Salient is an excellent design with a fresh approach for the ever-changing Web. Integrated with Gantry 5, it is infinitely customizable, incredibly powerful, and remarkably simple.
DownloadWith the 2023 MLB season in the books, it's always fun to look back at the player's earnings. The FREE spreadsheet available via download has final earnings for
12-Team AL only and 12-team NL only, both 4x4 and 5x5, where you either KEEP players traded to the other league or LOSE them
12-Team Mixed
15-Team Mixed
I'm happy to address questions on the site form.
Look for an announcement regarding 2024 Mastersball soon. I will launch by November 1 (maybe earlier, we'll see).
I'm guessing this is out there already, with studies a lot more intense than what I'm about to present. That said, I ran some quick correlation studies on component average exit velocity (AEV) and component BABIP and thought I'd share the findings. Since it's too long for a tweet, I figured I'd dust off my old site column and post it here.
The impetus was writing a profile for Jeff McNeil as his Statcast levers are not favorable - at least they appeared wonky for such a consistent hitter.
The idea is learning how AEV on grounders (GB), fly balls (FB) and outfield line drives (OLD) affects their respective BABIP. I wanted a full season's worth of data, so I looked at 2018 and 2019. These make a good pair since the ball in 2019 incurred much less air resistance than 2018 and while it doesn't influence AEV, it could affect the outcomes.
I landed on 50 batted ball events (BBE) after running the data for several BBE. The number doesn't matter for this quick study since the goal is unearthing general trends to aid in profile writing as opposed to incorporation into my projection engine.
The study is straightforward. I (well, Excel) calculated the correlation coefficient between AEV and BABIP for all players with at least 50 BBE for each type of event. By means of reminder, perfect correlation is 1, perfect reverse correlation is -1 (this will be relevant) while a completely random relationship is 0.
Here are the findings:
BABIP | 2019 | 2018 |
GB | 0.28 | 0.26 |
FB | -0.13 | -0.11 |
OLD | 0.24 | 0.30 |
Intuitively, I expected the correlation to be stronger. Sure, it's positive, but there is a lot of wiggle room. Looking at the GB AEV and OLD AEV and assuming because it's low, a high BABIP will regress isn't as salient an argument as I perceived. Similarly, a high GB AEV and OLD AEV and a low BABIP may not manifest in a higher BABIP.
The fly ball data may surprise some, but based on prior research, it's not alarming. The small negative correlation is saying it's not always a bad thing to hit soft fly balls. These fall into the purgatory between the outfielders and the infielders. Better struck fly balls are the proverbial cans of corn.
One more correlation was conducted, examining the relationship between FB and OLD AEV and HR%. Don't worry, this one yielded the expected results:
HR% | 2019 | 2018 |
FB | 0.83 | 0.81 |
OLD | 0.51 | 0.48 |
Sure enough, elevating the ball with velocity correlates very well to homers. The OLD data incorporates batted balls with trajectories too low be classified as FB, but with too small a launch angle to clear the fence,
Again, there isn't anything earth-shattering here, but it does demonstrate AEV is much more relevant for power than average.
A couple weeks ago, the Tout Wars board (Ron Shandler, Peter Kreutzer, Brian Walton, Jeff Erickson and yours truly) decided to shift Tout Wars weekend in Manhattan to an online affair. The four auctions scheduled for the weekend of March 14 and 15 were conducted in the Fantrax auction rooms, at the times originally scheduled.
To be honest, the determination to cancel the live festivities was easy. It became apparent asking the Touts to travel, perhaps at conflict with their loved ones was unfair. Less than 24 hours later, the decision proved prescient as it was obvious the well-being of everyone would be at risk.
The decision to hold the auctions as scheduled or postpone was more difficult. Admittedly, part of opting for “The show must go on.” was SiriusXM’s commitment to broadcast the drafts remotely. That said, the larger reason was when plans for the (hopeful) commencement of the 2020 campaign are announced, everyone will be scrambling in both their personal and professional lives. A major objective of Tout Wars is getting out if front of most drafts and auctions, showcasing possible strategies and helping to establish the market. With this off the table if we postponed, the board concluded it’s best to hold the auctions as scheduled, perhaps even offering an escape for what will no doubt be a long ordeal.
