Previously, I uncovered potential undervalued speedsters and power bats by comparing the Steamer projections to the current NFBC ADP. The exercise now continues for batting average.

In 2018, there were 43 qualified players with least a .280 batting average. There were 32 players above the .290 mark, and 16 above .300. Mookie Betts led all of baseball with a .346 BA, followed by his teammate, J.D. Martinez who hit for .330.

Prospective projections though, are typically more conservative. Steamer only projects 11 regular players to bat over .290 in 2019, and only 5 players to hit for at least .300. For the following analysis, I will focus on all players with a Steamer projection of a .280 BA or more. That should give us a nice group of players who can greatly help your team’s batting average in upcoming fantasy season.

For these draft value comparisons, I look at:

• The player ranks as computed by the FanGraphs Auction Calculator with Steamer projections (standard NFBC 15 team roto league settings).
• The current NFBC ADP (of Draft Championship leagues from January 24 to present).

Below are the players selected within the top 30 ADP, who also have a Steamer projection of at least a .280 BA:

These 14 players are projected to provide a nice batting average base for your draft. Juan Soto, a 2^nd year player, just missed this list at an ADP of 31.

Below are all of the remaining players in the draft pool with a Steamer projection of at least .280 BA:

The players above are once again ordered by their difference in Steamer Hitter Rank versus ADP Hitter Rank. Differences highlighted in GREEN are the players who are going later than their Steamer values indicate that they should; differences in RED show the overvalued players.

What is nice about this list, is that it contains quite a diverse range of player types and situations. Included in the player set are:

• Injury bounce back players
• Speedsters
• Power hitters
• Catchers
• Rookies / Top Prospects
• Part time contributors
• Steady Year to Year players

The fact that these batting average contributors are so diverse in their makeup, might make it easier for you, the knowledgeable drafter – to focus on average before your competition contemplates the task. Every year, I see many fantasy players focus on only accumulating counting stats. Batting average counts nonetheless – and needs to be addressed. You will also find it easier to collect a low BA / one category contributor later on, if your batting average kicked off on excellent footing.

Nelson Cruz and Jose Abreu were previously covered in this series, but here are a few other players from above that I would like to highlight:

Ketel Marte (Steamer Hitter Rank: 88, ADP Hitter Rank: 126, Overall ADP: 207)

Ketel Marte flashed a touch of power last year, hammering 14 round trippers. I have always viewed Marte as more of a speedster than anything else; his low 6 stolen base total last year was somewhat surprising to me.

Looking at the power, his HR/FB rate has been ticking up in recent years. It is one peripheral reason that he may be able to sustain double-digit homers.

As for his batting average, which has hovered around .260 in the past few seasons – his BABIP was somewhat lowish for a player with excellent speed (.290 in 2017, .282 in 2018). Steamer is projecting a jump all the way to .280!

The increased batting average projection, as well as a jump in his walk rate in the 2^nd half of last season – should lead to more opportunities for stolen bases. He currently projects to be the leadoff hitter in Arizona, and any increased volume of plate appearances would surely help his counting stats.

My word of caution is in his platoon splits. He is a far better hitter vs. left-handed pitching than vs. right, which could ultimately lead to a good-side platoon split (possibly with Jarrod Dyson taking away some of his ABs?).

He is not my favorite player on this list, but if you buy Steamer’s batting average upside projection, he is a solid mid-to-late round selection.

Adam Eaton (Steamer Hitter Rank: 106, ADP Hitter Rank: 129, Overall ADP: 210)

Eaton, who is being drafted right around Marte in the early 200s – is the better player from a pure batting average perspective. Eaton has eclipsed the .280 mark in each of his prior 5 seasons in the majors. With his batted ball profile improving throughout last year (GB% down 6%, LD% up 11%), he is a good bet to achieve that for a 6^th straight season.

Long removed from his 15/15 destiny, Eaton’s plate skills are still excellent. He should still supply fantasy owners with a good source of runs if he bats at the top of a very good Washington lineup.

Health is the larger concern for Eaton, as he hasn’t managed to stay on the field for a full season since he played on the Southside of Chicago. The Nationals are loaded with capable outfielders, and I worry a bit for Eaton losing playing time to others.

