Anyway, we’ve done some informal comparisons in the past w/ ESPN but – after having a prolonged, dorktastic debate on another blog – I decided to take it one step further.  I created a test where I pitted our Point Shares against two other player raters:  ESPN and RotoTimes.

The test went like this:  Create 10 random 10 team leagues and calculate the standings using the real stats.  Then do the same using the rating points for each of the services (so if you add up the ESPN HR player rater points for each team, the one with the most points gets a 10 in HR).  The team point totals calculated by the player raters is compared to the point totals from using the real stats and we added up all the differences (so if the real points total was 70 and the player rater projected 68, it’s worth 2 points).  The lower the point total the better.

Before we go into the results, it’s worth noting that this test puts our Point Shares at a disadvantage.  Why?  Our methodology factors in position and projected team standings so that you can use it to directly estimate the impact of a trade or draft pick.  We adjust our ratings by crediting points against the average found at the player’s position instead of the average hitter.  All stats equal, we know that a catcher will be much more valuable than a 1st baseman (why else would people draft Russ Martin and V-Mart in the 3rd round last year?).  Geovany Soto and Justin Morneau both hit 23 HRs.  While RotoTimes and ESPN ignore position and credit each with the same number of points, we have a 0.5 difference.  This is saying that – assuming you fill the rest of the rosters up with average players – owning Soto will give you a 0.5 advantage in HR points vs. owning Morneau in a 10-team league.

But a test where you just add up rosters takes this out of the equation.  You could conceivably be perfect just by creating a ‘rating point’ completely proportional to the real total.  So 20 vs. 30 HRs could be worth .2 and .3 points or 2 and 3 points, etc.  Will those numbers help determine the value of 20 vs. 30 HRs?  Not really.

Okay, with that said, the results of the test are as follows (if you want to see the spreadsheet, click here – warning: it’s messy).  Out of 100 teams, the total points off by the Player Raters was:

RotoTimes – 112
Razzball Point Shares – 143
ESPN – 152

Our Point Shares were the most accurate for 3 of the 10 leagues while RotoTimes claimed at least a share of 1st in the other 7 (ESPN tied them 3 times).

At a category level, I performed correlation tests between the ‘real’ standings and those of the player raters.  100% would be perfect.

As you can see, Point Shares held up pretty well to ESPN and RotoTimes despite taking on the extra burden of factoring in position and tying it to expected point gains/losses in the standings.  The test did shine light on some improvements we can make on pitcher counting stats (W, SV, K) – note the higher correlation we have on ERA/WHIP because we can directly tie it to IP.

Final summary:

1) RotoTimes is the most accurate of the three.  Combined with the facts that you can both customize the rankings based on league size, categories, roster size, etc. and they provide $ estimates, we’d say this is the best pure ranking tool.

2) Point Shares have proven to be in the same league as these other player raters.  Given the extra utility of Point Shares because it directly estimates the impact on team points of player moves, we’d say our Point Shares are the most useful of the three.

3) ESPN, while not the ‘testwide leader’, did pretty well – especially in hitting stats.  Their biggest pure weakness is ERA/WHIP as it would appear that they don’t factor in IP like Razzball (and, we assume, RotoTimes).  But we’d say their biggest total weakness is that their player points mean ABSOLUTELY NOTHING.  They are arbitrary numbers that could be used to rank players but not to estimate their value in the standings or worth at the draft table.  They do a good job, though, at keeping it updated throughout the year…

A ‘point share’ is the estimated impact on a team’s points by substituting a player for the average drafted player at his position on a team filled with average players.  So in a 10 team league, this team would otherwise earn 5.5 points per category (55 points).  Substituting Cliff Lee for Zack Greinke on an average roster would mean an average of 6.6 points (6.40 for Cliff Lee, -0.24 for Greinke).

Our 2008 Player Rater that is based on a 10 team MLB league with 5×5 scoring.  Only the top 50 are displayed below the post.

We will use this as the foundation for future articles but here are answers to some anticipated reactions:

1) How could pitchers be in the top 4 slots?

