Earlier this week I discussed some general auction principles. This was mostly to set up Part Two of this series, a study focusing on dissecting three auctions of identical format and specifications. What follows today is a lot of data with some observations. Early next week I’ll conclude the troika by incorporating my findings into my general approach to auctions.

Before we get into the crux of the presentation some general framework needs to be outlined.

It’s integral to understand what transpired in the trio of auctions investigated won’t necessarily emulate what happens in your auction. That said, experience has taught me there are some transient principles which I will point out.

I briefly touched on some valuation principles in Part One but I want to elaborate just a tad. As noted earlier in the week, fantasy baseball is a zero-sum game. There is a fixed number of dollars in the economy. Conventional valuation assigns $1 to the lowest drafted player at each position and scales upward relative to expected production such that exactly as many players that are on the initial active roster of each team have a positive value. This will be important to keep in mind when we take a look at the data.

The leagues in question are all 15-team mixed with standard 23-man roster (14 hitters, 9 pitchers). There are two catchers, one at each infield spot, five outfielders, a corner infielder, a middle infielder and a utility. The leagues are all National Fantasy Baseball Championship satellite leagues so they are pay leagues. They were conducted within one week of each other so the news had not changed all that much. The projected values I use were mine at the time of the auctions.

What I do is look at the number of player purchased between different ranges and compare the auction price to my projected value. Specifically, I count up the number of players purchased in each range that I projected lower, higher and the same. I use five-percent as the filter. Players bought within five percent of my projected value are deemed the same. Players purchased for at least five percent more than my expected cost are labeled over and in my estimation were poor purchases (please keep in mind their owner may have a different expectation). Players selling for more than five percent below my projected price are called under and are good buys in that they have built-in profit if the player produces as expected.

So without further ado, let’s take a look at the three auctions.

AUCTION ONE

RANGE PROJ SOLD over under same
$50+ 0 1 1 0 0
$40-$49 1 2 2 0 0
$35-$39 2 4 4 0 0
$30-$34 5 6 4 1 1
$25-$29 18 17 8 1 8
$20-$24 33 35 15 9 11
$15-$19 44 50 28 16 6
$10-$14 70 55 31 18 6
$7-$9 59 35 16 15 4
$4-$6 52 54 23 28 3
$3 16 21 9 11 1
$2 21 22 6 15 1
$1 24 43 17 24 2
TOTAL 345 345 164 138 43

AUCTION TWO

RANGE PROJ SOLD over under same
$50+ 0 0 0 0 0
$40-$49 1 2 2 0 0
$35-$39 2 3 3 0 0
$30-$34 5 8 7 0 1
$25-$29 18 21 13 3 5
$20-$24 33 32 17 8 7
$15-$19 44 43 25 14 4
$10-$14 70 62 31 26 5
$7-$9 59 48 19 21 8
$4-$6 52 35 13 18 4
$3 16 25 10 14 1
$2 21 27 9 17 1
$1 24 39 22 15 2
TOTAL 345 345 171 136 38

AUCTION THREE

RANGE PROJ SOLD over under same
$50+ 0 1 1 0 0
$40-$49 1 2 2 0 0
$35-$39 2 2 2 0 0
$30-$34 5 6 3 1 2
$25-$29 18 27 15 0 12
$20-$24 33 24 12 6 6
$15-$19 44 46 22 17 7
$10-$14 70 67 39 22 6
$7-$9 59 41 17 18 6
$4-$6 52 48 24 20 4
$3 16 18 9 8 1
$2 21 17 3 13 1
$1 24 46 20 24 2

Let's combine the data from the three auctions to get a better idea of what happened within each range.

RANGE SOLD over under same
50+ 2 2 0 0
40-49 6 6 0 0
35-39 9 9 0 0
30-34 20 14 2 4
25-29 65 36 4 25
20-24 91 44 23 24
15-19 139 75 47 17
10-14 184 101 66 17
7-9 124 52 54 18
4-6 137 60 66 11
3 64 28 33 3
2 66 18 45 3
1 128 59 63 6

OBSERVATIONS

1. Combining the three auctions, 17 players were purchased for more than $35 and each went for considerably more that I projected, led by Mike Trout. Owning Trout is great, but there is no profit possible at $50-plus which means there is no chance of getting a positive return on your investment on about 20 percent of your budget. In fact, you're almost assured of netting a loss.

2. Twenty players went between $30 and $34 with 14 costing more than I projected, four went for less than expected with two being spot on. If you wanted to invest in a top player, this is the range to begin. But even then, on the average, only two players in the entire auction could be purchased in this range at or below expected value.

3. While there weren't many bargains, at least there were a decent number of at-value purchases in the $25-$29 range. This will be relevant next time when specific strategies are discussed.

4. The vast majority of good buys occurred below $25. The key is finding the balance between doing your damage in this range and still spending your entire budget. As a harbinger, that's where the $25-$29 range may come into play.

5. Jumping to the bottom, note how many players conventional valuation systems price at $1-$3 as compared to how many players are actually purchased, especially in the $1 range. This will be most relevant next time when the strategy of stars and scrubs is discussed.

6. Further, check out how many players purchased for $1 were actually OVERPRICED! This can only mean one thing; each auction had players bought that I didn't even have on my draft-worthy list. On the average, there were 44 players per league that I would not have paid even $1 to own. These 44 players averaged $85 worth of value. That's $85 worth or profit (according to my numbers) that is built into the inventory. Not to mention, on the average, the absolute worst player on my roster is at least the 45th from the bottom. This is a $4-$5 player than I can get for a buck.

There's a lot here to digest so we'll call it a day. Early next week I'll conclude the trilogy with detailed outline of how I approach an auction, citing examples from the above data to justify the process. To that end, it should be reiterated that not every league will follow this exact same trend, but they are close enough that the experienced player should be able to recognize and pounce in the soft spots if they are patient.




Comments

Todd Zola 

As I will rant about - umm - talk about is overpaying is still overpaying. Why give back profit in the end game? Why not supplement profit garnered elsewhere?

Tom Z. 

Todd, Very interesting read. I am in an AL only league that is heading into our 31st season. We have had 10 teams most seasons, but have had some with only 9. During the seasons with 9 teams, I have felt much more comfortable going the extra buck or two to get top tiered players, as the dollar end game picks had more value. A more balanced approach seems to work better when we have 10 teams as it is challenging to find dollar players that will return a positive return. I think this might partially explain why higher priced players were sold more than you were predicting, as a 15 team mixed league only penetrates 50% of the player pool. At this level, the $1-$5 players are still pretty valuable in relationship to their auction prices. I bet if you look at three 18 (or 20) team mixed leagues, you would find less players reaching the $40 price range.


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About Todd Zola

Affectionately known as Lord Zola, Todd was the 2013 Fantasy Sports Writers Association recipient of the Fantasy Baseball Article of the Year, Web. He's been with Mastersball since its inception in 1997 and presently Todd writes for the ESPN Insider and Baseball HQ. Todd is a frequent guest on SiriusXM and is a regular on HQ Radio. He's a veteran of Tout Wars and LABR as well as a multi-time NFBC champion. Follow Todd on Twitter @ToddZola

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