In terms of boosting a team’s average, you could do worse with a 15^th round pick according to Steamer – who projects a return to double digit power and steals.

Justin Turner (Steamer Hitter Rank: 55, ADP Hitter Rank: 72, Overall ADP: 113)

Justin Turner is a player that I call a “Low Variance Projection.” That is, all of the projections I look at come close in their 2019 projections.

20 HRs, 4 SB, ~.295 BA, 75-85 Runs & RBIs.

With an 11.5% strikeout rate over the past two seasons, a mid-20s LD% rate, a ~30% GB% rate, and a .319 career BABIP – His batting average looks to be rock solid. While it is tough to pencil in a .300+ BA, bet the over on .285+.

Turner always seems to be undervalued at fantasy drafts, but he shouldn’t be. He is a 4-category contributor … he does everything other than steal.

There is risk attached with Turner – health risk. He only played in 103 games last season. At age 34, he could ultimately lose a few at-bats to Max Muncy or to others, as the Dodgers have many options in the infield.

Jose Peraza (Steamer Hitter Rank: 62, ADP Hitter Rank: 56, Overall ADP: 90)

I refer to Jose Peraza as Starling Marte Lite.

Let’s dive into Peraza’s batted ball profile and contact/plate patience:

Jose’s walk rate is ticking up, and his strikeout rate was nicely down last year. The mid .280s BA that he hit last year can absolutely be sustained.

What about his power? His groundball rate has been moving downwards, and it has translated into a corresponding fly-ball uptick. Peraza hit 14 HRs last year, 10 of which were in the 2^nd half alone. Mid to high teens power is very possible for Peraza.

And his speed? As good as ever – you can bank on the mid-20s stolen bases, or more … if the plate skills persist.

Peraza also has a better lineup surrounding him, so expect a small climb in run production counting stats to boot.

Jose Peraza is not a bargain according to Steamer; he is going roughly in the spot that Steamer suggests he should. However, since speed is at a premium once again in 2019 drafts – the fact that he can be acquired at par value means that he is nicely priced. If you miss on someone like Starling Marte earlier on, Peraza is an excellent fill-in with upside.

Other Assorted Notes:

• Buster Posey is shown as the top batting average bargain. As a catcher though, the magnitude of his bargain may not be as high as indicated here. First, as I don’t know exactly how the replacement level for catchers are set in the FanGraphs Auction Calculator; it is possible that the catcher bump may be too great. However, even if the theoretical bump is accurate – the market for catchers may be depressed depending upon your specific league tendencies, which would skew this analysis.
• As batting average is not a counting statistic, players who accumulate more playing time are more beneficial to your roster. For example, you will get more BA benefit from a player with 500 ABs and a .290 BA, then from a player with only 250 ABs and a .295 BA. Some of the bottom players on the list above (R. Tapia, W. Astudillo, J. Martinez, E Nunez, G. Hampson) won’t have as direct of a full season impact as the others on the list would.

You should buy an ace.

The fantasy landscape has changed dramatically over the past few years. Just a half decade ago, a mid-$20s bid at a mixed league auction would buy you a top pitcher. $30 was unheard of … for any pitcher. A non-hitter in the first round was blasphemous. Pitching was thought of to be too volatile, and far too risky to roster at such a considerable cost.

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Introduction:

The catcher position in 2019 is the weakest offensive position in our beloved fantasy baseball competition. It is no secret. Every reasonably astute or semi-intelligent fantasy player is aware of this phenomenon. The more experienced competitor is also cognizant that the position has been getting even weaker over the past few seasons.

Unlike the middle infield positions which I have discussed here, it is clear that the catcher player pool demands a correction to account for “positional scarcity.” A boost is required to the otherwise dreadfully low values that the position would manufacture on its own.

This may be elementary to some, but the idea is as follows:

Using the current ATC Projections with my personal auction valuation method (a Z-Score method similar to the FanGraphs’ Auction Calculator) – the above auction prices represent what a catcher would be valued at assuming that we didn’t make any corrections to offensive positions, i.e. no positional adjustments. I assumed standard NFBC league settings [15 team, 5×5 mixed roto, 9 P, 14 H as per NFBC rules, which include 2 catchers].

