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# The Disappointing Diamondbacks Offense

Who caused this ?

When team’s construct rosters they have a baseline of expectations from each of the players they choose to be on the roster. How they arrive at those expectations varies of course from organization to organization. However they all use some form of projections to set their baseline. Some teams may use sophisticated statistical models to forecast performance and rely heavily on them when constructing rosters. Others may use more basic forms of projection, and rely less on statistical models and more on scouting and coaching input. Regardless of where an organization may fall on that spectrum however, they are all projecting something out of their players.

The projection systems that are available publicly to us at Fangraphs are useful in setting up a baseline of expectations. They don’t have medical or scouting input, but they have an ever increasing level of sophistication built in as more and more information becomes available.

What I am attempting to do here is quantify which performances helped and hurt the Diamondbacks offense this year. My approach is to measure against EXPECTATIONS. Knowing that Paul Goldschmidt is going to out produce Chris Owings doesn’t really help us. They are counting on Paul to produce at a certain level. And they know going in that Chris is not going to give them Goldy level production. What matters is how much over or under expectations the player produced.

The stat I’m using is wOBA. If not familar with wOBA I urge you to click on that link. However it is based on individual events which are given linear weights values and added up and converted to a rate set up to the same scale as On Base Percentage. wOBA and OPS have roughly the same correlation to team run scoring.

Correlation is a statistical tool that measures how closely one set of numbers relates to another set. Correlation runs from -1 to 1. The closer you get to either extreme the closer the two sets of numbers are tied together. The closer the number is to 0 the less likely one number will tell you anything about the other. If the number is negative it means that when one number goes up, the other goes down. If the number is positive they both rise or fall together.

Measures such as batting average simply lag far behind. It should be noted however that despite the claims at Fangraphs and Tom Tango, it turns out that OPS correlates just as strongly to team run scoring. You can read about that here

The reason for using wOBA in this post is simple. It’s better suits my purpose to judge the actual impact of over or under performance against projections because it can be converted to runs, or in this case wRAA (weighted Runs above average). The description and formula for doing so is in the wOBA link above I urged you to read.

So....with all of that out of the way......lets take a look .

NOTE: I use the actual PA’s of the player, and convert the projected wOBA to wRAA. Then I take the actual PA’s and convert the actual wOBA to actual wRAA. Comparing the two wRAA numbers then allows us to see the actual impact of that players over or under performance. The table is sorted from negative to positive, so as to help answer the question in the article heading. Don’t worry about the rounding “errors”

There probably aren’t any huge surprises here. We know already who have had good and bad years. But the above table helps to quantify and contextualize the actual impact on the team offense. Owings, Lamb, Avila, Dyson, and Souza all managed to put a very large dent into the team offense this year, despite the fact that none of them even reached 300 PA.

The second half slump of AJ Pollock unfortunately more than offset his hot start, and Jon Jay remains something of an enigma. Deven Marrero managed to rack up -8 wRAA in just 85 PA. Impressive.

Better than projected years by Peralta, Descalso, Ahmed, and even Goldy were simply not enough to offset the massive under performance of the guys highlighted in Red and Yellow.

Now what about going forward ? Well we can check out the rest of season projections to get a clue. Some players have seen their wOBA projections drop a great deal compared to the pre season. Others have gone up.

My personal opinions:

I would non tender Chris Owings. I don’t think he is ever going to be a good enough hitter to justify more than 100-200 PA in a season. He’s too expensive for that kind of role now as an arb 3 player, due to make close to 4M.

Alex Avila may have passed the point of no return with his K rate. (see graph). I think they need to move him for whatever they can get and save the 4M he will make in 2019.

Jake Lamb , despite his down season is still going to be a rather expensive Arb 2 guy due to 2016-17 HR and RBI totals. He probably would be tough to trade and get much in return, until teams see how he bounces back from shoulder surgery. But if they felt they could resign Eduardo Escobar at a reasonable price they could look to trade Lamb for low level prospect simply to save his 5 Million and use that towards EE’s new contract if they wanted to try to keep him.

Dyson is signed for next year and if he recovers from his groin injury, will still be viewed as a viable 4th-5th outfielder/defensive replacement. While I hope he won’t hit .183 again, I don’t expect any more than a .240 hitter with a .280 wOBA next year.

Steven Souza Jr. they just have to hope he rebounds.

I expect some significant roster turnover one way or the other. Dave Magadan is probably on the hot seat too. Team’s don’t collapse like this without “consequences”