How Can the Twins Front Office Regain Twins Fans Favor?

23 hours ago, ashbury said:

I'm pretty unimpressed by the outward evidence of analytics, for this supposedly analytics-heavy front office. 

Say more about this please...I would love to hear your perspective on this.

18 hours ago, ashbury said:

That's pretty open ended.

Let me counter with something that may seem irrelevant, to try to get on the same page together.  What do you think of this 80-second clip of Rocco discussing a computer game?

https://www.mlb.com/video/baldelli-on-using-ootp-baseball

Separately, Rocco has been quoted concerning that game, “It’s more real than unreal, I’ll tell you that.”

Does that fairly represent your impression of the organization's view of Out of the Park, that it's a useful tool?

Not a trick question or a Gotcha.  I want to understand if my perception is correct about this.

 

Interesting clip. I had never seen that from him. Teams were struggling during Covid to keep front office, scouts, coaches, etc engaged. I'm guessing this was supposed to be a fun way to keep people involved, ask questions, and possibly do some fun/interesting research projects. With the Dbacks we were scouting KBO games. I'm not totally sure what to make of it. I'm guessing it was more team building. Is this what you're thinking?

On 10/6/2022 at 8:40 PM, ashbury said:

Before breaking it down with analysis, first look at the big picture.  b-r.com splits numbers for Twins and for MLB as a whole.

PA with RISP: Twins 1484, MLB 44760

R with RISP: Twins 471, MLB 14969

Ratios of these: Twins .3174, MLB .3344

With runners in scoring position the Twins were pushing across significantly fewer runs per opportunity.  Had they held the same ratio as MLB as a whole, 25 more runs might have scored.  That's about 2.5 wins over the course of a season. 

That there is problem seems evident.  It's a matter of semantics whether throwing away 2 or 3 wins is dreadful.  But it needs fixing.  (I hope nobody is engaging in a strawman argument that anyone's saying any particular problem is the ONLY problem.)

What the cause is, may be hard to pinpoint.  You suggest it's not simply the batting average.  I'm not so sure.  Batters usually have better numbers with RISP than with bases loaded, for reasons probably not worth dissecting here.  MLB wide, BA with bases empty versus RISP were .235/.253.   Our Twins notched .236/244.  Is that significant?  Given the rather large numbers for a team or a league over a full season, not really SSS, I'm inclined to believe yes.

Slugging average, likewise.  MLB was .383/.409 (empty vs RISP), Twins were .380/.385.  When they hit, it wasn't with the usual bump in power, with runners were on 2nd or 3rd.  Don't know why.  But it seems significant.

Maybe it's not all on the batters themselves - could be slow baserunners?  This team frustrated us with their running, just by the eye test.  Perhaps the run scoring numbers are confirmation of the eye test.  I don't know quite how to separate that out, with aggregate figures from b-r.com.

 

also the Twins had 8 fewer opportunities with runners in scoring position then the average team as well.  We need more runners in scoring position too.  (We should be striving to be well above average to be a winning team).  44,760/30 = 1492 PA per team average.  

23 hours ago, ashbury said:

Okay, good.  You asked me about my perspective, and I wasn't sure how to address that, but OOTP plays into it.  As background, I'm retired now, but spent my career in a branch of analytics used in a wide variety of industries; my work started on the technical side but I interacted with those industrial users and got a smattering of how those analytics software products were used by airlines, forestry, petroleum, military logistics, financial portfolios, etc, and wound up eventually in product marketing for such products.  So, I'm gonna have my opinions, as an outsider looking in on baseball when they start talking up analytics, not so different from a high school baseball coach who thinks he knows how major leaguers operate.  

I believe OOTP got significant consulting from baseball insiders from its earliest design.  So when they have added features involving player personalities, injury risk, and so forth, it makes me go "hmmm".  Analytics isn't always about developing formulas that result in a final number to 5 decimal digits.  It can be as simple as sorting into "red" versus "green" for what to avoid and what to go after.  OOTP's system for injury risk is about like that. 

