ASK ROTOMAN: Altuve v. Heyward

Hi..

I’m in a 14 team .. 5×5 rotissire league that can keep players for $5 more then they were purchased the year before..

I have Jose Altuve at $1 (can be kept for $6) but I can trade him for Jason Heyward at $16 (Can be kept for $21)..

I’ve always loved Altuve but im not buying his magazine listed price as an over $20 player.. what are your thoughts on that deal???

“Head Over Heart”

Dear HoH:

If you really love Altuve you’ll keep him for $6. He earned $25 last year. Heyward earned $26, not that much more. So the question here is why would you distrust the $22 price in the Guide, and why would you distrust it so much that Heyward would look like a better keeper.

Remember: Who you keep is a function of who would save you the most money above their keeper price on draft day, assuming you want them on your team.

If you don’t want Altuve on your team, that’s fine, but here are some facts:

Last year Altuve earned $25 in 5×5, according to me. According to Alex Patton he earned $24 in 4×4. I think it’s safe to say in an AL only league he earned in the low to mid 20s.

This year, the CBS Sports experts league paid $24 for Altuve (that’s 5×5), while in LABR he went for $19. I think Altuve is worth $22 this year (a 23 year old coming off a $25 season can only be discounted so much), but even if you buy the LABR valuation, you’re saving $13 keeping him at $6.

Jason Heyward earned $28 in 5×5 last year, I say. Alex Patton says he earned $30 in 4×4.

This year, the CBS Sports expert league paid $28 for him, while in LABR he went for $30. I think he’s worth $28 this year, but even if you buy LABR’s price (and I’m not saying that’s wrong), you’re saving $9, which is less than you’re saving with Altuve.

Plus, of course, you’re spending more than three times as much to get the savings. We just gave every rounding edge to Heyward and the numbers still point to Altuve. I think you have to keep the smaller man.

Here’s another way to look at it, assuming 10 percent inflation in your league:

If you throw back Altuve, it’s going to cost you $22 to replace him, based on LABR’s low price. That’s $16 over his freeze price.

If you throw back Heyward, it’s going to cost you $33 to replace him, based on LABR’s high price. That’s $12 over his freeze price.

The bottom line is that you’ll do better freezing Altuve and buying Heyward on draft day than vice versa, even though Heyward is the better and more attractive player overall.

Quickly,
Rotoman

Outliers: Shopping for VMart at Walmart

walmartlogo One of the players my projection and my initial bid price deviated on most was Victor Martinez. VMart was one of the game’s best hitting catchers, but he missed all of 2012 (his age 34 season) with a torn ACL. After earning $26 and $21 the preceding two years before the injury, he would seem to be a $20+ player this year, even while aging. But a closer look made me wary.

Between 1947 and 2000, four players earned 10+ dollars in their 33rd year and then missed all of their 34th year. None of them played again.

In that same time frame, five players earned 10+ dollars in their 32nd year and then missed most of their 33th year. Only one, Danny Tartabull, came back, and he had one $10 season and then retired.

During that same period, four hitters earned $10+ dollars in their 31st year and then missed most of their 32nd year. None of them earned more than $6 the next year, though two did earn $17 in their 34th year.

Obviously these are small samples, but when we widen it to include even hitters who weren’t that good the year before they missed a season, the tendency is clear: Once you’re in your 30s it’s hard to come back.

None of which is to say that VMart can’t come back. He’s swinging a hot bat so far in camp, and is going to be hitting behind Miguel Cabrera and Prince Fielder, which isn’t going to hurt. But while the projection, which doesn’t really figure in the injury, is strong, my sense of where the bargains lay makes me wary. History says he’s not likely to be nearly as good as he was before he missed the entire year, because of rustiness and conditioning and aging issues. I wouldn’t be unhappy with him for $10 at all, but he’s likely to go for more like $17-20. At that level I’ll pass.

Outliers: Finding Disagreement With Myself

Creating my initial Bids and my initial Projections are two discrete processes.

For the Bids I sit with a player’s history of Cost and Earnings, look at his age and any injury information, and try to determine how much I think he’s worth and how much I think everyone else thinks he’ll be worth, since everyone else is who I’ll be bidding against. If I’m way higher than I think the market will be, I’ll shave my bid down so that it will win, but not tower above the competition. And if I’m way lower than I think the market will be, I’ll bump my bid up to just below the market. I want to indicate my predilections, but I’m also trying to describe the market as a whole, so the prices are useful even if you disagree with me.

My projections come in two phases. The first is running a player’s historical data, including a bunch of component parts (batted ball data, mostly), through my projection formula, which also takes into account age and league and home field and league. This gives a rough idea of what players will do but has to be adjusted for playing time, and for changes in roles. After those adjustments the projections run in the Guide, and a similar but more complex set (more categories, mostly, and more time to smooth anomalies) run in the Patton $ software, at first. As spring training progresses I tweak the projections manually, mostly for playing time with veterans, but also to deal with differing situations on teams with platoons and competition and as I get a better sense of new players and their roles.

Once the projections are loaded into the Patton $ software they get priced using Alex’s formula, which is an excellent way to discover what the projection formula is telling me, especially when it differs substantially from the bid price. I’ve been going through the lists, looking at some of the substantial differences, assuming that these are players who might be of special interest this year.

HITTERS (Proj$, PK5)

Mike Trout ($49, $41): The bid predated the reports about Trout’s reporting weight. It assumes he’s not going to be nearly as good as last year, but still plenty good. THe projection is a result of increased playing time, even though he’s projected to not be nearly as good as last year. Verdict: Assuming he can run once the season starts, I would be fine standing by the projection, but I think there’s enough risk of sophomore slump and/or other issues that I wouldn’t bid more than $41.

