2019’s Fantasy Baseball Auction Bargains
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.”
I often like to remind our readers that the key principle to succeeding in fantasy baseball auctions is to maximize the value of your accumulated roster. Purchase players at discounts. You need to make a “profit” on as many roster spots as you can.
Each team is handed $260 at the start of the auction. If you buy every player for the value that he is worth, you will have paid $260 of auction dollars for $260 of value. What you will have is an average team. You won’t finish last, but you won’t finish first. Instead, with your $260 – you need to buy some $290 or $300 or $310+ of total value.
Suppose that you competed in a live NFBC fantasy baseball auction this year. Let me ask you a seemingly easy question:
Which player should you have bought back in March?
Mike Trout (OF, LAA)
OR
Trey Mancini (1B/OF, BAL)
Before you give your response, let’s take a quick look at the final 2019 stat line for the two players in question:
| Player | R | HR | RBI | SB | AVG |
|---|---|---|---|---|---|
| Mike Trout | 110 | 45 | 104 | 11 | .291 |
| Trey Mancini | 106 | 35 | 97 | 1 | .291 |
Well, Trout has more HR, SB, R and RBI than Mancini, and he has the same batting average to the thousandth decimal place. This seems like a slam dunk answer of Mike Trout, right?
Well, let’s now take a look at the full season dollar valuation comparison of the two:
| Player | Team | Position | $ Value |
|---|---|---|---|
| Mike Trout | Angels | OF | $33 |
| Trey Mancini | Orioles | 1B/OF | $25 |
Once again, Mike Trout’s $33 is objectively higher than Mancini’s $25.
But the correct answer to the above question is … Trey Mancini.
What is key is not the value of the player in question. It is the value of the player relative to what you paid for him.
At NFBC auctions, Trey Mancini cost owners an average of $3 to acquire. On average, he would have earned his owners $22 (= $25 – $3) of fantasy profit. On the other hand, Mike Trout was purchased for a whopping $51 to the average fantasy team in March. As Trout earned $33 of roto value this year, he was a value drainer, losing $18 for the average owner.
Please be aware that my argument that Mancini was the better purchase as compared to Trout, does not imply that a $51 Mike Trout purchase is a poor one. Earning roughly two-thirds of the price paid for him is not necessarily a bad thing. Mike finished as the ninth best hitter – a clear first round player – which is a fine result for fantasy teams.
However, the Mancini purchase was unquestionably the one which was more efficient.
Methodology:
Let’s define three quantities:
- $Value – The full season 5×5 roto value of each player. For this, I am using the FanGraphs auction calculator on YTD 2019 stats, with NFBC standard settings (15 teams, Mixed AL/NL, scaled to a $260 budget with positions – 9 P, 2 C, 1B, 2B, 3B, SS, CI, MI, 5 OF, U). This represents what a player was worth for the full season of 2019.
- $AAV – The average auction value for each player from all auctions conducted by the NFBC during the month of March 2019. This will represent the cost that it would have taken to acquire a player. For the players who were not drafted, or who were only drafted as a reserve, we will set a nominal price for them of $0.10. Please note that NFBC only provides rounded AAV data; all amounts are whole dollars.
- $Bargain – The difference between the $Value and $AAV. This represents the profit that each player had provided over the 2019 season, relative to their initial pre-season draft price.
One important note. The empirical hitter/pitcher split based on NFBC $AAV data was roughly 63%/37%, which has a pitcher tilt. As for the full season values – the FanGraphs auction calculator (which is a Z-Score based method of valuation) inherently determines the hitter/pitcher split of the auction dollars, and the result came close to 70%/30%. I have decided not to make any adjustments to the final value hitter/pitcher split in this analysis. This will make hitters seem a bit more profitable and pitchers a bit less profitable.