It might be surprising to see starting pitchers in the first 4 slots.  This isn’t a flaw in the ratings- it’s a flaw in your thinking (sorry).  The best pitchers in a season generally dominate 4 categories (W, K, ERA, WHIP).  While they don’t contribute in Saves, there is little opportunity cost to this since saves are concentrated in 30-40 players and there are 90 pitching roster spots.  For hitters, it’s rare for a player to be excellent across more than 3 categories and there’s a larger opportunity cost for the categories they are not great (i.e., OFs like Ichiro and Taveras hurt HR/RBI).  Only 6 hitters in 2008 ranked above average across all 5 categories – Pujols, Wright, Berkman, Holliday, A-Rod, and Braun.  Hanley Ramirez had a great year in Runs (125), HR (33), and SB (35) but was mildly valuable in AVG (.301 or .006 less than Ryan Theriot) and negative in RBI (67 or tied for 6th among SS).  Converting Roy Halladay’s stats to an OF (W=R, HR=SO, RBI=WHIP, SB=SV, AVG=ERA) would net 119/34/121/10/.335.  Sabathia, Lincecum, and Cliff Lee weren’t far off this.  The reason why it’s usually not advisable to draft a pitcher in the 1st round is the unpredictability of who’ll be the top pitchers (none of the top 4 were top 50 picks based on MockDraftCentral’s Average Draft Position) vs. their true value.  Here’s a more thorough explanation of a pitcher’s fantasy value.

2) Why are there are only 110 players that have positive value when there are 230 open roster spots?

In Point Shares, 0.0 represents an average player at their position.  So it is expected that about 1/2 the eligible players are above average, 1/2 are below.  A negative score doesn’t mean that a player isn’t worth having on your roster – it just means that he’s below average.  If the system was built with 0.0 representing a roster-worthy player, the points would then represent the value of a player on a team in last place.  This overestimates the value of a player when measuring the impact of a player swap (e.g., Lee for Greinke) for every instance except when a team actually did finish last.  The best approximation of player value is starting from the middle.

3) What is the highest/lowest score possible?

Theoretically, the best possible score should be 4.5 pts in each category (moving someone from 5.5 to 10) or 22.5 for a 10 team league.  Any other league size, just divide the team total by 2 and subtract 0.5 (12 team = 5.5).  A simpler way of looking at it would be to consider how one would calculate the average value per team of a player with 50 SBs.  For the team that’s 1st in SBs, his value is 0.  For the 2nd team, it could be worth +1.  Take this to its logical conclusion and you get (0+1+2+3+4+5+6+7+8+9)/10.  That’s 45/10 = 4.5.

While no hitting scores fall above 4.5 or below 4.5 (closest is Willy Taveras’s 4.3 in SB), the Point Shares system is just a model so it is conceivable that an extraordinary performance would net more than 4.5.  The only cases in 2008 were extraordinary bad ERAs and WHIPs.   (You’d think K-Rod’s 62 SV but that only netted +3.9).

Assuming you have a completely average team (55 points in a 5×5 10 team league), each player’s point shares reflect how many points they would add/subtract from your team’s totals if they replaced the average stat projections at that position. For example, if you swapped out an average team’s 1B (Mark Teixeira, David Ortiz) with Lance Berkman, they would increase from 55 points to an estimated 67.5 points. Point Shares also allow for basic trade comparisons (add the points of each side) and assessing your team vs. others (just add up the points and add to 55).

Seeing that we’re 2 months into the season, we thought it was a good time to update our Point Shares rankings – in this case, it is based solely on actual stats through June 8, 2008. So this is more comparable to the ESPN Player Rater vs. ESPN’s player rankings or Yahoo’s Big Board. Except better. (Not saying there aren’t flaws in ours but, c’mon, Ichiro is #17 among all players with a .290/43/3/17/26? At OF?)

June 8th – Point Shares for 5×5 10 team league and for Fantasy Razzball (play for worst team)

(Click on images to enlarge)

Pre-Season – Projected Point Shares for 5×5 10 team and 12 team leagues

Pre-Season – Projected Fantasy Razzball Point Shares

Below are the links to these posts. Interesting reading if you’re a fantasy baseball or stat junkie. Much less interesting than smack if you are just a junkie.

Part 1: How Valid Is The ESPN Player Rater?

Part 2: Are Fantasy Baseball Pitchers Correctly Valued By Player Raters?

Part 3: How Do You Value Fantasy Baseball Hitters?

The whole journey to prove/disprove the ESPN Player Rater eventually led me to the Point Shares concept that is the foundation of my 2008 drafting and player valuation.

Anyway, I checked in on the ESPN Player Rater in 2008 and it looks like they listened to good ol’ Rudy. Some of the improvement I’m seeing:

• Negative values (particularly in AVG, ERA, WHIP) – Where 2007’s version would have a floor at 0, the current rater penalizes very bad performance. CC Sabathia currently sports -3.31 points in ERA and -2.64 in WHIP.
• No arbitrary cap at 5 points per category – I’m seeing some category leaders at 3 and Michael Bourn at a 7.64 for SB.