With that as a backdrop, I participated in the National League only auction. I’ll be honest, since winning the league in 2016, I’ve been embarrassed with my poor showings. Humbly, I’m adept at patience and money management. Recently, I’ve taken this too far, eschewing the top tiers, both hitting and pitching. I’d make some purchases in the mid to high twenties, but most were in the teens where in my mind, I was cleaning up. It wasn’t working.
The odd thing is it hasn’t always been this way. I’ve been aggressive at the top, though not with the elite. For years, my plan began with three players for $100, usually manifesting with three players costing around $35.
Before delving into specifics, here is my general approach. I sit down at the table with a roadmap, allotting a target price for each of the 23 roster spots (14 hitters, nine pitchers). As the roster is built, budget is moved from or added to the spots, as dictated via the buys. I use a tiered method of bookkeeping, constantly making sure there are ample players left to occupy the highest priced open slots. If it’s clear there isn’t anyone worthy of the top spot, budget is redistributed, lowering the top target while increasing some lower ones. For those interested, this procedure is detailed in the Platinum Download as part of the Z Files.
The initial plan was for the first three spots to be $35, $35, $30 with the mindset to spend up to $39 if warranted. However, after looking at the inventory, identifying ample players most likely to populate those spots was tough. Ergo, I swerved to four players for $110. In addition, since I knew I wouldn’t be paying for an ace starter, a bit more budget was dedicated to pitching than what was expected for the league in aggregate. Traditionally, NL Tout Wars spends around 69% of the budget on bats. My roadmap was $175 hitting, $85 for arms, a 67/33 split.
Here is what I took into the auction and how I ended up filling each line.
Target | Player (Price paid) |
35 | Starling Marte (30) |
30 | Charlie Blackmon (28) |
25 | J.T. Realmuto (24) |
20 | Marcell Ozuna (24) |
20 | Kole Calhoun (14) |
15 | Starlin Castro (13) |
12 | Jon Berti (12) |
5 | Asdrubal Cabrera (7) |
5 | Corey Dickerson (7) |
3 | Colin Moran (3) |
2 | Jake Lamb (2) |
1 | Tim Locostro (1) |
1 | Dom Nunez (1) |
1 | Jason Kipnis (1) |
20 | Brandon Woodruff (21) |
15 | Sonny Gray (19) |
15 | Kirby Yates (18) |
15 | Carlos Martinez (13) |
8 | Adrian Houser (8) |
5 | Anthony DeSclafani (7) |
5 | Brandon Kintzler (5) |
1 | Merrill Kelly (1) |
1 | Kevin Ginkel (1) |
Cal Quantrill (res) | |
Ryon Healy (res) | |
Brock Holt (res) | |
Daniel Ponce de leon (res) |
Link to all the Tout Wars Auctions and Drafts
The prices for starting pitching remained elevated and since I was devoid of an ace, hitting the middle hard was necessary. In addition, Yates was a few bucks over the target price for a closer but was too good a deal to ignore. The result was $167 to hitting and $93 to pitching, a 64/36 split.
Even with the game plan to be more aggressive than the past few seasons, a $30 Marte was the top buy. Even so, $106 was spent on four batters, just $4 below the target.
The budget required to supplement pitching emanated in part from the $4 saved above along with funneling some from the $20 and $15 hitting lines. This is exactly the area I usually thrive, but the redistribution was needed. As it turned out, it was fortuitous as there weren’t a lot of perceived good buys in that range. The auction had a strange feel, which was shared by those in the NL LABR auction earlier in the month. The spending of both NL auctions didn’t level off until very late, reducing the earlier “bargains”, confining them to the end game. On my end, this enabled the purchasing of Cabrera and Dickerson, a couple of guys I had priced into the mid-teens.
