Archive for February, 2009

Net Steals, K/AB, and K – BB

18 Comments
February 28th, 2009 by
Categories: Price Guide, Site News

I’ve got a handful of Price Guide updates that I’d like to make you aware of:

  • New categories: Net Steals (SB – CS) and K/AB for hitters, K – BB for pitchers. If you happen to be in a fantasy league that uses those exact three categories, Juan Pierre is the man you want. Ryan Howard comes in at a spectacular -$64.
  • The league averages now show up for rate stats (BA, ERA, WHIP, etc.) In a standard league, the Price Guide projects the average hitter to bat .279; the average pitcher will post a 3.73 ERA and a 1.26 WHIP.
  • I’ve been experimenting with a way to export the Price Guide’s results to a spreadsheet. For those of you who like to poke around, you can see an early version if you add “&o=CSV” to the querystring. I haven’t quite got it working for minor league players, but it’s a start.

As always, let me know if there’s a feature you would like to see.

Ryan Howard or Mark Teixeria?

8 Comments
February 26th, 2009 by
Categories: Other Sites

Yahoo’s Roto Arcade made a characteristically pun-filled comparison of Ryan Howard and Mark Teixeria:

Undoubtedly, Teixeira will hit for a healthier average, but his power numbers, even in the Bronx Bombers’ loaded lineup, will pale in comparison. Howard will likely finish with 8-12 more homers and 15-30 more RBIs.

The Price Guide’s composite projection gives Howard a 12 HR advantage and an extra 14 RBI — pretty close to what Brad Evans guesses, although more optimistic about Teixeria’s RBI chances.

However, the Price Guide has Howard batting a surprisingly solid .272 this year. That’s quite an improvement from the .251 he batted last year, but remember that he did manage to hit .313 in his MVP-winning year. Assuming that Howard can hang with Teixeira in AVG, his advantages in HR and RBI put Howard about $4 ahead of Tex in a standard league or $7 up in a Yahoo-style league.

So which one do you pick? (Yahoo’s poll indicates a preference of 2:1 for Teixeira.)

The answer might be neither of them. In the same price range as Howard and Teixeira, we also find Lance Berkman and Prince Fielder. Personally, I don’t have any strong feelings about any of those four, and I’d probably take whichever player is looking like the best bargain on draft day.

Tiering Up, Part II

4 Comments
February 25th, 2009 by
Categories: Strategy

Yesterday, I talked about how splitting players up into tiers before a fantasy draft can be a useful exercise. Today we’ll look at some of the problems that tiers can create.

Consider the 3B values the CHONE projections give for a standard fantasy league:

Alex Rodriguez $43
David Wright $41
Aramis Ramirez $19
Garrett Atkins $19
Chipper Jones $12
Ryan Zimmerman $12
Chris Davis $10
Kevin Youkilis $10
Adrian Beltre $9
Edwin Encarnacion $9
Chone Figgins $8
Aubrey Huff $7
Troy Glaus $7
Ian Stewart $6
Evan Longoria $5
Carlos Guillen $5
Mark Reynolds $4
Jorge Cantu $4
Hank Blalock $2
Alex Gordon $1
Kevin Kouzmanoff $1
Melvin Mora -
Mike Lowell -

We’ve decided that there’s clearly a top tier of A-Rod and Wright — no one else is valued at even half of their prices. The second tier is also easily demarcated by a $7 drop after the next two players, Ramirez and Atkins.

But do you see any tiers after Atkins? I’m seeing a pretty steady decline from $12 to $1.

Let’s say we decide to split the remaining players into roughly equal-sized groups, drawing the line between Troy Glaus and Ian Stewart. That gives nine players from $7-12 and eight from $1-6.

But does it make sense to say that a $6 player is closer to a $1 player than he is to a $7 player? That would be prefering a $5 difference to a $1 gap, which doesn’t seem logical to me.

This is the problem with tiers: They work fine for about the upper 20-25% of players, where you can find clear separations between groups of players. But for most of the draft, there just aren’t big gaps in value between players. In these situations, I’d argue that attempting to separate players based on arbitrary dollar value cutoffs does more harm than good.