It’s too early to do a full assessment of the methodology. I figure I’ll do a Point Shares update at the All-Star Break and compare it then. But given the shit I gave ESPN during the offseason, it’s only fair that I give them credit for coming to their senses (and listening to me).

Has anyone in Razzball Nation been using ESPN for their fantasy league? If so, post your feedback! Grey and I went cold turkey on ESPN FLB after last year’s debacle (first two weeks of stats were fried – I had to calculate the data offline and make year-end adjustments). But I thought their new platform was pretty good. Interesting to hear what the rest of y’all think.

Oh, and just in case the worldwide leader is listening, add smart people to Baseball Tonight. Replace Eric ‘The Emmitt Smith of ESPN Baseball” Young and John Kruk with guys from ESPN.com like Keith Law and Rob Neyer. If you must pander to the masses, go with some tail like Erin Andrews.

Also, do you have the replacement level averages you used for the point shares handy?

Rudy’s Response:
Regarding Dunn, here are the baseline projections for us and Baseball HQ:

Razzball: 513 AB / 100 R / 38 HR / 100 RBI / 7 SB / .256
Baseball HQ: 553 AB / 105 R / 41 HR / 104 RBI / 7 SB / .251

Can’t say that I’m familiar w/ Baseball HQ’s Player Rater (have the book and access to online projections) but I’m looking in the book and Dunn is drafted 62nd overall in their 15 team mixed league snake draft and tied for about 52nd place overall in projected dollar value at $24. Our Point Shares project him at #40. Blogmate Grey ranks Dunn at #33 in his top 100.

I think if you took Baseball HQ’s ranks and put them next to ours, you would find more dramatic differences than this. I see them having Pierre in the top 30 where he barely cracks our top 100 b/c we dock him for his crap HR/RBI (on a side note, I ended up with Dunn and Pierre in my expert league).

Here is one thought for the differences and a reason that compelled me to do Point Shares. Sites like Baseball HQ and BP tend to be snobs on fantasy league structures. They prefer single league auctions or – in the case of Baseball HQ’s simulated snake draft – a 15 team league (which I’ve never seen). I think the majority of players are in 10 or 12 team mixed leagues so the rankings have to be filtered through the scarcity/needs of that universe.

I think 10-12 team mixed leagues aren’t as starved for speed and middle infielders as the leagues that a Baseball HQ projects for. Pierre went in the 9th round of my 12 team expert league and no one was patting me on the back for great value (including myself).

Let’s dig into Dunn a bit more. While no one loves Dunn, look at where his projections rank him in his position:
1) Projected at #1 for OF HR (38)
2) Projected at #3 for OF Runs (100)
3) Projected at #4 for OF RBI (100)

Compared to the other power positions (1B/3B), the average OF has lesser power numbers: 78/20/77 vs. 1B’s 85/28/95 and 3B’s 85/25/90. So our point shares system likes Dunn a lot for those three categories. It would value him less if he was a 1B/3B, more if he played 2B/SS/C.

Now if he hit .300, I think he’d go in the 2nd round. He’s projected to hit in the .250 – .260 range. Not good since we’ve got the average 12 team BA at .282. His walks help because he’s slated only for 500-550 AB vs. 600-650 AB. The Point Shares takes all this into account and basically says that his crappy average neutralizes his Runs or RBI advantage (BA is -1.5, RBI is +1.5). So an OF hitting .260 with 100 RBIs and an OF hitting .282 with 77 RBIs are worth the same points on an average team (note: for comparison’s sake, universally loved OFs like Granderson and Sizemore are set to hit about 77 RBIs and only hit .275. their RBI + AVG point shares equal 0 and -0.4 respectively)

So Dunn’s remaining two category advantage and not awful 7 SBs still give him overall positive value. I’d take the Point Shares rank at face value and say he’s worthy of a 4th round pick in a 10 team or 12 team league – particularly if a team drafted speed or a pitcher in the first three and needs to compensate on power. His batting average is a drag but it’s an overrated drag. Yes, a switch to Ichiro would give you an estimated swing of 3.6 points in AVG but you’d also lose 3 points in RBI and 4.2 points in HR (surprisingly, SBs don’t make up this dramatic difference…hence, Ichiro barely makes the top 100 in player rater and is our consensus worst 2nd round pick).

Not sure if this fully answered your question but hope it shed more light on why Dunn does well on Point Shares and why he might end up on more than one of my teams.