In an NFBC auction, each team must select two starting catchers. The math works out so that with 15 teams, there must be a total of at least 30 starting catchers selected.

The 20^th catcher, according to the above, is worth -$4.3. That is, someone should pay you $4.3 to take him off of their hands! Obviously, one cannot buy a player at an auction for -$4.3, yet someone must buy the 20^th ranked catcher at a price of at least $1.

It is about marginal value. It is about the privilege not to roster the 30^th best catcher. The catcher valued at -$4.3, is still $3.2 better than the 30^th catcher valued at -$7.5. That dreadful (30th ranked) catcher still has to be … unfortunately … purchased by someone for $1.

One very simple “back of the envelop” method to adjust catcher prices would be to set the 30^th ranked catcher to be valued at $1, and to price all other catchers by adding $1 to their marginal cost above #30.

Since the 30^th ranked catcher was valued at -$7.5, this simplistic correction adds $8.5 to all catchers. This quick procedure is a bit more elementary than the theoretical way to do it – but it isn’t that far off. It is certainly a method.

Z-Scores:

A bit of background on general auction valuation by the Z-Score method:

Z-Scores, often referred to as standard scores, are the kernel of a widely popular auction valuation method for fantasy. The heart of its engine calculates the following value for each player, by scoring statistic.

Where: Z[i] = Player i’s Z-Score;  X[i] = Player i’s Category Stat;  X-Bar = Average Stat for the category;  S = Standard Deviation for that category.

To calculate your player/category’s Z-Score: Take your player’s stat, subtract the average stat, and divide by the standard deviation across the player pool for the stat. Repeat for all scoring categories – and add them up to get a total Z-Score.

Let’s look at an example of what the calculation of total Z-Score looks like. Let’s assume a standard 5×5 roto contest for 3 teams only, each having to select 1 catcher apiece.

Justin Collette here is the best player of this fictitious set, with Jason Sporer as the worst.

The key to adjusting catcher valuations begins with assessing the total Z-Score of the lowest ranked [starting] catcher that must be selected. The term for the “lowest catcher that must be taken” – is the replacement level catcher. That player here is, Pike Modhorzer.

Modhorzer, the 3^rd best catcher – sets the replacement level at a Z-Score of -1.2. The theoretical Z-Score adjustment to make [along the lines of the adjustment in the introduction], would be to add 1.2 to all catchers, thereby setting the adjusted Z-Score of the replacement level catcher to zero.

Without getting into the math [which Zach Sanders explains in a 2011 post found here], the adjusted Z-Scores are then converted into auction dollars – with an adjusted Z-Score of 0 becoming a $1 player.

Historical Catcher Z-Score Trend:

I mentioned above that the catcher position has become exceedingly weaker in recent years. This is evident in the following chart:

The figures in the body of the chart represent the historical Z-Score levels for replacement level catchers, for various league types/settings. The table was calculated using final MLB stats for prior years, current ATC Projections for the 2019 season, and a Z-Score based method of valuation.

League Formats:

• NFBC – National Fantasy Baseball Championship – 15 Team leagues with 14 hitting slots, of which 2 are catchers.
• TGFBI – The Great Fantasy Baseball Invitational – Although the contest in 2019 will be aligning itself with the NFBC format, last year’s game featured 15 Team leagues with 14 hitting slots, of which 1 was a catcher.
• RTS – RealTime Sports – Leagues have 10 teams, 14 hitting slots, of which 2 are catchers.
• HOME – Home League – A home league that I play in which features 10 teams, 14 hitting slots, but only 1 catcher.

Glance at the progression of values in NFBC from 2016 to 2018. The replacement level declined from -6.33 to -6.26 to -6.71. The HOME league similarly sunk from -4.60 in 2016 to -5.43 in 2018. That is quite a change.

For 2019, ATC projections are indicating that the slide will continue. The HOME league, for example, is showing a horrific -6.97 replacement level, a 1.5 drop from 2018. Seven standard deviations below average [in the aggregate] is atrocious.

My colleague Jeff Zimmerman, similarly pointed out the dreadfulness of the catcher position in a recent article entitled “Catchers … What a Dumpster Fire.”