Tiers of Common Traits
So what can we do for players in the mid-to-late rounds of a draft? One idea is to group players by similar traits instead of strictly relying on dollar values. For example, with the 3B above, we might form a fantasy tier of Solid Yet Possibly Declining Veterans with Chipper, Beltre, Glaus, Guillen, Mora, and Lowell. We might form a Young, High Risk/Reward Tier with Davis, Stewart, and Longoria.

With tiers formed by common characteristics, you can get some insight that you don’t get with value tiers. If your early picks at other positions were geared towards players with lots of upside (and downside), maybe you should draft the best available 3B in the Veteran Tier. A consistent performer like Beltre can bring some balance and stability to your team.

If you have played it safe in the early rounds, maybe now is the time to take some risks. I highly doubt Longoria will still available, but Ian Stewart is an intriguing player if he gets some playing time. Why not roll the dice and and see if you can grab a bargain?

Stat Category Tiers
Maybe we go a slightly different route and form tiers based on common statistical contributions, while relaxing the positional requirements. We make a tier called Late Speed Options that has Figgins, Pierre, and Taveras. There’s a Good Batting Average Tier with Polanco, Loney, Kendrick, and Helton.

Suppose you get near the end of the draft and your team is looking light on AVG. You have an OF spot open and a MI spot available, so you can look in the Good Batting Average Tier for the best player left that you can put in one of those two spots. That player might not be the highest player on your overall draft board, but he could still be the best choice for your team.

Do you see any other ways to divide up players into meaningful tiers?

Projection Updates

8 Comments
February 24th, 2009 by
Categories: Site News

Some of you have already noticed, but there are a couple of updates with the projections on the Price Guide:

  • CHONE projections are now updated to the 02/23 release. Not a big change for most players, but I think it will update the park factors for players that have switched teams since December.
  • I have added a Composite projection as the new Price Guide default. This is my own brew of the various projections that should knock some edge off the occasional extreme prediction. It’s mostly CHONE and CAIRO with a little bit extra thrown in.
  • I finally decided to list Matt Wieters as a catcher. The Price Guide previously went strictly by games played in 2008 to determine qualifying positions. Since Wieters hasn’t hit the majors yet, he was being counted at Utility. Counting him as a catcher significantly changes his value.
  • The Price Guide results now show the league average in each category for your league. Currently that’s more helpful for counting stats than for rate stats, but I’ll try to get them all working soon.

Please let me know if you have any opinions about these changes.

Tiering Up, Part I

13 Comments
February 24th, 2009 by
Categories: Strategy

I imagine that most people are already aware of the concept of tiers — the idea of placing players into groups with similarly valued players.

Today, I’m going to look at what I consider to be the benefits of using tiers for your draft preparation. I’ll address some of the problems with tiering tomorrow.

So what’s to like about tiers? Well…

Tiers recognize that projections are far from exact.
In fantasy, it doesn’t really matter much if your projections have Alex Rodriguez valued at $43.48 and David Wright at $42.21. At the end of the year, either one has essentially the same probability of outearning the other.

Ron Shandler has noted that even the best projections will only fall within +/- $2 of what a player earns about 46% of the time for batters and 37% of the time for pitchers. With that margin of error, it’s not a big deal to go to $45 on David Wright. It’s not the end of the world if you stop at $40 for A-Rod.

With tiers, we don’t make a big deal about that $1 difference in their projections. We put A-Rod and Wright in the same tier. We know there are pros and cons with either one, but we also recognize that they are very similar in value.

Tiering recognizes that the important thing is realizing that both players should be valued somewhere around $40+.

Tiers show where there are gaps in value.
So we have put A-Rod and Wright in the $40+ Tier. What is the next tier of 3B? According to CHONE, it’s Aramis Ramirez and Garrett Atkins, both at $19. (See note on Longoria below.)

That’s less than half of the value of our top tier players! In draft terms, we’re dropping from early first round players to somewhere in the fourth round. Below these two $19 players is another $7 drop down to Chipper Jones at $12.

Mind the gap!

These gaps between tiers is especially important information in a draft: Let’s suppose it’s your pick, and you are choosing between Atkins and Brian Roberts. You have Roberts ranked marginally higher than Atkins. Your 2B rankings have Brandon Phillips, Dan Uggla, and Robinson Cano ranked just below Roberts — all in the same tier. Atkins is the only remaining player in his tier at 3B.