Regarding replacement value, I decided to stop using them with our 2008 Player Rater and stick to position averages (making average player stat = 0 vs. replacement player stat = 0). My reasoning is that replacement player stats regress to a similar mean, exacerbated by disproportionate slotting of 1B/3B/OF in the UTIL slot. So the replacement player at every position looks about the same. I think this is misleading as a 1B/3B/OF with that average stat line hurts your team vs. competition more than a 2B/SS/C. By using average, it gives you a better indication that Figgins KILLS a team at 3B (think of the HR/RBI difference vs. teams w/ A-Rod, Wright, Braun, Cabrera, A-Ram, and Atkins) but is pretty valuable as a 2B.

The blogs set to participate are:
Razzball.com (Rudy Gamble)
Razzball.com (Grey Albright)
RotoProfessor.com
Greener on the Other Side
Mop Up Duty
Herb Urban
Cards in the Attic
Lou Poulas (Fantasy Insider Online, Sweet Lou’s Baseball Lab, Razzball.com)

We need two more participants so if you’re interested in joining, please e-mail us at info@razzball.com. Draft day is scheduled for Saturday, March 22nd at 4PM EST.

Check out these links for the rules and a review of the least valuable – or as we like to say the most invaluable – players in 2007.

The biggest thrill and challenge is the absence of established strategies and expert rankings. A-Rod is almost a universal #1 in standard games – who will be #1 in our “Nick Punto is Ford Tough” Razzball league? I have no idea though I would’ve guessed league poster child Nick Punto if he was assured of playing time.

To create somewhat of a level playing field, I’ve created a 2008 Fantasy Razzball Player Rater based on Baseball Prospectus and Baseball HQ projections. I adopted our Point Shares methodology that we used for projected rankings of standard fantasy baseball. I used Baseball Prospectus’s depth chart to make sure only projected starters or key backups were included in the rankings for position players and starting pitchers.

This Player Rater should help all the participants set up their draft rankings and, for those of you not playing, should prove to be somewhat amusing….

While peers suggest I try other high-quality (and free) projections like CHONE, ZiPs, etc., I’ve put projection experimenting on hold to tackle a greater quest – one that could benefit our site’s loyal readers and the fortunate souls who get redirected here by a search engine.

The challenge is answering the question “How do you convert player projections into rankings?”  As once you’ve settled on your projections, there are several key pre-draft considerations that need to take place to ensure success:

1. Value of Player Based on Position Depth – e.g, how much does a player’s value increase/decrease based on the other available options for that position?
2. Value of Players in Different Positions – e.g., how much do you sacrifice on a player’s total stats because they play 2B vs. 1B
3. Value of a Player’s Stat Mix – e.g., how do you compare the value of 40/120/10 (HR/RBI/SB) vs. 15/75/40?
4. Value of Hitter vs Pitcher Stats – e.g., how do you compare A-Rod vs. Santana?
5. Value of a Player By You vs. Others – e.g., how long can you wait before picking a player?

(Note:  Risk and health are other key considerations but they ideally should be factored into the projections – i.e., Rich Harden shouldn’t be projected at 200 IP)

While a solution for the above factors appears complex, the concept behind how to do it is rather simple:  Convert all the statistics to the same metric (think money – it’s real easy to compare 10 dollars vs 15 Euro vs. 2000 Yen if you convert the Euro and Yen to dollars).  This is the underlying concept behind Bill James’ Win Shares.

So what metric makes the most sense for fantasy baseball?  Where real baseball success is measured in Wins, fantasy baseball success is measured in points.

Hence, “Point Shares”

Please click for our inaugural edition of Fantasy Baseball Point Shares for 2008.  I’m going to refrain from a drawn-out explanation of the methodology.  The important parts to understand are:

1. Point shares represent the estimated impact on a team’s points by substituting a player for the average drafted player at his position on a team filled with average players.  So in a 10 team league, this team would otherwise earn 5.5 points per category (55 points).  Substituting one of those average pitchers (approx. Ian Snell) for Johan Santana would net an approximated gain of 7.8 points to 62.8.
2. To account for a hitter’s value outside their position (The utility spot, the fact that a SS HR is worth the same as an OF HR), hitters receive 2/3 of points value based on their stats vs. the average drafted player in their position and 1/3 of points value based on the average drafted hitter.
3. Since pitching positions can be filled with starters or relievers, player value was adjusted.  Starting pitcher values are 75% based on average drafted starting pitcher, 25% on average drafted pitcher.  Relievers are 40% on average drafted reliever, 60% on average drafted pitcher.
4. Hitters are placed at their most valuable position where they are 20 games eligible.  Their rank/value at other positions they are eligible (down through expected eligibility like Ryan Braun in OF) is listed lower down in the spreadsheet.
5. Two versions are included:  a 10 team, 5×5, MLB universe, C/1B/2B/SS/3B/CI/MI/5 OF/Util/9P and a 12 team, 5×5, MLB Universe with 2C/1B/2B/SS/3B/CI/MI/5 OF/Util/9P.

