12/18/19

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NOTABLE TRANSACTIONS/INJURIES/RUMORS

• A.J. Puk (3:25)
• Taijuan Walker (8:00)
• Jordan Montgomery (9:55)
• Cole Hamels (12:25)

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Introduction

I thought it would be an interesting exercise today to look at fantasy baseball in a different way – profitability at the major league team level. Certainly, the better real-life clubs consist of not only more fantasy relevant players, but also of the higher quality ones.

But what else can be said about the profitability of the fantasy player pool at the team level? Does a higher spend translate to more value for fantasy owners? Does winning ball games correlate with higher levels of fantasy profitably? What can we learn from looking at player investments from this unique ball club perspective?

Let’s dive in and see …

Definitions & Methodology

For today’s analysis, I have used the same pre-season pricing and full-season valuations as in my game theory projections comparison. There are three specific quantities that are relevant here:

• $Value – This is the 2019 full season rotisserie value that each player provided this season. I use my own auction calculator which employs a Z-score methodology to generate the $Values. Standard NFBC 15-team settings are assumed (Mixed AL/NL, $260 budget, standard NFBC positions). I assume that players are only eligible at their original 2019 positions + any positions that they were expected to gain in the first 2 weeks of the season.
• $AAV – Average Auction Value – This is the average of what NFBC owners paid to acquire players during the heart of the 2019 draft season. These values come from all NFBC auctions between March 15, 2019 and March 25, 2019.
• $Profit – The difference between the $Value and the $AAV per player.

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Using the current NFBC average draft data for their 50-round Draft & Hold leagues, I’m going to put together most of an offense going at 200 or later (2 catchers because I hate myself, an infield, and 2 OF). I guess it’s just a different way to identify some sleeper/later values that I like, but hey, let’s do it!

C1 – Omar Narváez, MIL | Pick 237

Among the 21 catchers with at least 650 PA the last two years, Narváez’s 120 wRC+ in 804 PA is 3rd behind only Mitch Garver (130 in 694 PA) and the guy he replaced, Yasmani Grandal (123 in 1150). He’s a brutal framer which could cut into his playing time a bit unless they have some plans to improve him, but I’d take 400 PA with 15 HR and a .277 AVG.

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In my previous article, I compared a number of baseball projection systems for the 2019 season using a game theory approach. We looked at the profitability of each projection system in the context of simulating what would transpire at a fantasy baseball auction. We measured each projection’s successes and failures.

Several readers had approached me to further split out the resulting analysis into the hitter and pitcher components. By popular demand, I have decided to do exactly that. Today’s article will detail the analysis by its offensive and defensive elements.

For a refresher on the process and methodology, or for reference, please refer to the original post which can be found here.

Overall Results:

First, let’s quickly remind ourselves of the results of overall total profitability by projection system in 2019.

As we previously saw, ATC and Steamer were the two best overall systems according to this analysis in 2019.

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I compared the average draft position data of the first 10 NFBC Draft Champions leagues with the 2020 Steamer Projections to identify 10 of the best values going in the top 150. I just took their auction calculator rank using Steamer and compared it against their ADP. Here’s what I found (sorted by ADP – Auction Calc. difference, highest to lowest):

Dinelson Lamet | SP – Auction Calculator Rank: 52, ADP: 128

He feels like a winter riser. He was getting hyped at the Baseball HQ event in Arizona for his strikeout prowess after posting a 34% mark in his 73 IP this year. While he won’t reach as high as this Auction Calculator Rank, I think he’ll beat this current ADP, especially in the NFBC realm where pitching is always pushed up.

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Introduction

Last year, I introduced a game theory approach for comparing baseball projection systems. Today, I have once again applied the same methodology in order to evaluate which set of baseball projections excelled in 2019.

Most others who venture in such a comparative exercise make use of some type of statistical analysis. They calculate least square errors, perform a chi-squared test, or perhaps do hypothesis testing. I won’t be engaging in any of these capable methods.

Instead, I will look to determine the profitability potential of each projection system by simulating what would have happened in a fantasy auction draft. Instead, I’ll play a game.