Although Roberts is projected to be worth more, in this situation, you might consider taking Atkins over him. The values are close, and there are other 2B options in the same tier as Roberts.

All else being equal, you should prefer to pick a player at the bottom of one tier over a player at the top of another.

The main things to take away from tiers are that they can help you to mentally group similar players, and they can show you where gaps lie between players at each position.

But are there situations where tiers don’t work? That will be our topic tomorrow.


*”What about Evan Longoria?” you ask. “He’s been going for $25-30 in auctions.” Well, for this example, I’m just using the CHONE projections, and CHONE puts Longoria at $5 in a standard mixed league. “Five dollars?!”

Now, I’m not saying that I agree or disagree with that projection, but it does give me pause… There could be some very disappointed Longoria fans this year.

Rotoworld’s Pitcher Values

8 Comments
February 23rd, 2009 by
Categories: Theory

You may have noticed a recurring theme here is dealing with valuing pitchers relative to hitters. Average draft position starts drafting pitchers in round 2 and doesn’t really get going on them until the fourth round. The Price Guide (as well as several other sources) tends to rank the top-tier pitching higher and advocates grabbing Santana in the first round.

(Since it’s a topic I seem to be stuck on, I have appreciated the comments that have been left on the various pitcher/hitter ADP posts. Lots of stuff has been written that has really made me think about this.)

Anyways, being ever vigilant for evidence that supports one approach or the other, I took a look at how Rotoworld valued pitchers. Here are a few SP dollar values from their magazine, with overall rankings included:

5. Johan Santana – $37 (tied with Pujols)
14. Tim Lincecum – $31
19. Roy Halladay – $30
22. Cole Hamels – $29
26. Brandon Webb – $28
29. CC Sabathia – $28

Not quite as aggressive as the Price Guide, but considerably higher than ADP. Actually, those are probably a good indication of what you would end up paying if you were following the Price Guide and the rest of your league was using ADP.

Another New Price Guide Category: Pitcher Walks

20 Comments
February 21st, 2009 by
Categories: Price Guide, Site News

By request, I’ve added another stat category for the Price Guide: pitcher walks.

It works as you would expect in a normal league (i.e. walking fewer batters is better).

Please let me know if there are any other categories you are interested in. If it’s a stat that is typically projected, it is usually pretty easy to add. (Holds and quality starts, unfortunately, aren’t projected by any of the systems.)

For those who aren’t familiar with it: The Fantasy Baseball Price Guide is an online tool that builds auction dollar values or draft rankings customized for you league. It handles any number of teams, any number of starting positions, and most stat categories. You can also edit the projected stats for any player to fit your own expectations.

SGPs Part IV: The Difficulty of Inconsistent Scales

3 Comments
February 20th, 2009 by
Categories: Theory

I have mentioned that I think Standings Gain Points (SGPs) are a pretty good method of determining player values for fantasy. However, I don’t use them for the Price Guide based on some shortcomings I have found. This week I’m pointing out some of the quibbles that I have with the SGP methodology:

If you have looked at any of the projection systems that the Price Guide uses, you may have noticed that they look a little conservative. Marcel projects Ryan Howard to lead the league with 119 RBI? No pitcher is expected to finish with more than 16 wins?

These things are not indicative of problems with the projection systems and are, in fact, positive features. While it’s very likely that someone will get close to 20 wins, it is impossible to predict who it will be. I’d bet that someone tops 130 RBI, but I don’t have a clue who it will be. When you are predicting something as unpredictable as baseball stats, the smart route is to be conservative. (Tango explains this fully here.)

So it’s clear that our projections are operating on a different scale than the real life stats. On the projections scale, a player projected for 100 RBIs is elite. In real life, he’s just “pretty good.”

What happens when you mix-and-match the projected scale with the real life scale? Standings Gain Points attempts to find out. On one hand, it’s looking at the stats from last year (the “real life scale”) to determine the relative value of each category. It then takes those values and applies them to a completely different scale — the regressed scale from the projections.

Consider saves, a highly variable stat: Players on fantasy teams will always finish with more saves than what was projected for players before the year. When SGPs look at last year’s stats, they might see about six saves separating each team (McGee came up with 6.2 – 6.3 in his book) and determine that 6 saves are worth 1 SGP.