As with any player ratings system – especially one this ambitious – the standard question would be “How do you test this?”.  The beauty of this methodology is it was relatively easy to test.  I took 7 drafts off of Mock Draft Central and calculated the rankings based on the underlying projections (weighted model of PECOTA and Shandler) and the Point Shares.

After making a few adjustments, the results of the test were very promising – Point Shares predicted total team points within +/- 2 point for 45 of the 70 teams.  Another 18 were predicted within +/- 5 points.  Only 1 team fell outside of +/- 7 points.

On a category-by-category basis, the Point Shares correlate well with the total team stats.  For the hitting stats, the team Point Shares correlated at 97+% with the total stats.  For pitchers, Saves, ERA, and WHIP correlated at 90+% while Wins and Strikeouts were at 90% aside from one league where the projections tanked.  Why did the pitching stats not do as well as the hitting stats?  It is because of the random mix of starters and relievers who – unlike hitters – have vastly different counting stats.   ERA and WHIP proved most successful because they could be weighted by innings pitched.

Look out for future posts referencing these Point Shares and probably make some tweaks along the way – especially if we get revised player projections.

We also want to state clearly that this is NOT a recommended draft ordering.  The main reason is that it doesn’t factor in the 5th pre-draft consideration mentioned earlier – the “Value of a Player By You vs. Others”.  Yes, I believe Peavy is worthy of a top 5 pick but if you can get him in the 2nd round or possibly the 3rd round, by all means wait.  Average Draft Position stats are the one piece of valuable information you can get from Yahoo!, ESPN, etc.  If you’re playing in an advanced league, you may want to use those on Mock Draft Central (requires subscription).

Also note that some of the differences aren’t statistically relevant.  If you like Jose Reyes at 3.65 over Ryan Howard at 3.72, go with your gut b/c it’s a virtual pick’em anyway.

So use this as your rankings base then make adjustments based on your preferences and your feel for your fellow drafters.  And good luck…

So what makes a player truly invaluable in Razzball? All it takes are two simple things – opportunity and poor performance. The challenge is finding those magical players who both underperform vs. their baseball brethren and keep their role for a significant percent of the season.

The Razzball 6×6 format aims to reflect this opportunity/underperformance balance. Common hitting stats R/HR/RBI/AVG where (like golf) your goal is to score lower than your opponents are complemented by ABs (an opportunity measure) and K’s (a measure that credits both opportunity and underperformance). To ensure incompetence is rewarded instead of inactivity, teams with less than 5200 team ABs (400 per roster spot) receive All-Star prorated stats for those missing ABs.

Common pitching stats K/ERA/WHIP reward pitchers who can’t miss bats and are complemented by Losses (the inversion of Wins), Innings Pitched (a measure of opportunity) and HRs allowed (like the hitter’s K, the ultimate measure of a failed AB). Gone for the purposes of the game are the niche stats – SBs and SVs – as it’s too easy not to compile them and their inversions (CS and Blown SV) do not happen frequently enough.

Here is a brief explanation behind our Razzball Player Rater methodology. If you have any questions, please post on the board:

We carried over our regular Player Rater methodology which credits players for their performance vs. the Best Available Option (BAO) – i.e., the best option on the free agent wire in a 10 team, MLB league. Points are awarded based on the difference between the player’s stats and that of the BAO for each category. These increments for Razzball were created using some fancy math and some less fancy trial and error. Definitions for each category are in the attached player rater.

Half a player’s stats are based on the BAO for their position and half for the BAO hitter/pitcher. This factors in position scarcity without overvaluing as, at the end of the day, a HR is a HR no matter who hit it on your team.

The hitter BAO stats for Razzball are remarkably similar to those we had for regular FLB. It’s as if the BAO serves as the top of a bell curve and Razzball and FLB draft on either side of it (with the exception of no-hit/good speed guys like Juan Pierre who are equally valuable in both formats albeit for different reasons). Note the Razzball BAOs factor in that slightly weaker hitting positions like C, 2B, and SS will dominate the UTIL category where 1B/OF usually do in FLB.

The pitcher BAO stats for Razzball are higher in ERA/WHIP but, otherwise, not that far off from FLB BAOs.