All of this would suggest a sizeable adjustment for catchers. At an auction/draft table – we always observe a hike in catchers’ prices, but we don’t always exhibit it to such an extraordinary level.

Adjusting Catcher Values:

So, what is the appropriate adjustment to make for catchers?

There is no perfect answer to the question above. The experts do not fully agree. Most fantasy players tend to apply a heavy adjustment. Earlier this winter, I had a conversation on Twitter with Razzball’s Rudy Gamble who suggested that there shouldn’t be much of an adjustment at all.

The basic options are as follows. Should we:

1. Adjust the catcher auction values fully to set the lowest ranked starting catcher at $1? [We would do this by the fundamental process described above]
2. Make no positional adjustments, and leave the catcher values alone? [Most will be purchasing a catcher valued negatively]
3. Do something in the middle? If so – what?

I believe that in theory, it shouldn’t matter. Optically, we are best generating prices somewhere in the middle to help discover draft bargains.

Let’s look at what the market paid for catchers last year, in comparison to our adjustment options [after converting Z-Scores to Dollars]. For 2018 market value, we will use an average auction value (AAV) from a set of actual NFBC online auctions which Todd Zola of Mastersball had provided.

Perspectives above:

A) Full formulaic Z-Score catcher replacement level adjustment.

B) The Average Auction Values in 2018 for catchers.

C) No positional adjustments.

Other than the top catcher, you can see that the market did not pay the fully adjusted price. Had you valued players as in (A), you would consider buying two expensive catchers, because catchers appear as large bargains. Had you valued players as in (C), you wouldn’t want to spend any money on catchers. Both approaches are extreme and are flawed.

To find the catchers generating the greatest relative discounts, one should value catchers akin to the way the market does. Only then, can you realize which are undervalued. Setting a similar perceived optic can lead to the capitalization of a present market inefficiency.

So how do we configure this?

The method that I am suggesting today involves setting the appropriate replacement level Z-Score. In the above, the “No adjustment” replacement level was -3.92. The “Full adjustment” level was -6.43. There is some Z-Score value that is more appropriate, given the observed market curve.

Above are computed auction dollars calculated using a variety of underlying historical Z-Score adjustments. 2017’s replacement level was at -6.26, while back in 2014 it was -5.63 [we saw the magnitude of the historical slide above].

Which curve should we select?

At the very top, market prices are best fit by the fully adjusted curve. The next few catchers are fit best by the 4-year historical average Z-Scores. The bottom of the curve is fit best by something in between the 4-year average, and the year 2014 curve.

The takeaway here, is that the historical catcher replacement levels provide a better fit to the market than the fully adjusted Z-Score method. Although the 4-year average curve fits best overall, I suggest to use the 3-year average one. With the 2017 Z-Score close to the 3-year average, we can see that replacement levels have somewhat stabilized. The 4-year average contains the 2014 season, which was considerably stronger for catchers, and an outlier for our going-forward purposes.

The next step would be to use the -6.22 implied replacement level Z-Score for the catcher adjustment, and subsequently converting to auction dollars. Had we applied this suggested adjustment in 2018 – on average, we would have yielded catcher values approximately $1 lower than the fully adjusted method [and about $8.5 higher than no adjustment].

2019 Adjusted Catcher Values:

It is yet too early to fully see how NFBC players are pricing catchers. For now, let’s apply what we have learned to the projected 2019 catcher pool:

With catcher values plummeting further this year, the selected 3-Year average curve now provides something closer to a $2.5 difference to the fully adjusted Z-Score method [a $7 bump from unadjusted values]. That delta sounds reasonable to me; it jives with the fact that the catcher pool has deteriorated this year.

Rudy Gamble makes a smaller adjustment to catchers. Without going into his math, his catcher bump comes out to about $3 off of unadjusted values. Here is a brief summary for 2019:

I hope that you have found this discussion of adjusting the 2019 catcher values constructive and insightful. I am interested to hear your thoughts on both the method and results. What will you be using for your auctions/drafts this year?

Last week, I uncovered potential undervalued speedsters by comparing the Steamer projections to the current NFBC ADP. Today, I will go through a similar exercise for power.