What do I mean by this?

First, think about what happens in a fantasy baseball draft auction.

Suppose that Rudy Gamble of Razzball (or anyone who exclusively uses the Razzball projections) walks into a rotisserie auction league prior to the 2019 baseball season. Let’s say that Rudy decides to participate in an NFBC auction league. Mr. Gamble would take his projections and run them through a valuation method to obtain auction prices. He would generate a list that looked something like this …

Razzball Projected Values: Chris Sale 49, Mike Trout 45, Jacob deGrom 44, Max Scherzer 44. Mookie Betts 42, J.D. Martinez 37, Giancarlo Stanton 36, Justin Verlander 35, … , Brandon Lowe 1, Josh Reddick 1, Mark Melancon 1, etc.

In addition to the raw projected values generated by the Razzball system, Rudy would then establish a price point that he is willing to pay for each player. There might be a premium that he will pay for the top ones, and a discount that he expects to save on lower cost players. He may be willing to bid up to $46 on Jacob deGrom (valued at $44), but would only pay $1 for a $4 Jason Kipnis, etc. Read the rest of this entry »

The past three years, our Justin Mason has organized too-early mock (#2EarlyMock) drafts ahead of the next fantasy baseball season. The 15-team snake drafts have taken place each September, which means I’m recounting this about two months too late. However, with some early offseason developments and the release of Steamer’s 2020 projections, the wait at least offers the benefits of both hindsight and foresight.

There’s no such thing as average draft position (ADP) data in September, so we rolled into these drafts blind to everything but our own recency biases. The dynamic is compelling, if frequently odd, and can be difficult, frustrating, but ultimately enthralling to endure. Ideally, my commentary here will not painfully boring and might provide insight into my “process” on a microcosmic level.

My draft was not without fault, but I do feel good about it. I’d like to think that means something, as someone highly critical of his drafts and rarely feels truly “good” about a roster I’ve compiled. I don’t play in many deep leagues, so 15-team drafts routinely jack me up. Somehow, I feel like not having ADP information actually benefited me; I feel like I scripted my draft more cogently than usual. But also, it’s fairly clear where I made suboptimal decisions. Overall, I don’t think it turned out half-bad, especially for a 15-teamer.

The results of my draft follow, and the minimum (“Min”) and maximum (“Max”) pick information comes from Smada’s ADP information compiled from all six #2EarlyMock drafts.

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Last week, I looked at the largest auction player bargains of 2019. These were the players who were highly profitable after considering their opportunity cost of acquisition. We defined the bargain amount as:

$Bargain = $Value – $AAV

We defined $Value as the accumulated 5×5 full season rotisserie value of each player, and $AAV as the average auction cost to purchase the player pre-season. We make use of the NFBC Average Auction Values which are readily available to us.

For the full methodology of how these player bargains are calculated, please refer to my introductory post.

Today’s attention will be directed to what I refer to as the value drainers. These are the largest “rip-offs” of 2019 – i.e., the players who earned the most negative profits for fantasy owners on a full season basis (net of their auction price). Read the rest of this entry »

Every year, as the season comes to a close, I put together a series of mock draft with industry analysts to start getting first thoughts on where people might end up in drafts for the next season. This year I ran six mocks during the month of September with interesting results. All drafts were 15-team leagues with one catcher standard formats. Read the rest of this entry »

Winning Fantasy Baseball is All. About. Value.

Introduction:

Several years back, a friend of mine was preparing for his fantasy baseball auction. He asked me a simple question –

“How much is Lorenzo Cain worth according to your projections?”

That was a straightforward question for me to answer. I ran the ATC Projections through my valuation model. I set the league parameters to match his specific league settings, and I generated a value for Cain of $18.

A few days later, my friend came back to me and said,

“Ariel, I bought Lorenzo Cain at my auction for $18! Isn’t that awesome?!?!”

I responded “No, that’s awful. If Lorenzo Cain is worth $18, you need to only pay $14 or $15 or $16.”

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