Despite spending less than intended on hitting, including an expensive catcher, I’m pleased with the offense. It needs Berti to come through along with Locostro chipping in some bags, but I like the balance and flexibility with several multi-eligibility players. This will facilitate upgrading Lamb, Kipnis, Locostro and possibly Moran.
Pitching may not appear to be strong, but I’m high on Woodruff, Gray, DeSclafani and Houser, though I wish they weren’t centralized in two of the best hitting venues in the Senior Circuit. Martinez continues to get a discount, one which I’m happy to accept.
With respect to saves, Josh Hader sold for $23 so the expectation was Yates would cost at least $20. I had no issue taking him to $18, but that was likely my max. When he sold for that number, I was giddy, knowing lesser closers would fall in the $14-$16 range and I’d much rather spend the extra on Yates. As it turned out, Kenley Jansen and Edwin Diaz sold for $16 with Hector Neris and Craig Kimbrel drawing $14 bids. Yates and Kintzler cost $23. It’ll be interesting to see how that compares to Archie Bradley ($12) and Giovanny Gallegos ($11), selling for the same $23.
Before I go, Tout Wars weekend included one of the proudest moments of my professional career as I was the recipient of the first Lawr Michaels Zen and Now award. This was via peer nomination by my Tout Wars colleagues, making it extra special. Giving a peek behind the fourth wall, I was informed of the honor a little before the official announcement on SiriusXM, availing just enough time to compose myself and try to come up with something to say. As I said on the air, especially in the current trying time, it’s heartening knowing while I may be the first, there’s a litany of other worthwhile Zen and Now recipients, carrying on Lawr’s memory and spirit for decades to come.
Tuesday night I participated in Tout Wars Mixed Draft League. This is a 15-team 5X5 league with OBP instead of BAvg where you draft your 23 starters and then get six reserve picks. I drew the ninth pick so let’s see how I fared and what happened at this draft table of fantasy industry veterans that might help you in upcoming drafts.
The draft started normally with the usual suspects – Mike Trout, Christian Yelich, Ronald Acuna, Juan Soto, Cody Bellinger, and Mookie Betts taken off the board. One of the first-round questions in a fifteen team is when would the top pitchers get drafted? In this draft it was 1.07 when Gerrit Cole was taken. Then we had the middle infield run as Trea Turner was taken at 1.08, I selected Fransisco Lindor, and Trevor Story followed. Back to the elite starting pitchers, Jacob deGrom went at 1.11, hardly a surprise. But after Noland Arenado was drafted the end of the first round was Walker Buehler (surprisingly ahead of), Justin Verlander, and Max Scherzer.
At my second pick I had to choose whether to take the best pitcher available (Jack Flaherty) or add another big bat and hope I would see either Stephen Strasburg or Clayton Kershaw (yes, I think he is back this year and 200 innings from him would be huge) would make it back to me in the third round. So, I took Mets first baseman Pete Alonso hoping for 40 home runs in his second season (I doubt he hits another fifty in his sophomore season). No such luck as the Cole owner doubled up with Shane Bieber and the Betts owner took Flaherty at 2.10. Strasburg went with the last pick in the second round and teams two, three, and four took Mike Clevinger, Patrick Corbin, and Kershaw in the order. I chose Charlie Morton at 3.09 over Zach Greinke.
Blake Snell was the only other pitcher taken in the third round but the fourth round saw Yu Darvish, Chris Paddack, Luis Castillo, Chris Sale, and Aaron Nola get selected. So through four rounds every team had drafted one starting pitcher and three teams had taken two. This is definitely an increase or this group and more closely resembles and NFBC draft. The two surprises for me were the injured Clevinger being drafted in the third round and Sale being drafted in the fourth. Sale was taken with a significant discount, but with him seeking a third opinion on his left elbow is too much of a risk a team’s “ace”.