The other thing about OOTP that strikes a chord is the thorough database it provides the person at the keyboard about each baseball player.  There's no possibility that in the real world you would have such accurate insight into player scouting forecasts, to say nothing of personalities and so forth, and I never forget that it's a game, But the presence in the game suggests to me that top-notch analytics minds are thinking along those lines; even when the data is shaky, you can do some analytics with it, and the results may tell you where you need to invest more resources in getting better data (and where to not even bother).  Give me a database, and I'll worry about sharpening up the data that populates it, incrementally.

Baldelli's clip talking about OOTP may not imply that baseball teams literally use it as a roster building tool.  But I expect that what's seen in OOTP reflects a synthesis of how teams organize their thinking, nothing more (but that's a lot).  It's why I asked first of your impression of Rocco's comment.  If you thought OOTP is trash, there'd be little common ground for discussion.

OOTP "trained" me, in the sense of doing well in their game, to pay close attention to injury risk.  My teams do better when I maintain a bias toward always improving the overall risk of injury on my current 40-man roster or even prospects.  I trade off the riskier guys while they still have value.  Can a team know what the injury risk is for some other team's player?  I don't know, but the feature being in the game leads me to believe some analytics experts think they can - always with the proviso that the risk assigned to a player is never exact, always a range - any player can get hurt, but the chances may be greater with some than with others.

So, finally.... this is why the trades for Paddack and Mahle, the trade for Gray, the signing of Bundy and Archer, taken together, baffle me.  Each trade required a trading partner, and I envisioned the Reds and Padres being OOTP players like me, seeking to recoup the remaining value of a risky player to another team willing to take on that risk.  Any individual roster move might be defensible, in the context of a full "portfolio" of lower and higher risks, just as a stock portfolio blends instruments to some acceptable level of risk and reward.  Sometimes the Twins risks have worked out to a degree, e.g. value was gotten from Bundy and Archer, at the expense of babying their arms and putting more burden on the bullpen, but even that merely achieved a meager upside.  This doesn't even touch on the apparent injury-proneness of some prospects in the pipeline (Ober, Winder, off the top of my head); does one augment that with veterans also in the risky category?  The body of work altogether suggests a strategy that I just can't understand - not even just an indifference to injury risk but a downright intentional strategy to use some sort of "secret sauce" they have to leverage more out of the riskier pitchers than other organizations know how.  And when the season is over and the excuse is, "ohhhh, teh injurieses, what bad luck!", I'm not receptive.

On my less charitable days, I blame bad analytics.  Most of the time, I just want to know more, because what I'm seeing doesn't make sense to me and I want to know why.

I don't have any visibility into the Twins FO or particularly the analytics staff.  In my career I was interacting with analytics teams in industry that were populated with PhD researchers, or MBA holders who were heavy, heavy, heavy on the quant side.  (Wall Street went through a "rocket scientist" phase where Physics PhDs were the preferred candidate to hire for portfolio optimization.)  That's my bias toward what it takes to succeed.  I would be pleasantly surprised to learn the Twins analytic team was like that, even by now under Falvey.

There are literally millions of people in the analytics world, and I'm just a guy who spent 35 year or so in a corner of that ecosystem.  If you were looking for something else when you asked for perspective, well, sorry.

 

 

I've always appreciated your posts. I find them well thought out, curious, educated, and rational. OOTP has had significant input from ML employees I believe. One of the MANY reasons I wanted to hire an employee within the analytics department was his involvement in OOTP from both the technical side and his involvement as a player. I thought there were some things we might be able to explore, verify, and implement. In addition, I agree with you on analytics being more than formulas. I would say on a foundational level it's helping you sort into "red" vs "green" as you mentioned. Just starting here is a necessity. Analytics should also help you ask better/deeper questions and lessen risk.

OOTP or any other well-constructed simulation exercise, should give you insight into risk, and also help maximize your roster construction. These simulations should aid in maximizing platoon situations and positional flexibility along with bullpen chaining.

As you mentioned, the acquisitions of those 5 pitchers together is confusing. All have injury and/or performance questions attached to them that don't play well together. I agree with you, building a team is like building an asset portfolio. You're trying to balance asset allocation, sectors, cost, risk, etc....Perhaps it wasn't the strategy, but the execution or difficulty in executing the strategy. I'm not sure. 

In the end, I do agree with you and appreciate your insight and ability to mix in "real world" experience into the game of baseball.