A last note is that if a player’s stats exceed the BAO’s in a category, the player receives negative points. Some Player Raters, like ESPN, have a floor of zero. Not in ours. So a guy like Mike Cameron will gain points in average and K’s but will give back those points in HRs and RBIs.

So without further ado, let’s look at the top 20 most invaluable Razzballers of 2007:

1. Nick Punto – 3B/SS – Minn
2. Scott Olsen – SP – Fla
3. Livan Hernandez – SP – Ariz
4. Woody Williams – SP – Hou
5. Casey Fossum – SP – TB
6. Adam Eaton – SP – Phi
7. Nook Logan – OF – Was
8. Mike Maroth – SP – Stl
9. Dontrelle Willis – SP – Fla
10. Jerry Owens – OF – CWS
11. Felipe Lopez – 2B/SS – Was
12. Jose Contreras – SP – CWS
13. Daniel Cabrera – SP – Bal
14. Marcus Giles – 2B – SD
15. Trot Nixon – OF – Cle
16. Jeff Weaver – SP – Sea
17. Alfredo Amezaga – OF/SS – Fla
18. Kyle Davies – SP – KC
19. Dave Roberts – OF – SF
20. Nelson Cruz – OF – Tex

Similar to our standard 5×5 Player Rater, pitchers dominate at the top. Seven of the first 10 and 11 of the top 20 are pitchers. The reason behind this is also similar to our regular Player Rater – when pitchers are good or bad, they tend to be good or bad across the board. Scott Olsen’s 5.81 ERA and 1.77 WHIP over 176.2 poorly pitched IP couldn’t have happened without a higher HR rate (29), a healthy number of losses (15) and a strikeout rate that’s only a hair above average (133 Ks). Only Ron Shandler’s $19 folly Nick Punto was able to put together a hitting season that consistently invaluable.

Let’s analyze pitchers and hitters separately to better understand invaluable performance:

Pitchers
Like in the best books/movies, the pitchers who resonate in Razzball are rarely one-dimensional villains. They aren’t purely bad – there’s always something about them that holds out promise of rehabilitation. Is it that they are young and have good arms (Scott Olsen, Adam Eaton, Daniel Cabrera, Kyle Davies)? Is it that they were once all star caliber pitchers (Livan Hernandez, Dontrelle Willis, Jose Contreras, Jeff Weaver)? Maybe they seem solidly mediocre like Mike Maroth? Whatever that promise may be, it serves the purpose of instilling faith in their manager to keep handing them the ball every 5 days.

The most common aspect across these pitchers is a tragic inability to keep baserunners off the base paths and touching home plate. The average ERA and WHIP among these 11 pitchers is a 5.82 ERA and a 1.61 ERA over about 160 IP.

Losses are an interesting stat to analyze. While 36 pitchers had 14+ wins in 2007, only 17 had 14+ losses. These top 11 Razzball pitchers represent 7 of them but they also have some pitchers with downright mediocre Loss totals. Let’s look at two factors that seem to play a role on a pitcher’s loss totals:

1) Their Team – The better their team, the more they get bailed out.
2) Their Home Park – The more hitter-friendly the park, the more likely they get bailed out (and the less egregious their pitching truly is)

Adam Eaton and Livan Hernandez are examples of good team / good hitting park. These two somehow managed to sport .500 records (10-10 and 11-11, respectively) with WHIPs at 1.60 or better. Eaton owes Rollins/Utley/Howard some cheese steaks. Livan’s 2007 season puts the defect in defector.

Mike Maroth had a good team (Tigers) / average park for most of his 20 starts and 7 relief appearances which could explain how he went 5-7 while sporting a ghastly 6.89 ERA/1.88 WHIP. The Cardinal trifecta of Mike Maroth, Kip Wells (17 Losses, 5.70/1.63) and Anthony Reyes (2-14, 6.04 ERA) proved once and for all that if there’s an honorary Razzball manager, it’s Tony Larussa (also see the 721 total ABs gifted to Aaron Miles and So Taguchi which netted 5 HRs).

Dontrelle Willis and Scott Olsen had bad teams / bad hitting parks and managed identical 10-15 records in 35 and 33 starts, respectively, showing racial equality exists when it comes to left-handed Marlin pitchers.

Woody Williams, Jose Contreras, and Daniel Cabrera had bad teams / good hitting parks and stacked up some awful W-L records: 8-15, 10-17, 9-18.

Based on this sample, I’d say finding a bad pitcher on a bad team is the most important thing for Losses. Home park might play a role for their ERA and WHIP but probably not a big factor for Losses.