Remember, however, that the projections don’t project that many saves! And on a scale with fewer saves, the saves that are available become more valuable.

This is a nuance that is missed by SGP, but is caught by the Price Guide. Notice that when the Price Guide determines the value of each save, it is using the scale determined by the projections themselves. Which means it is willing to value saves from the reliable closers more highly than SGP does.

SGPs Part III: The Problem of League Specifics

6 Comments
February 19th, 2009 by
Categories: Theory

I have mentioned that I think Standings Gain Points (SGPs) are a pretty good method of determining player values for fantasy. However, I don’t use them for the Price Guide based on some shortcomings I have found. This week I’m pointing out some of the quibbles that I have with the SGP methodology:

How many types of fantasy baseball leagues are there out there? Fantasy leagues might have 6 teams or 30 teams or anything in between. They use different stats: 4×4 and 5×5 and 6×6 and hundreds of other combinations. Different leagues start different positions: two catchers, middle infield, middle relievers, etc.

When I was developing the Price Guide to build fantasy values, I obviously wanted something that could be used by people outside of the Standard League. And requiring that flexibility ruled out using Standings Gain Points.

See, SGPs are tied to the final standings of a specific league. They are built based on a certain number of owners, a certain number of hitters, and a certain number of pitchers. The more you deviate from those specific settings, the less accurate SGP prices will be.

Consider Razzball‘s Point Shares, which are essentially a SGP system. A while back I drafted a league that had 6 teams using Point Shares and 6 teams using the Price Guide, tailored specifically to the league settings that Point Shares were based on. When I checked the final results, the Price Guide teams and the Point Shares teams split the points right down the middle. Out of 550 total points, each system got 275 — exactly half. In a league customized for a SGP system, SGPs and the Price Guide can do equally well.

However, if you change any single aspect of that league, the Price Guide will very likely take the top six spots. If you add a couple of new positions or add a couple of teams, the Price Guide values will adjust for it, and SGPs won’t. (This fact became very clear when I setup the Price Guide/Point Shares league, which wasn’t even competitive when I accidentally left out CI and MI.)

I imagine most people can live with SGPs inflexibility: After all, most people aren’t trying to build an online tool that works for any league, they just want a system that works for their league.

But what happens if your league decides to expand from 10 to 12 teams this year? What if they decide to use OBP instead of AVG?

If anything in your league changes from the year before, the accuracy of your SGPs is greatly compromised; but the Price Guide will adjust for whatever settings your league chooses.

SGPs Part II: The Danger of Past Results

No Comments
February 18th, 2009 by
Categories: Theory

I have mentioned that I think Standings Gain Points (SGPs) are a pretty good method of determining player values for fantasy. However, I don’t use them for the Price Guide based on some shortcomings I have found. This week I’m pointing out some of the quibbles that I have with the SGP methodology:

There’s a standard disclaimer in financial investments that “past results do not guarantee future returns.” Just because a stock has done well in the past, it doesn’t mean that it will continue to do well. It’s a principle that applies to baseball as well: A good hitter who is 0/10 against a pitcher might go four-for-four the next time they meet. And I think a big problem with SGP is expecting the next year to be just like the past one.

Since SGPs are based on the standings from previous years, they will be affected by past strategies. If two owners decided to punt saves last year, SGP will factor their save totals into this year’s denominators. If a few teams ran away with stolen bases, that will be included in the prices as well.

But remember, past results do not guarantee future returns. What happens if no one punts saves this year? What happens if stolen bases end up being a tight race, with no one pulling away with a huge lead?

Fantasy owners are dynamic: They are trying out new strategies from year to year. They are zigging if they saw people zag last year. You can’t rely on the same strategies being used from year to year, but that is exactly the assumption that SGP makes.

In his book, Art McGee does make some efforts to account for this problem. He suggests throwing out the top and bottom teams when building your SGP denominators, because these are more likely to be outliers. He recommends using multiple years of data if you have it.

Definitely, the more data you have to work with, the better your SGPs will be. But when I developed the Price Guide, I wanted a method that didn’t require years of historical, league-specific data to be effective.

And speaking of league-specifics, that’s actually my next quibble with the SGP method.