2019’s Biggest Bargains:
Below are the top 35 most profitable hitters for 2019:
| No. | Player | R | HR | RBI | SB | AVG | $Value | $AAV | $Bargain |
|---|---|---|---|---|---|---|---|---|---|
| 1 | DJ LeMahieu | 109 | 26 | 102 | 5 | .327 | $30.0 | $1.0 | $29.0 |
| 2 | Rafael Devers | 129 | 32 | 115 | 8 | .311 | $36.3 | $11.0 | $25.3 |
| 3 | Ketel Marte | 97 | 32 | 92 | 10 | .329 | $30.4 | $5.0 | $25.4 |
| 4 | Pete Alonso | 103 | 53 | 120 | 1 | .260 | $29.2 | $5.0 | $24.2 |
| 5 | Jorge Soler | 95 | 48 | 117 | 3 | .265 | $27.2 | $3.0 | $24.2 |
| 6 | Marcus Semien | 123 | 33 | 92 | 10 | .285 | $28.5 | $5.0 | $23.5 |
| 7 | Danny Santana | 81 | 28 | 81 | 21 | .283 | $22.2 | $0.1 | $22.1 |
| 8 | Trey Mancini | 106 | 35 | 97 | 1 | .291 | $24.7 | $3.0 | $21.7 |
| 9 | Josh Bell | 94 | 37 | 116 | 0 | .277 | $24.2 | $3.0 | $21.2 |
| 10 | Mitch Garver | 70 | 31 | 67 | 0 | .273 | $20.5 | $1.0 | $19.5 |
| 11 | Yuli Gurriel | 85 | 31 | 104 | 5 | .298 | $24.2 | $5.0 | $19.2 |
| 12 | Christian Vazquez | 66 | 23 | 72 | 4 | .276 | $20.0 | $1.0 | $19.0 |
| 13 | Eduardo Escobar | 94 | 35 | 118 | 5 | .269 | $24.2 | $6.0 | $18.2 |
| 14 | Carlos Santana | 110 | 34 | 93 | 4 | .281 | $24.3 | $7.0 | $17.3 |
| 15 | Jeff McNeil | 83 | 23 | 75 | 5 | .318 | $18.7 | $2.0 | $16.7 |
| 16 | Austin Meadows | 83 | 33 | 89 | 12 | .291 | $23.2 | $7.0 | $16.2 |
| 17 | Cody Bellinger | 121 | 47 | 115 | 15 | .305 | $40.5 | $26.0 | $14.5 |
| 18 | James McCann | 62 | 18 | 60 | 4 | .273 | $15.6 | $1.0 | $14.6 |
| 19 | Christian Walker | 86 | 29 | 73 | 8 | .259 | $14.5 | $0.1 | $14.4 |
| 20 | Jorge Polanco | 107 | 22 | 79 | 4 | .295 | $19.9 | $6.0 | $13.9 |
| 21 | Giovanny Urshela | 73 | 21 | 74 | 1 | .314 | $14.2 | $0.1 | $14.1 |
| 22 | Bryan Reynolds | 83 | 16 | 68 | 3 | .314 | $13.8 | $0.1 | $13.7 |
| 23 | Yoan Moncada | 83 | 25 | 79 | 10 | .315 | $21.9 | $9.0 | $12.9 |
| 24 | Hunter Dozier | 75 | 26 | 84 | 2 | .279 | $14.2 | $1.0 | $13.2 |
| 25 | Shin-Soo Choo | 93 | 24 | 61 | 15 | .265 | $15.1 | $2.0 | $13.1 |
| 26 | Brett Gardner | 86 | 28 | 74 | 10 | .251 | $13.8 | $1.0 | $12.8 |
| 27 | Omar Narvaez | 63 | 22 | 55 | 0 | .278 | $15.3 | $3.0 | $12.3 |
| 28 | Kevin Pillar | 83 | 21 | 88 | 14 | .259 | $15.3 | $3.0 | $12.3 |
| 29 | Yordan Alvarez | 58 | 27 | 78 | 0 | .313 | $12.2 | $0.1 | $12.1 |
| 30 | Fernando Tatis Jr. | 61 | 22 | 53 | 16 | .317 | $14.0 | $2.0 | $12.0 |
| 31 | Kevin Newman | 61 | 12 | 64 | 16 | .308 | $13.0 | $1.0 | $12.0 |
| 32 | Anthony Rendon | 117 | 34 | 126 | 5 | .319 | $35.9 | $25.0 | $10.9 |
| 33 | Joc Pederson | 83 | 36 | 74 | 1 | .249 | $12.7 | $1.0 | $11.7 |
| 34 | Kolten Wong | 61 | 11 | 59 | 24 | .285 | $11.8 | $0.1 | $11.7 |
| 35 | Nelson Cruz | 81 | 41 | 108 | 0 | .311 | $25.9 | $15.0 | $10.9 |
Here are the top 25 most profitable pitchers for 2019:
| No. | Player | K | W | SV | ERA | WHIP | $Value | $AAV | $Bargain |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Liam Hendriks | 124 | 4 | 25 | 1.80 | 0.96 | $18.8 | $0.1 | $18.7 |
| 2 | Hyun-Jin Ryu | 163 | 14 | 0 | 2.32 | 1.01 | $24.3 | $7.0 | $17.3 |
| 3 | Lucas Giolito | 228 | 14 | 0 | 3.41 | 1.06 | $18.0 | $1.0 | $17.0 |
| 4 | Brandon Workman | 104 | 10 | 16 | 1.88 | 1.03 | $16.6 | $0.1 | $16.5 |
| 5 | Mike Soroka | 142 | 13 | 0 | 2.68 | 1.11 | $16.4 | $0.1 | $16.3 |
| 6 | Sonny Gray | 205 | 11 | 0 | 2.87 | 1.08 | $17.9 | $3.0 | $14.9 |
| 7 | Emilio Pagan | 96 | 4 | 20 | 2.31 | 0.83 | $14.9 | $0.1 | $14.8 |
| 8 | Hansel Robles | 75 | 5 | 23 | 2.48 | 1.02 | $12.6 | $0.1 | $12.5 |
| 9 | Taylor Rogers | 90 | 2 | 30 | 2.61 | 1.00 | $13.2 | $1.0 | $12.2 |
| 10 | Hector Neris | 89 | 3 | 28 | 2.93 | 1.02 | $12.0 | $0.1 | $11.9 |
| 11 | Lance Lynn | 246 | 16 | 0 | 3.67 | 1.22 | $12.8 | $1.0 | $11.8 |
| 12 | Seth Lugo | 104 | 7 | 6 | 2.70 | 0.90 | $12.0 | $1.0 | $11.0 |
| 13 | Justin Verlander | 300 | 21 | 0 | 2.58 | 0.80 | $44.4 | $35.0 | $9.4 |
| 14 | Josh Hader | 138 | 3 | 37 | 2.62 | 0.81 | $21.1 | $11.0 | $10.1 |
| 15 | Will Smith | 96 | 6 | 34 | 2.76 | 1.03 | $16.3 | $6.0 | $10.3 |
| 16 | Jake Odorizzi | 178 | 15 | 0 | 3.51 | 1.21 | $11.4 | $1.0 | $10.4 |
| 17 | Charlie Morton | 240 | 16 | 0 | 3.05 | 1.08 | $22.1 | $13.0 | $9.1 |
| 18 | Daniel Hudson | 71 | 9 | 8 | 2.47 | 1.14 | $9.3 | $0.1 | $9.2 |
| 19 | Giovanny Gallegos | 93 | 3 | 1 | 2.31 | 0.81 | $9.3 | $0.1 | $9.2 |
| 20 | Domingo German | 153 | 18 | 0 | 4.03 | 1.15 | $11.1 | $2.0 | $9.1 |
| 21 | Shane Bieber | 259 | 15 | 0 | 3.28 | 1.05 | $22.2 | $14.0 | $8.2 |
| 22 | Yusmeiro Petit | 71 | 5 | 0 | 2.71 | 0.81 | $8.9 | $0.1 | $8.8 |
| 23 | Frankie Montas | 103 | 9 | 0 | 2.63 | 1.11 | $9.6 | $1.0 | $8.6 |
| 24 | Jeff Samardzija | 140 | 11 | 0 | 3.52 | 1.11 | $9.6 | $1.0 | $8.6 |
| 25 | Will Harris | 62 | 4 | 4 | 1.50 | 0.93 | $8.4 | $0.1 | $8.3 |
Assorted Hitter Notes (in no particular order):
- DJ LeMahieu was the top hitter bargain this season. He was typically purchased at NFBC auctions either late or not at all, with an AAV of $1. He was a player who was widely available on league waiver wires for most of April. LeMahieu’s price was depressed at 2019 auctions due to the seemingly crowded Yankee infield to start the season.
- To compare to last year, LeMahieu’s bargain of over $29 exceeds the $25 of profit earned by Javier Baez in 2018 (last year’s most profitable hitter). Last season, Baez’s cost to acquire was similarly depressed due to a perceived “crowded” Chicago infield.
- Danny Santana was the most profitable hitter who was not drafted, making him the best full-season waiver pickup of the season.
- The other non-drafted hitter bargains in the top 25 were: Christian Walker, Giovanny Urshella, Bryan Reynolds, Yordan Alvarez and Kolten Wong.