HRs allowed, on the other hand, definitely skews on home park. Of this cheap baker’s dozen, the trio that topped 30 HRs allowed all played in the hitter parks (W. Williams, L. Hernandez, A. Eaton). Jose Contreras’s 21 HRs was the exception – a gift to the small-ball loving Ozzie Guillen.

Strikeouts and IP don’t have much in terms of interesting stories. Daniel Cabrera is probably the only plus-K guy in the group and he more than makes up for it by walking so many hitters. Throwing 175+ IP isn’t the only way to near the top of the Razzball Player Rater for a pitcher but it helps. Tampa Bay’s Casey Fossum – the one-time Red Sox ‘prospect’ – had a bucket list kind of year, cramming all sorts of experiences within his 76 innings that led to an eye-popping 7.70 ERA and 1.79 ERA.

Stepping away from the top 20, the lessons we see in the Player Rater when it comes to pitchers are going to sound like bizarro FLB advice:

1) Look for starters with bad WHIP, average to bad K rates, and, preferably, bad teams.
2) Look for some positive story that assures them some role security – whether it be they once were good, they have ‘potential’, they are ‘workhorses’, they are the best a team has, etc. No use picking a stinker who gets demoted after 3 bad starts.
3) For relievers, you really want to stick to pitchers on bad teams. This provides a boon to both Losses and, potentially, innings pitched. Amazing that the 6 most invaluable relievers pitched for either Tampa Bay or Baltimore. Generally avoid closers – even the bad ones – as they don’t pitch as many innings.

The net-net on pitchers – predicting a bad pitcher is even harder than predicting a good pitcher. Draft conservatively and keep an eye on the FA wire for the next worst thing.

Hitters
What makes a good Razzball hitter? If you had to boil it down to one thing it would be this: little power. Besides minimizing HRs, low power guys are kept out of the meat of the lineup which reduces R and RBI opportunities (leadoff hitters would be less Run challenged) Of the 7 hitters to make the top 20, only Felipe Lopez made an honest run at double digit HRs (9).

The value of low power guys’ minimal R/HR/RBI per AB goes beyond their stats alone. With a team minimum of 5200 AB, the more AB you receive from low power guys, the less you need to invest in guys with medium/high power. Despite hitting for a measly .245, Felipe Lopez’s greatest value was his 603 AB that could allow you to carry a platooning 300 AB 1B and OF and still average 400 AB per hitter.

But a team can’t be built on little power guys alone as they tend to hit for higher averages, are less likely to strike out, and may be AB-challenged b/c of benching or platooning. In fact, only 9 players were able to hit the pick-six – being worse than the BAO in all six hitting categories (first number is their total player rater rank):

1. Nick Punto – 3B/SS – Min
14. Marcus Giles – 2B – SD
21. Tony F. Pena – SS – KC
24. Josh Barfield – 2B – Cle
30. Craig Biggio – 2B – Hou
44. Bill Hall – OF/SS – Mil
48. Lyle Overbay – 1B – Tor
51. Gerald Laird – C – Tex
66. Tadahito Iguchi – Phi

Strikeouts are a particularly vexing category as the top K guys often have a lot of power. Brandon Inge was the only player in the top 10 in K’s who didn’t have 20 HRs. Outfielders like Jason Bay, Chris B. Young, Mike Cameron, and Jack Cust are invaluable Razzball players as their power is compensated by high K’s, generally low average, and above average ABs.

An interesting twist to Razzball is that multi-position players are more invaluable for their more offensive-minded position. Nick Punto on the hot corner beats Nick Punto at MI. Guys like Rich Aurilia warrant a look at 1B. Alfredo Amezaga is a find at OF (forget the SS eligibility). Darin Erstad is an embarrassment of riches with 1B and OF eligibility (luckily, Erstad’s valuable team spirit and punting skills don’t factor into Razzball.)

So here are some Razzball lessons we see in the Player Rater:

1) Invaluable Razzball hitters are more predictable than pitchers. Concentrate on hitters during the early parts of the draft.

2) Find high AB, low power guys – no matter what the position.

3) Avoid starters at key power positions like 1B, 3B, or 5th OF in favor of platoon players or multi-position eligibility players.

4) Consider job security/opportunity. Nook Logan is a Razzball god but how many ABs will he get?

5) Try to find positive K guys with somewhat minimized power potential – i.e., a power hitter in San Diego. At the very least, hopefully they contribute low AVG and ABs. It may pay to draft a R/HR/RBI killer like Adam Dunn or Dan Uggla and save them for bad pitching matchups or bad hitter parks – say when they go on an NL West road trip to SF, LAD, and SD.