In 2018, just three players launched at least 40 round trippers (K Davis 48, J.D. Martinez 43, J Gallo 40). Eleven additional players smacked at least 35 dingers, and all together there were 25 players who amassed at least 30 homeruns. Let’s dive into the players with a HR projection of 25+.

For these draft value comparisons, I match:

• The player ranks as computed by the FanGraphs Auction Calculator with Steamer projections (standard NFBC 15 team roto league settings).
• The current NFBC ADP (of Draft Championship leagues from December 15, 2018 to present).

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Unless you plan on attempting to punt categories at your 2019 draft, at some point, one must acquire stolen bases. If you plan on completely ignoring the SB category – you can stop reading this article now. But for the rest of us, here is a look at where some potential bargains for speed may present itself in drafts.

For these draft value comparisons, I look at:

• The player ranks as computed by the FanGraphs Auction Calculator with Steamer projections (standard NFBC 15 team roto league settings).
• The current NFBC ADP (of Draft Championship leagues from December 1, 2018 to present).

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Introduction:

Today, I will introduce a game theory approach for comparing baseball projection systems. The day’s venture will not be a typical statistical analysis. I won’t be using any Chi-squared tests, nor will I calculate Type I or Type II errors. I won’t be evaluating MSEs or the like.

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?

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The MLB playoffs are now upon us. We’ve had back-to-back one-game division title games! We’ve got a statcast broadcast! Hey … even hugs are a-plenty this postseason!

Just a reminder … I am recapping my bold predictions for 2018. You won’t see anything like “Giancarlo Stanton will hit at least 25 homeruns” – that would have been too easy a prediction. Sure, I could have filled up my list in March with much more likely calls to boast that “Ariel Cohen got 50% of his predictions right!” But that isn’t the point here. I don’t expect to get most of these correct.

The aim of the exercise is to choose a few unlikely outcomes, yet achievable upsides (or downsides) – so that the analyst can highlight certain players. My general rule for bold predictions is to target somewhere between a player’s 70^th & 90^th range of percentile possible outcomes, or in other words, predictions which are about 10-30% likely.

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The date is March 19, 2018. You are about to compete in a live NFBC fantasy baseball auction. You are prepping vigorously for your draft auction. You are reading over your player lists, mulling over which OFs you will go for at the auction table.

Fast forward to September 27, 2018. Now that the season is almost all in the books, you can now look back at your fantasy auction and see all the good, the great, the bad and the terrible decisions you had made just 6 months prior.

Let’s start with a simple OF decision. Which player should you have bought back in March?

Mike Trout (OF, LAA)

OR

Eddie Rosario (OF, MIN)

Sounds like a fairly easy decision, no?  But to help you out, before you answer the question … I’ll provide you with some 2018 statistics (as of 9/26):

Don’t answer the question just yet … let me also provide you with a full season dollar valuation for the two players in question.

For those new to subtraction, Trout’s valuation is larger than Rosario’s valuation by $15.30, or another way to look at it … Trout was worth almost 70% more than Rosario was in 2018.

So which player of the two should you have purchased for your fantasy team on March 19?

The answer is ……  Eddie Rosario!!!

Wait just a minute … Trout had the same number of RBIs, but more Runs, more SBs, a higher BA, and more SBs than Rosario. You may even ask, “Ariel, didn’t you just tell me that Trout was worth 70% more than Rosario?” How can that be???

Well, to answer that – you need one more piece of information, namely, what the price was to acquire each player.

First, let’s define three quantities:

• $Value – The full season 5×5 roto value of each player. For this, I am using FanGraph’s auction calculator on YTD 2018 stats, with NFBC standard settings (15 teams, mixed AL/NL, $260 budget and positions – 9 P, 2 C, 1B, 2B, 3B, SS, CI, MI, 5 OF, U). This represents what a player was actually worth in 2018.
• $AAV – The average auction value for each player in 5×5 roto / NFBC style format. For this, I am using the average of a set of actual NFBC online auctions run by Andy Saxton that Todd Zola of Mastersball had provided. This will represent the cost that it would have taken to acquire a player back in March. For those players who weren’t drafted, or who were only drafted as a reserve, we will set a nominal price for them of $0.10.
• $Bargain – The difference between the $Value and $AAV. This represents the profit that each player had provided over the 2018 season, from his initial pre-season draft price.