Albert Pujols ($36, $31): The projection is remembering Albert’s past greatness. Age deductions of significance don’t kick in until the mid 30s. He could be great again, but the trend is clear. Verdict: One reason to bid $31 on Pujols is that he could put up another $36 year. But counting on an aging player to keep running is a mistake. I’ve bumped his projection down a bit, especially the SB.

PITCHERS (Proj$, PK5)

Joaquin Benoit ($15, $1) The bid is wrong. It is the standard bid for a setup guy in 5×5. Especially a guy on a team with a different pitcher named as closer (Bruce Rondon) and at least two other worthy CIW candidates (Al Albuquerque and Phil Coke). But it’s wrong because I’m projecting Benoit to be the closer at some point this year, and to do a good job at it. So, I’m bumping him to $3. That may seem silly, but that’s what he’s worth if Rondon does the job (I doubt it) or one of the other guy ends up the closer. Verdict: Right now Benoit is a closer in waiting. Maybe not even first on line. The reason closers in waiting are valuable is because you don’t pay much for them. So until there’s more smoke, I’m going to keep the bushel on this fire.

Andy Pettitte ($12, $1) He’s 41 years old this year. He only pitched 79 innings last year, and took the year before that off. It’s fine to say last year’s injury was not age related, but not many pitchers stay effective and healthy into their 40s. The projection reflects what he might do if he stays healthy, but the bid is a severe hedge. Verdict: It will be in the $8-$10 range if he emerges from ST in the rotation.

More to come!

ASK ROTOMAN: Calculating Inflation

Rotoman,

Years ago The Fantasy Baseball Guide had a section where there was a formula for inflation in keeper leagues. I think maybe the article was from maybe seven to nine years ago? It may have been even 10 years ago. Would it be possible to have that formula again?

Thanks in advance,
Charles

Dear Charles:

To calculate inflation:

Subtract the bid prices of the frozen players from your total league budget. That leaves you with how much money will be available to spend in your auction.

Subtract the projected value of the frozen players from the total league budget. That leaves you with how much talent will be available to spend in your auction.

For instance, in a 12 team league the total budget is $3120. Let’s say the price of all the kept players is $500. Your league will have $2620 to spend.

If the projected value of the frozen players is $1000, your league will be chasing $2120 worth of talent with $2620 of money. Divide the talent into the money and you discover that your inflation rate is 24 percent.

Note that the inflation is usually not distributed evenly in the auction. You should allocate the $500 inflated dollars to players you want (being realistic about what other players might go for and distributing inflation to them, too). The danger is backing off the best players because their price is 24 percent over the “book” value, letting them go at par, and then getting stuck spending your inflated dollars in the endgame so you don’t leave money on the table.

Largely,
Rotoman

Get Your Mid March Fantasy Baseball Guide 2012 Update Here!

Download the spreadsheet by clicking here. Includes fully updated projections and bid prices for 5×5, just like in the Guide.

Questions about a player? Come visit pattonandco.com and join the discussion.

Illustrating the Projection Problem: Real Life Example

Last post I wrote about how accurate projections have to regress player performance to the mean. I used the example of AB, since it is simply a measure of playing time and role, not subject to the variance that Hits is, for example.

Here is a chart showing the Top 10 2009 AB Leaders, and how they did in 2010.

Read more…

Projections are not prices, Part 1

PROJECTIONS ARE NOT PRICES, Part 1

Winning at playing fantasy baseball has two obvious components:

Player Projections and Player Pricing.

It is, one assumes, most helpful to have the best projections, because they tell us what players are going to do. The best set of projections would give you the best idea of who is going to be good this year, and who is going to be not so good, and this information should give you an edge over someone who doesn’t have such good projections (or no projections at all).

Plus, good projections should lead to better prices. If you know better than anyone else what the players are going to do in the coming year, you should be better able to value a home run, for instance, in the context of all the other home runs hit, and so on and so forth for all the categories. This would give you a better price in each category for each projection and overall more accurate prices for all players.

This is how good projections are thought to lead to winning fantasy teams, but it just isn’t so. At least not when it comes to the conversion of projections into prices to pay at auction. The fact is that accurate projections are a map of regression to the mean. In making accurate projections we average out the highs and lows of a player’s history, in order to better identify his baseline, which is the core description of his true talent.

A perfect illustration of this comes from the projection of at bats. In any given year six to 10 hitters will accumulate more than 700 PA. These are, obviously, guys who have and hold the leadoff position in the lineup, on good teams, all year long. But when one uses regression analysis to look at past history of players with more than 700 PA in a year, the math comes back that that sort of player will have 630 PA in the subsequent year.

What the formula does is look at the, let’s say, 10 hitters with 700 PA each (for a total of 7000 PA), and notes that on average in subsequent years a player in that group will have, on average, 630 PA. Now this could break out in a variety of ways. Nine might have 700 again, and one 0, or 5 might have 700 and five might have 560. The specifics are changeable, but the point is that based on the actual history of baseball players over the past 40 years or so, what we know is that on average each of the top 10 PA guys in one year will have 10 percent fewer at bats the next year.

What we also know, is that most of the leading PA guys in one year will be the leading PA guys the next year, with about 700 or more.

And what we don’t know is which player or group of players is going to fail and bring down the average PA of the group.

So, is a good projection the one that gives each of the 10 players 630 PA, spreading the risk between them?

Or is a good projection one that gives each of the 10 players 700 PA, getting more of them individually right, but making the misses that much more wrong?