Here are a few other draft picks that you may be interested in:
Here is a recap of my draft
1.09 Francisco Lindor
2.07 Pete Alonso
3.09 Charlie Morton
4.07 Cavan Biggio
5.09 Ramon Laureano
6.07 Mike Soroka
7.09 Gary Sanchez
8.07 Liam Hendriks
9.09 Justin Turner
10.07 Mike Minor
11.09 Adam Eaton
12.07 Jorge Polanco
13.09 Masahiro Tanaka
14.08 Justin Upton
15.09 Eric Thames
16.07 Kole Calhoun
17.09 Ryan Yarbrough
18.07 Alex Verdugo
19.09 Kurt Suzuki
20.07 Dakota Hudson
21.09 Dallas Keuchel
22.07 Anibal Sanchez
23,09 Jesus Aguilar
24.07 James Karinchak
25.09 Jose Martinez
26.07 Jordan Hicks (IL)
27.09 Carl Edwards Jr.
28.07 Jose Peraza
29.09 Domingo German (S)
The Hicks and German picks were made because this league will have its first FAAB run right before the season starts when I can “DL” them and add two more reserves.
An interesting draft to be sure. As with most teams, the fate of this squad will be dependent on how the pitching ends up and in vigorous pursuit of free agent players to help either specific category shortages or replace players who might be injured or not performing. I certainly have enough power and a strong OBP. Steals may need Peraza running for the Red Sox. Saves will need either Edwards to break out of the committee in Seattle; Karinchak succeeding Brad Hand if he is traded; or finding some on the free agent list – one reason I created two slots to be replaced.
Always glad to answer questions about my picks or this draft in the Subscriber Forum.
Previously, the hitting and pitching projection zystems were described. Now it's time for the next step - valuation. Please note this is an edited version of an essay first written in 2010 and abridged over the years. At the end, I’ll chime in with some present day commentary.
Introduction
Simply stated, fantasy baseball is a game in which you assemble a team of real baseball players whose statistics are used to score and ultimately rank your team. To do this effectively, you need to do three things
This essay will focus on the middle aspect, the quantification of performance, perhaps better known as player valuation.
There are a bevy of valuation systems in use to quantify statistics. Why are there multiple? Because there is no definitive right or wrong. There is no precise manner to put a static designation on a fluid entity. There may be better ways, but it follows that if there were truly a correct or even best way, that would be basically universal. Admittedly, in my younger, more naïve days I felt the method I am about to describe was the be‐all‐end‐all and dedicated my life to that crusade. But over the years, I have developed a truer grasp of what it really takes to succeed at this endeavor and have softened my stance. Player values and rankings are a guide, a piece of the puzzle. I much prefer being recognized for my acumen in the third element of the hobby described above, the assembling of your squad than being known as the premier valuation guy in the industry, though that does have its advantages. That said, those of you that favor the popular SGP method are using an inferior process as it is theoretically and mathematically flawed. After all, I softened, not completely changed my stance.
What you need from a valuation system is a snapshot view of what a player is worth relative to other players. Since this snapshot is composed of several elements, it also helps if you have an idea of what comprises that snapshot. It really helps if you understand how the snapshot is generated, so you can do some massaging to the system to best make it work for your league and its unique tendencies.
What you don’t need is a green light, red light designation of perfectly accurate value. I chalk it up to the maturation process, both as a person and a fantasy gamer, but I honestly feel the focus I put on “proper player valuation” stunted my growth as a player, detracting from my ability to look at the big picture, understanding how to use that piece of information most efficiently.
With all that said, what follows is a description of a valuation process that I believe to be most effective when looking at the big picture. It does not presuppose anything in terms of player value. It gives an unbiased snapshot of how each player can help your squad. It is incredibly flexible, so it can handle any tweak or alteration you feel necessary. It can account for all aspects of your league’s dynamics and does so in a sound philosophical as well as logical manner.
The Concept
Simply put, value is distributed in proportion to each player’s contribution to the overall player pool. If I have $1000 to pay a crew for doing a job, someone did 50% of the work gets $500. If someone else did 30%, they get $300, leaving $200 for the remaining 20% contribution of the third member.
