Davis is a player entering his age-30 season who had just two above-average major league seasons in his 20s, and those two seasons did not come consecutively.

Because those above-average seasons were two of Davis’s last three seasons, our 5/4/3 weighting of those three seasons (five times his 5.2 wins above replacement, baseball-reference.com version, from 2015, four times his below-average 1.8 bWAR from ‘14 and three times his 6.5 bWAR from his breakout ‘13 campaign) generate an encouraging 2016 projection of 4.4 wins above replacement. Projecting a slow and steady decline from that point would result in Davis being clearly above average in each of the next five seasons (making it six straight above-average seasons) from the age of 30 to 34 and compiling 18.3 bWAR from his age 30 to 36 seasons after accumulating just 14.7 bWAR in his 20s.

To correct for what would be an extreme outlier of a career path, I ran Davis through the system a second time, accelerating his decline. I did this not only because that career path seemed extremely unlikely, but because there was something about Davis’s game that gave me good reason to expect a more dramatic decline: his contact rates. Davis made contact with just 64.4% of the pitches he swung at in 2015 and his career contact rate is just 66%. None of the other nine men to hit 40 or more home runs in 2015 (Davis led the majors with 47) made contact less than 69% of the time they swung the bat last year. Fielder, the most free-swinging of the three stars Boras used as comparisons for Davis, made contact with 76% of the pitches at which he swung at prior to reaching free agency. My own search for a similar combination of big-time power and poor contract rates turned up a far more appropriate and alarming comparison for Davis: fellow big-money first baseman Ryan Howard, whose contact rate through his age-29 season was an identical 66%.

https://www.si.com/mlb/2016/01/16/baltimore-orioles-chris-davis-free-agency-new-contract

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Note: even this pessimistic analysis of the Chris Davis contract by Cliff Corcoran of SI was badly incorrect; it was far too optimistic.  But the prognostication in general about Chris Davis was right on.  MLB teams are doing this kind of analysis on a regular basis for potential player acquisitions and new contracts.  This gives you a feel about how specific analytics can be used about a single player.  And why some teams avoid some players like the plague, and others value particular players more than others.

 

 

 

Thanks for that detailed response on CD, @nadecir. It does seem incomprehensible that the O's wouldn't be on par with the analytics of SI. I note some subjective or creative tweaking by Corcoran, which I guess is the kind of thing the two sides do to the data in arbitration hearings. No doubt Davis's agent tweaked data for their case, too. I also presume the O's weighed other factors, perhaps more important to them at the time? Good guy, clubhouse, good defense, gate draw, the appeal of big-time power, loyalty, etc. Not defending them... just trying to figure out how it all went down. Paul did a good job of laying out both sides to the other "wrong horse" picks too. 

[nadecir]

14 hours ago, now said:

Thanks for that detailed response on CD, @nadecir. It does seem incomprehensible that the O's wouldn't be on par with the analytics of SI. I note some subjective or creative tweaking by Corcoran, which I guess is the kind of thing the two sides do to the data in arbitration hearings. No doubt Davis's agent tweaked data for their case, too. I also presume the O's weighed other factors, perhaps more important to them at the time? Good guy, clubhouse, good defense, gate draw, the appeal of big-time power, loyalty, etc. Not defending them... just trying to figure out how it all went down. Paul did a good job of laying out both sides to the other "wrong horse" picks too. 

The analysis by Corcoran in 2016 was pretty good at forecasting exactly what happened to Chris Davis.  In another earlier article about Chris Davis, Corcoran says:

"The question then becomes: If Davis is struggling to make contact now, when his bat speed is near its peak, what happens when his bat inevitably slows down with age? The answer is unlikely to be a gradual decline and more likely to be a quick collapse in his value "

If the Orioles would have taken his other piece of advice in early 2016, fans would be feeling a bit better about the Orioles future today:

" If the Orioles were dead set on spending $150 million this off-season, the best way to spend it would have been on an extension for Machado, whose age-26 season is on the other side of his scheduled free agency. "

Your comment about the subjectivity of the analysis from Corcoran gets to the important point about analytics

Data analytics is a science.  Baseball executives today have an enormous amount of data at their disposal to use to run their organizations.  The key to success is to collect all the data you can and analyze it to find meaningful patterns that allows you to forecast better.  What data is important, and what data should be ignored; that's the heart of regression analysis which forms the foundation of this subject.  One can only reasonably answer these questions by having experienced analytic personnel in your organization using state of the art tools.  This requires significant investment.   This foundational investment is necessary in Major League Baseball in order to be competitive today. 

A team can certainly be successful for a few years by using traditional methods to assign player and prospect value.  But in the long run, teams with vast experience with analytics, more data, and better tools to analyze the data will invariably come out better than the other teams with little investment in analytics.  It's true in baseball, and it's true in most businesses today.