- Santana and Wong were the only players on this list that had more than 20 SB this season – and they were both undrafted. Speed was certainly at a premium at 2019 auctions.
- Three of the top 20 hitter bargains were catchers (Mitch Garver, Christian Vazquez and James McCann). 2019 was a very good season to stream catchers, and a year not to spend large amounts at the auction. There will be more on that in an upcoming article.
- Of the top 35 most profitable hitters, Cody Bellinger amassed the most roto dollars, returning a $Value of $41. He was also the most expensive player to buy on this list, with an $AAV of $26. Anthony Rendon was the next most expensive to purchase pre-season.
- The huge bargains this season typically came from players who cost just $3-7 pre-season. To compare, last year I noted that this range was $2-8. This leads me to believe that having an extra $1-3 dollars to spend on each of your final few hitters at an auction may lead to some of the best bargains of the season, as opposed to buying the single dollar players.
- The average cost of the top 35 hitter bargains (including undrafted players at $0.10) was $4.6. The average returned value was $21.4.
Assorted Pitcher Notes (in no particular order):
- The most profitable pitcher of 2019 was Liam Hendricks, who was undrafted in NFBC auctions. For a FAAB pickup, Liam earned owners a full season value of close to $19.
- Hyun-Jin Ryu was the most profitable of the drafted pitchers this season. A $7 cost earned fantasy owners $17+ in profit. Since Hendricks is a relief pitcher, Ryu was the most profitable starting pitcher in 2019.
- Of the top 10 most profitable pitchers, only 4 of them were drafted. None of the ten were drafted for more than $7.
- Justin Verlander ($44 $Value, $35 $AAV) is the only pitcher of the top 25 pitcher bargains to have an $AAV of over $14. Gerrit Cole (not shown) finished as the 30th best pitcher bargain. He cost $36 pre-season and returned $41 of value. There is a large void of highly profitable pitchers from $14 to $35, which further supports my contention for avoiding the middle of the road SPs in drafts/auctions.
- Jacob deGrom who was the 2018 NL Cy Young award winner, earned a -$11 profit (i.e. a $11 loss) despite finishing as the 3rd highest earning pitcher. He amassed $29 of value but cost $40 at auctions.
- Stephen Strasburg was “Mr. Even Steven” this season. His $AAV was $24, and he earned exactly $24 in 2019.
- There were only 3 pitchers in 2019 who cost at least $20 to roster yet turned a profit. They are (in order of cost): Gerrit Cole, Justin Verlander and Zack Greinke.
- About half of the pitcher bargains earned saves during the season (i.e. were relief pitchers). This is typical.
- The average cost of the top 25 pitcher bargains (including undrafted players at $0.10) was $4.0. The average returned value was $15.7.
Ariel is the 2019 FSWA Baseball Writer of the Year. Ariel is also the winner of the 2020 FSWA Baseball Article of the Year award. He is the creator of the ATC (Average Total Cost) Projection System. Ariel was ranked by FantasyPros as the #1 fantasy baseball expert in 2019. His ATC Projections were ranked as the #1 most accurate projection system over the past three years (2019-2021). Ariel also writes for CBS Sports, SportsLine, RotoBaller, and is the host of the Beat the Shift Podcast (@Beat_Shift_Pod). Ariel is a member of the inaugural Tout Wars Draft & Hold league, a member of the inaugural Mixed LABR Auction league and plays high stakes contests in the NFBC. Ariel is the 2020 Tout Wars Head to Head League Champion. Ariel Cohen is a fellow of the Casualty Actuarial Society (CAS) and the Society of Actuaries (SOA). He is a Vice President of Risk Management for a large international insurance and reinsurance company. Follow Ariel on Twitter at @ATCNY.
Auction calculators take into account playing time when it comes to batting average, right? Like hitting .340 over 600 AB is almost certainly better for your team average than hitting .350 over 400 AB. I assume this must be the case, since I’ve never seen a part time guy who hit .400 listed at the top of an end-of-season valuation model.
Does it work this way for counting stats, too? Comparing Mitch Garver and Josh Bell implies that Bell’s additional 24 R, 6 HR, 49 RBI, and 4 points of average is only worth an extra $4, which I find difficult to believe. is this accounting for Bell’s additional 200 AB?
If this is the case, is it possible to construct a scenario where one batter has better stats across the board than another, but is still worth less in an auction due to playing time disparities?