Of course, valuing players for rotisserie style scoring is more complex as contributions are across multiple scoring categories. The player’s contribution in each category is determined, and these are all summed for a total value
Boundarie$ and Parameter$
Even though much of the introduction was designed to drive home the point that ultimately the value assigned should be viewed rather loosely, we still need to treat the system in a static nature. As such, there are several logical boundaries and parameters of a sound valuation method.
Let us begin with what will be referred to as the draft‐worthy pool. The draft‐worthy pool should be composed of exactly enough players to field a league full of legal rosters, taking into account positional requirements. By means of example, a 12‐team league with 14 hitters and 9 pitchers will have a draft‐worthy hitting pool totaling 168 players, with 108 in the draft‐worthy pitching pool. More specifically, if the positional requirements are the standard 2C, 1B, 2B, 3B, SS, CI, MI, 5OF and UT, then there needs to be 24 C, 12 1B, 12 2B, 12 SS, 12 CI, 12 MI, 60 OF and 12 UT in the hitting pool.
Because most rules specify a minimum bid of $1 on each player, the lowest ranked player of the draft‐worthy pool should be worth $1, with the top‐ranked non‐drafted player being $0. An argument can be made this condition should be set upon each position. That is, the worst catcher in the draft‐worthy pool be set at $1, the worst second baseman $1, etc. Later, the mathematical manner to do this will be detailed.
Values should be assigned in a zero‐sum nature. A typical team budget is $260. That means our 12‐team league has $3120 to spend on the previously discussed 168 hitters and 108 pitchers. The entire $3120 should be exactly distributed amongst the 276 players comprising the draft‐worthy pool.
Because the points earned in each scoring category in most rotisserie league are equal, the money assigned to each should be the same. For example, in leagues that use a $260 budget with 5 hitting and 5 pitching categories, you should plan on spending $26 for each. However, as most everyone knows, conventionally, more money is spent on hitting than pitching. Currently, the average 5x5 league spends 69% of its budget on hitters. This drops to 67% in the ever‐disappearing 4x4 leagues. This equates to each 5x5 team budgeting $179.40 ($35.88 per category) for hitters and $80.60 ($16.12 per category) for pitching. In a global sense, a 12-team league distributes $430.56 per hitting category and $193.44 per pitching category.
Replacement Level and the Concept of Useful Stats
We have already established that each player’s value is assigned according to the summed percentage contribution across the categories. The number of players with a value of $1 and greater is dictated by the number of teams in the league and positional requirements while the total amount of money distributed is equal to the number of teams multiplied by the team budget.
All we have left is to determine the player’s contribution to each category. This involves employment of a concept that is becoming more and more familiar to the baseball statistical community and is generally referred to as value above replacement. Personally, I prefer to explain it in terms of useful statistics.
In short, I have an issue paying for something I can get for free. Okay, this does not explain my penchant for buying bottled water, but I digress. In fantasy baseball terms, due to the positional restraints of legal lineups, there is a certain level of statistics that everyone has on their roster. If everyone has these, why pay for, ergo, place a value on them? It does not make sense. If you are doing a football pick‐‘em pool and everyone chooses the same team to win, the result of that game is inconsequential. If the worst catcher on a roster in a fantasy league is projected to hit 5 homers, then everyone in the league has those same 5 homers, so why pay for them? What you want to pay for is that which differentiates you from the rest. I term these “useful statistics”. To bring the point home, our system only values these useful stats.
Here is an example I like to use to demonstrate the concept and utility of useful stats. Let us set up a 2‐team HR derby league, you and me. We each need a player from Group A and one from Group B. I will give you first pick. Here is the available player pool:
GROUP A
GROUP B
So, who do you want? Hopefully Green. Why? If you take Red because he is the best hitter, I will take Green then Blue for a total of 65 HR. You get Red and Yellow for a total of 60 HR and I get to call SCOREBOARD!!!
Here is how the pool should be considered:
GROUP A
GROUP B
This represents the number of USEFUL homers each batter swats.