Let’s go back to that OF comparison now …

Winning fantasy baseball is All. About. Value.

Although Mike Trout will finish the season as a top-10 performer, if you had purchased him in a fantasy auction this year, you would have paid some $47 – which meant that you LOST MONEY on him. Had you purchased Eddie Rosario, which would only have cost you about $12, you would have profited … by over 75% of what you paid.

Below are the top 20 most profitable players for 2018:

Assorted Player Notes & Facts (in no particular order):

• Blake Snell was clearly the best pitcher to buy pre-season 2018 at a roto auction. For a mere $7 average auction value, he will finish as the 3^rd most valuable pitcher this season worth $36, behind deGrom ($40 value) and Scherzer ($39 value). His 21 W currently leads all of MLB, his 1.90 ERA leads the AL, and add in a healthy 211 Ks too (only 14 pitchers have more than 200 strikeouts).
• The next most profitable starting pitchers were Mike Foltynewicz ($15 bargain), Walker Buehler ($14 bargain) and Miles Mikolas ($13 bargain). [Does Mikolas remind you at all of Colby Lewis?]
• Blake Treinen was clearly the most profitable RP in roto this season, with 37 saves and spectacular roto ratio stats (0.79 ERA / 0.83 WHIP). He even added nearly 100 Ks to boot. He was the 16^th most expensive closer to purchase pre-season at an AAV of under $10.
• Yasmani Grandal ($19 value) and Yan Gomes ($13 value) were the two most profitable catchers this year. Grandal could be had for only $4 AAV, and Gomes’s AAV was less than $1.
• The three most valuable undrafted players were Jesus Aguilar ($23 value), Miguel Andujar ($22 value) and Nick Markakis ($19 value). Of those three, Aguilar and Andujar were high skilled players not assured of playing time – which is why their draft price was so low. Javier Baez’s price was also depressed, because most projection systems didn’t give him enough plate appearances, with the Cubs’ logjammed IF roster on opening day.
• Nick Markakis on the other hand, was simply a mistake by pre-season drafters. Markakis was handed the cleanup spot on day #1 in Atlanta. Surrounding him the lineup was Inciarte, Albies, Freeman, and Acuna (knowing he would come up to the MLB shortly). They all cost a minimum of $12 in AAV, which suggested a good ATL lineup this season. Given who the players surrounding him were in his lineup, Markakis, who has a history of a high batting average – should have been projected for a much larger R and RBI total. At the very least, he should have been drafted in NFBC formats.
• Of the top 20 bargain players, Christian Yelich was the most valuable returning a $43 full season value. Yelich had an MVP-caliber season amassing a 33/104/.321 campaign with 21 swipes. He was also the most expensive player on this list to buy, with an AAV of $24. Javier Baez is the next closest to Yelich in pre-season cost at an AAV of $11.50. The huge bargains this year typically came from players which cost just $2-8 pre-season.
• Of the top 20 highest priced players pre-season only 1 player returned a profit – Mookie Betts ($47 value / $39 AAV). The other 19 highest priced players averaged a loss of $16 (A $Bargain of -$16).
• Jacob deGrom ($40 value / $29 AAV) was the highest priced pitcher pre-season who turned a profit. Only deGrom, Justin Verlander and Aaron Nola cost over $20, yet turned a profit. To note, pitching this season accounted for about 37% of NFBC auction budgets, which is rather high historically, and much higher than the traditional 70/30 split rule would indicate.
• The average cost of the top 20 bargain players (including undrafted players at $0.10) was $5. The average returned value of the players was close to $25.

Opening day is now just one short day away. The days this week seem to creep by ever so slowly for a baseball lover. We have already had our fantasy drafts and auctions, and now we want to watch/see how our teams will perform, both fantasy and in real life. Baseball is back … and this year, we get to watch real baseball games that start to count in March!

Below are my 2018 bold predictions. Some of them stem directly from a small stretch of the ATC Projections, which can be found here on FanGraphs. Others come from my own personal analysis on the player, or team situation. The rest arise from some sheer wild optimism, but I have convinced myself that it could happen.

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