It’s a fairly outlandish hypothetical, but I’m thinking somewhere along the lines of
50/15/50/5/.250 over 200 AB vs.
60/20/60/8/.260 over 500 AB
I can’t say for certain, since I don’t know with 100% certainty how the FG auction calculator works, but most Z-Score based methods incorporate playing time for batting average value.
The basic idea is “Hits over Average.” If the average of the pool is .250 and you hit .300 over 200 ABs, then you are 10 hits over average. If you hit .275 over 400 ABs you also are 10 hits over average. Those players would generate the same Z-Score.
For the counting stats, there is no adjustment for playing time. Do any adjustments yourself before valuation.
Good questions. Mitch Garver should really be the most valuable catcher this year because it should be calculated with him plus whoever you would use for the additional 300 PA.
So maybe their combined average comes down, but even if you used him and Maldonado or Gomes, that gives you an additional 12 HR and 30-40 R and RBI. Garver + Maldonado = 43 HR, 116 R, 94 RBI.
That’s definitely better than Realmuto (25/92/83) or Grandal (28, 79, 77). Even if the Galdonado batting average would be about .250.
So if Lorenzo Cain is worth $18, then I should set him in my pre-draft rankings at $17 which is what he should rationally be valued at at auction. But if he’s actually worth $17, then I should set him to $16 then. But if he’s worth $16, in that case…
Not exactly. There is a discount curve. For $40 players, you may want to buy them at a $1-2 premium. For $20 players, you may want at least a $4 discount, etc.
I like to operate with the values as is, but have the discount curve on the side next to it to know what to pay for them at an auction.
Its a bit more complicated than that, but that’s the basic idea.
Have you done any articles on a discount curve? I intuitevy agree with what you are saying, but it’d be great to see some more details on it. And either a graph or a method to build your own league-focused discount graph.
I have not done a specific one, but here’s one where I mention it …
https://fantasy.fangraphs.com/2018-projection-systems-comparison-a-game-theory-approach/
The main complication is simple in concept, and that is that you need to maximize not your total excess value, but your total overall value — I.e., you have to get as much bargain value while spending your whole budget.
To illustrate, if you spend $2 apiece on 23 players and they all end up earning $10 of value, congratulations, you have received an excess of $184 of player value over what you paid, undoubtedly the tops in your league!! Unfortunately, you also have a crummy team, because you have a starting lineup that earns a total of $230 of value, while anyone that spent their entire $260 budget and got merely what they paid for, $260 of value, has your team beat by $30 of value.
So you want to find values at many different price points so that you maximize your budget, and therefore your total overall value.
I have used a discount curve for several years, but I’ve found it has to be tailored to the behavior of the owners in the league. In my league, owners overbid the top players and underbid the bottom players. Thus I use a reverse S-curve to multiply projected values – higher at the top (e.g., a 1.2 multiplier) , par in the middle, and fractional at the bottom (e.g, 0.6). I justify (rationalize?) paying more at the top because those players can provide a larger fraction of your category values.
Even with this you still have to try to get ATC’s profit
You are correct. Take a look at the very rough discount curve I have here in this article:
https://fantasy.fangraphs.com/2018-projection-systems-comparison-a-game-theory-approach/
As an aside, this article was nominated for Baseball Article of the Year last year by the FSWA, and is worth a read.
Great Article. I had the same question about why Cain was such a bad deal at his projection value?
Moreover, why do you use a rough discount curve to smooth out results? It seems that if a projection system undervalues top 50 players that it would be more accurate to either
change the projections to be less conservative OR
change the auction calculator/z-score weighting before using some rough magic number.
Thank you!
At the $18 level in a mixed auction (and I believe his was a 12-team league), players shouldn’t be purchased at value. You need some $2+ discount. If a player here or there is purchased a dollar or two over, that’s fine – but my friend likely purchased most of his players roughly at value.
If according to your OWN projection set, you don’t come out of the auction with $290-300+ of value, it means that you failed. If you show that you have $260-$270 of value from your own numbers – what do you think your competitors will show that you are at? Likely underweight.
As long as you can spend ALL of your money, there should be discounts available at every stage throughout the auction.
As an aside to this aside, that would be an excellent analysis to revisit on a year over year basis so as to assess the relative worth of each of the included projection systems.
You are correct there. It is your total value that is key – which generally means you need two expensive players at the top, and then plenty of bargain players after that.