At this point, you may be wondering if this is the mathematical manner to deal with positional requirements, that is, what if instead of 2 groups there were 6 and instead of alphabetical designation, there were catcher, first base, second base, etc.? You are very wise, Grasshopper.
This is precisely the manner proper valuation should be conducted and will also result in the worst player in each pool being valued at $1 as discussed previously. It also explains why 20 homers from a catcher are worth more than 20 homers from a different position. In 2‐catcher leagues, the same 20 homers account for more useful homers for the catcher as the amount subtracted from the replacement catcher is smaller than that of the other positions. In mixed leagues 15 or 16 of a catcher’s 20 home runs are useful as compared to perhaps only 12 or 13 for the other positions.
While it is easiest to explain the concept of useful stats using a simple home run derby league, the fact there are multiple categories in standard rotisserie formats adds a significant layer of complexity to the process. The way we overcome this issue is to employ a mythical replacement player, who is a composite of the worst players at each position. You cannot single out a particular player as there are many reasons why a player is of low value. He could have a poor batting average but decent counting stats. He could have a poor average and low power, but a lot of steals. His average could be solid but the associated production minimal. The point is, using an individual player to set the replacement level can skew the useful stats as the adjustment could be too much or too little. So instead, we use the mythical player who has a mythical stat line representing the average production of the last few replacement level players
A final point to be made is some draft‐worthy players may in fact contribute a negative value in a counting stat category if their contribution is lower than that of the mythical replacement player in that category.
Converting Ratio Stats to Counting Stats
There is one final speed bump that we need to deal with before we are ready to tie it all up. It is straightforward to envision the distribution of value with the categories involving the counting stats such as HR, RBI, runs, SB, wins, saves and K in standard formats. It is a mite trickier with respect to the ratio categories of BA, ERA and WHIP. We need to convert a ratio stat to a counting stat. This exercise is worthy of an essay unto itself, so I will just provide the Cliff Note’s version and encourage questions on the message forum.
What we do is take the player’s ratio and compare it to a baseline ratio, then multiply the difference by at bats or innings pitched to apply a weight. We have empirically determined that the most effective baseline ratio is that of the typical last place team in your league of the category in question.
Since the baseline batting average for hitters is numerically lower than what you expect for a useful hitter, the baseline average is subtracted from the player’s average and multiplied by at bats. On the other hand, since a superior ERA and WHIP are numerically lower than the baseline, they are subtracted from the baseline and multiplied by innings. The resulting number is now treated the same as a counting stat.
Treatment of Middle Infield, Corner Infield and Utility Positions along with Multiple Eligibility Players
The in‐depth manner to account for the fact that either a second baseman or shortstop can fill middle infield, a first baseman or third baseman can be slotted at corner and all hitters can fill utility is beyond the scope of this essay. For those interested, the explanation is provided in other site material. For this essay, let us assume in our model league above the middle infield pool is composed equally of 6 second basemen and 6 shortstops while the corner pool has 6 first basemen and 6 third basemen. We will also assume the utility pool is all outfielders and DH‐only. This means the draft‐worthy pool will include 24 catchers, 18 at each infield position and 72 outfielders. In your league, the actual spread will be different. We explain how to deal with this in primers explaining the actual usage of the site’s CVRC (customizable value and ranking calculator).
As you know doubt are aware, some players carry multiple eligibility. We use the assumption that they will be drafted at the position they enjoy the most value. As such, we designate positions according to the following positional hierarchy:
C > 2B > SS > 3B > 1B > OF
Putting it All Together
We now have everything necessary components to determine dollar values. We can determine the number of useful stats each player contributes by subtracting the corresponding replacement level across the positions. Using our model league and considering just home runs, the top 24 catcher useful home runs total, the top 18 homer totals at each infield position and the top 72 outfield homer totals are all summed and represent the total of useful homers for the draft‐worthy pool. Value is then assigned according to the percentage of useful homers each player contributes multiplied by the monetary amount assigned for the pool.
By means of example, let us say the pool of homers for the draft‐worthy pool is 2000. An outfielder is projected to hit 40 and the replacement at the position is 10. He is thus given credit for 30 useful homers. According to our calculations above, each hitting category is allocated $430.56. The players HR$ is then 30/2000 x $430.56 or $6.46. This is done in a similar manner for the other categories and the individual categorical contributions are summed for a final value.
To emphasize a point discussed previously, let us consider a catcher that is projected to hit the same 40 homers as the outfielder. The difference is the replacement level for catchers is no doubt less than that for outfield, perhaps only 5. This yields 35 useful homers for our catcher, translating to a HR$ of $7.53. The same 40 raw homers are worth more coming from a catcher as he contributes more useful homers to the global total.
In the name of full disclosure, there is still some algebraic tweaking necessary as doing replacement in this fashion results in a hitting pool not necessarily composed of exactly 168 players and a pitching pool with precisely 108 hurlers. The take home lesson is not this adjustment, but the understanding of how we assign player value in a global sense.
Making the Theoretical Practical
You can now put away your calculator. We are done considering the value calculation as a static entity. While it is true that what has been described is a theoretically logical procedure, it is not an entirely practical means of assigning value in all instances. There is a fine balance between what a player is theoretically worth and the practical amount you need to pay to acquire his services.
The multiple eligibilities of players along with the corner, middle and utility designations cloud the picture. Who is to say every player eligible at both second and outfield are put at second? Doing this alters the number of players in each position’s draft‐worthy pool, skewing the composition of the replacement player which affects the number of relative useful stats each player contributes. The best way to combat this is to simplify your pool designation. In almost all leagues, the catcher pool needs to remain distinct. The first basemen and third basemen can be combined into a single corner infield pool. Similarly, second basemen and shortstops can be merged into the middle infield pool. This cuts down the total number of pools from 6 to 4. In addition, since many outfielders and corner infielders have eligibility in both pools, integrating those is perfectly acceptable as well. Now we only have 3 pools to deal with. Finally, partly due to the plethora of multiple eligibility players and the nature of the current player pool in general, in AL and NL only leagues and even some deeper mixed leagues, the replacement level player is so close to the same across all non‐catcher positions you can really simplify matter by using only a catcher and non‐catcher pool. All you need to do is lump the respective pools together and determine the replacement level player based on that new group.
NOTE: Since this essay was initially written, the inventory is such two pools are all that is necessary in most leagues: catcher and non-catcher. This is the manner the HITCVRC is currently programmed. The HITCVRC is the Customizable Value and Rankings Calculator, an excel program available for Platinum subscribers.
Another consideration is you may not feel it is practical to assign the same budget to each category. You may want to invest a higher portion to more stable categories. Perhaps this entails devaluing batting average and wins. Perhaps your league’s dynamics are such that speed or saves are devalued. You can readily adjust the budget you dedicate to steals or saves. The idea of devaluing speed makes sense from a theoretical aspect as well and is something we first discussed several years ago. Our value system assumes linear distribution of stats within the final standings. However, the reality is the spread between teams is not linear, especially in steals. We have conducted some studies that show you do not need to spend as much money in the steals category to finish at the same point in the category as you do others. We call this category efficiency and adjust our category weights accordingly, shunting some budget from steals to home runs. Why home runs? Site research demonstrates the category league champions fare the best in is homers, so it makes sense to help insure success there. In addition, the same studies show winning teams fare the poorest in steals, providing further evidence that it is practical to reduce steals allocation.
In Summary
As suggested in the introduction, the beauty of our system is it is flexible enough to easily handle these and any other practical alterations. The foundation is rooted by solid theoretical principles which can be modeled mathematically. So long as you understand the principles, you can adjust in any manner you deem reasonable to produce the most practical, hence useful set of bid guidelines possible. This is true for any size league with any positional requirements and any scoring categories. It can be adapted to keeper leagues. There is not a format we cannot handle. The key is understanding exactly what the value represents. It is not an (incorrect) measure of how many points you can gain in the standings with that player. It is not a measure of how many standard deviations a player is from an average player. It is the summed total of each player’s contribution of useful stats across each scoring category. We firmly believe this provides you with the optimal guidance to assist in your endeavor to assemble a championship team.