When doing optimization exercises though, the top bargain players will be found on the optimal team solution.
Hey Ariel,
Great article as usual! Any idea when the first run of ATC 2020 will come out? It would be useful for Ottoneu arbitration.
Thank you for that!
I certainly DO have an idea when ATC will come out! I do my biggest number on crunching on Martin Luther King Jr. Day, which is also late enough that ATC is highly credible. The first cut of ATC usually comes out sometime later that week.
Hope that helps you with timing. 🙂
Enjoyed reading this!
Thank you very much!
How close was Woodruff to making the pitcher list?
Woodruff was #37 with a $5.4 $Bargain.
I don’t mean to belittle this post – I really don’t – but anyone who does auction drafts knows getting bargains/value is key to drafting a winning team. Targeting those players and actually getting them at discounts is another story. Sometimes you can maybe get a guy you want at a good price. Most of the time, though, it boils down to luck. I got Alonso and McNeil on the cheap in my NL-only this year, for example, because it was toward the end of the draft and I needed to fill spots. At the time, no one knew whether Alonso would break camp, let alone hold the 1B job when given a chance. I paid $1 (out of $26) to get him and it obviously paid off big time. But again, it was a good element of luck here. You make judgments during the draft, evaluate the risk/reward and take chances. And no question, you should try to keep a stash for the end for players who could give you a solid ROI.
I don’t see anywhere here where you disagree with me in principle. And I agree with you that there is a strong element of luck involved. Would you call the game of poker a luck game? It is not. Over time, a stronger player will make the right percentage plays and will win in the long run.
Alonso and McNeil are but two data points that illustrate profitable buys for you that turned roster fillers into league winning players. Now I personally was high on McNeil. So was my colleague Alex Chamberlain. My partner, Reuven Guy was high on Alonso – so if we played in your league, you surely would not have rostered them.
But your point is valid. It is about evaluating and controlling the risk. Here at FanGraphs, I try to clue the readers in on how to do that – at least to give everyone some points to think about before drafting one’s team.
I disagree though that “anyone who does auction drafts knows getting bargains/value is key.” Most people that I encounter don’t to do that, or know how to do that.
I don’t think we disagree. Your post just makes obvious points that anyone who does an auction already knows. Maybe if you were in my league you would have gotten Alonso and McNeil. Maybe. There’s no way to know the answer to that question. Every year I go into a draft with a list of guys I’d want. But then the dynamic of the draft ensues and things become unpredictable. Maybe you’ve already spent more than you wanted to for someone. Maybe at some point you realize the supply of closers or catchers is dwindling, and so you make another buy there that impacts things. Then you find you can’t get the guy/s you were after. Maybe somebody overpays for an Alonso or McNeil and you have to bow out.
In an auction, the prices of players changes with every player purchased. One guy in my league is a math teacher and has a program that uses standard deviation on prices as the draft moves along, LOL. The dynamic of auction drafts is what makes it so interesting and challenging. You have to constantly make adjustments and the real-world price of a player isn’t the same as it is during the draft where the supply/demand equation is constantly in flux.
Its funny – you mention the math teacher that uses standard deviation dynamically, etc. – I do a number of those things, including an “anti-correlation” algorithm that let’s me know which players fit my portfolio the best, and who I should spend the extra $1 on, etc.
Auctions are the best!
Good success to you in 2020, and keep reading my work!
For Trout/Mancini, shouldn’t you factor in the replacement player you could use for the last 3 weeks of the season after Trout was hurt. I would guess that the counting stats benefit would outweigh the negative effect on the rate stat and the acquisition/roster cost.
Well, for Salvador Perez, he should similarly get a replacement level player as well. Basically, the analysis you are suggesting (which is not a bad approach) would be to add in the replacement level player for the duration of a player’s time on the IL.
This doesn’t account for variance of outcomes or adjust based on AAV. It is almost tautological that cheap players will provide more ‘value’. – there are more cheap players, they have higher variance outcomes, and great players would need to put up the best seasons in the history of the game to create similar ‘value’. It also doesn’t account for the quality of your opponents. If you don’t pay a premium for top talent then you won’t get any expected studs and you will have to rely on hitting every LaMahieu and Alonso out there or you finish in last. You could make a team of $1 AAV players who all put up tremendous value and you would destroy your league in surplus value, and you would lose every time.
If you could identify next year’s top surplus players with any significant abnormal accuracy you would already be a multimillionaire many times over.