As mentioned, Mastersball Platinum has an Excel tool programmed to generate values using the PVM method. The original process involves iterative sorts until replacement stabilizes, something I am not skilled enough to program. Instead, I use the LARGE function to derive the replacement level player. As an example, in a 12-team league with two catchers, the replacement level for homers is the 24th highest total. The replacement for the rest of the pool is the 144th largest. This is subtracted from the rest of the pool to derive useful homers.
Another small tweak from the original method is using marginal pricing, since it's easy to program. Here, every player is assigned $1, since conventionally, that's the minimum required. The replacement player then earns $0.
Mathematically, in a 5x5 league, each player gets $0.20 marginal pricing for each category. As such, the cumulative marginal pricing needs to be removed from the category pool. Recall in a 12-team, 5x5 league, each hitting category distributes $430.56 to the draft-worthy pool. There are 168 hitters, assigned $33.60 marginal value. This is subtracted from $430.56, leaving $396.60 to be distributed to the useful stats in each category.
This process is done for all five categories, then each category contribution is summed for the final value. At this point, the pool probably isn't perfectly sized, so the program adjusts the prices proportionately, so they fit within the parameters and boundaries of the specific league.
The final change from the original method is an empirical discovery, unique to Mastersball. The research is available to Platinum subscribers and will soon be brought out from behind the firewall. Even with accounting for catcher scarcity, the pre-season values aren’t representative of what will transpire over the season. In short, the calculated scarcity bump is too severe. To deal with this, I’ve coded the CVRC to price backstops more realistically. Note, this is only true for two-catcher leagues.
Now for the grand finale. In the inaugural Mastersball Annual, John Mosey authored the valuation chapter. Mosey did a great job, but some readers had trouble understanding it, so I was tasked with translating the chapter into English for our second publication. Mosey was quite gracious and helpful throughout the process.
I was not alone in the endeavor, enlisting friend and colleague Rob Leibowitz, now proprietor of Rotoheaven to be my guinea pig and editor. Rob not only made sure my words were clear, he tested the steps of the method along the way.
For those inclined to download the chapter and try it out, I can’t promise much support. Things have changed for me professionally and I may not be able to guide you through as closely as a few years ago. I can, however, preach patience. A LOT of patience. Eventually, the replacement level will settle. After going through the process several times, you’ll probably figure out some tricks. But again, to get there, BE PATIENT. Feel free to post questions on the message forum.
With that, here’s the chapter on Player Valuation, circa 2002 (or so).
OK, back to 2020 Todd again. Unfortunately, I’m about 100 pounds heavier with less hair, and what’s left is more stubby gray than curly brown. However, I am a bit wiser and possess a deeper understanding of valuation.
Regardless of the method, valuation is seriously flawed. This will be the subject of future essays but realize every process has shortcomings. That said, I’m still most comfortable with the method just detailed. The key is understanding it’s limitations and applying that knowledge to your drafts and auctions.
As always, please post questions and comments on the site message forum. Admittedly, marketing is a weakness, but I’m often asked, “What do I get with Mastersball Platinum I can’t get elsewhere?” The answer is simple. You get me. Masterball Platinum is the only place you can communicate with me personally, where I’m happy to address anything fantasy baseball related.{jcomments on}
This is part of part of the Z-Book, an ongoing compilation of new and refreshed pieces. It's part of the 2020 Mastersball Platinum subscription, available for just $39.95, featuring the industry's earliest and most comprehensive set of player projections.
Todd Zola is the Primary Owner and Lead Content Provider for Mastersball. He’s the defending Great Fantasy Baseball Invitational champion, besting 314 of the industry’s finest. Todd is a former Tout Wars and LABR champion as well as a multi-time NFBC league winner.
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