6) Gamble on the young ones – top rookies in 2007 include Alex Gordon, Tony Pena, and Stephen Drew. Look at minor league K rate as Gordon and Drew were particularly invaluable in this category. Figure their average will be hurt because of their greenness. Even partial successes like Delmon Young are worth it – his 65/13/93/.288 earned him a #67 on the player rater because of the 127 Ks and 645 ABs.

If you’re interested in joining the inaugural Razzball league, please send an e-mail to info[at]razzball.com. Special preference to fellow bloggers.

In two previous articles (part 1 and part 2), we’ve laid out alternative views for judging the most valuable player in 2007 5×5 MLB fantasy baseball (we say Peavy) and for pitchers – using and abusing the ESPN Player Rater in the process.

In this article, we’re going to focus on valuing hitters. The questions we will tackle are:

1) What is the value of each hitting stat?
2) How does position depth/scarcity affect a player’s overall value?
3) How does our approach to hitter value compare against the ESPN Player Rater?

To download our player rankings for 2007, please click our 2007 Fantasy Baseball Player Rater. To view the ESPN Player Rater.

What is the value of each hitting stat?

Our approach towards valuing player stats is to look at two factors: 1) the difference between a player’s statistics and those provided by the best available option (BAO) on the free agent wire (which would take position depth/scarcity into account) and 2) the impact that stat difference might have on a league’s standings (ambivalent to position).

We’ll set position scarcity aside for a second to look at the composite stats for the BAO hitter in 2007: 67 Runs / 14 HR / 65 RBI / 6 SBs / .277. The closest player equivalent to these stats is Luis Gonzalez.

We used the final standings of our fantasy league to understand the impact of each statistic by looking at the standard deviations between teams’ totals. While it would be better if we had more league standings on which to base these standard deviations, we still feel this is superior to building ratios off team averages because it takes into account that some statistics have larger percentage gaps between teams vs. others. This is most evident when looking at HR vs. SB – while the average team in our league average 1.69 HRs to 1 SB and the BAO has a HR:SB ratio of 2.33:1, the observed impact on a team was actually 1:0.77 or that a HR has more value (not even counting the R/HR/RBI/AVG implications) to a team’s rank in the standings than an SB.

The ratio for these stats based on our analysis was: 3.3 Runs / 1 HR / 2.8 RBI / 1.3 SBs / .003 AVG. Points are credited based on these ratios (a point actually equals the above ratio * 4.6) after subtracting the BAO’s stats.

Okay, let’s do two comparisons to show this works in action.

Eric Byrnes (103 / 21 / 83 / 50 / .286) vs. Miguel Cabrera ( 91 / 34 / 119 / 2 / .320)

This is an interesting one as it asks that inevitable question – how much are SBs really worth? Is it worth the addition 48 SBs to sacrifice those HRs, RBIs, and AVG that Miguel Cabrera provides? Let’s look at the points comparison of R/HR/RBI/AVG:

Runs: Byrnes 2.4 to 1.5
HRs: Cabrera 3.95 to 1.55
RBIs: Cabrera 3.95 to 1.43
AVG: Cabrera 3.48 to 1.01

(Note: While it might not look right that Cabrera’s 34 HRs could be worth 2.5x that of Eric Byrnes 21 HRs, remember that the BAO provides 14 HRs. So this is really a comparison of 20 HRs (34-14) vs. 7 HRs.)

Counting just these stats, Cabrera is about twice as valuable as Eric Byrnes (12.89 to 6.39).

But Eric Byrnes’ 50 SBs is huge given the average team only had 162 SBs in our league. A total like this could let you dominate SBs or focus on non-speed guys when filling out other positions (say, taking Khalil Greene’s 27 HRs instead of J. Lugo’s 33 SBs).

Eric Byrnes’ 50 SBs equates to 7.25 points in our scale while Cabrera’s 2 SBs equate to negative 0.45 points because it’s less than the BAO would’ve provided (which is 6). So factoring in SBs, Eric Byrnes is the more valuable fantasy hitter (13.6 to 12.4). But if your team was set for SBs, trading Eric Byrnes for Miguel Cabrera would be a no-brainer.

Placido Polanco (105 / 9 / 67 / 7 / .341) vs. Dan Uggla (113 / 31 / 88 / 2 / .245)

This comparison focuses on Polanco’s AVG contribution vs. Uggla’s power contribution.

Runs: Uggla 2.65 to 2.12
HRs: Uggla 4.0 to -0.78
RBIs: Uggla 1.94 to 0.30
SBs: Polanco -0.05 to -0.86

(Note: These comparisons do factor in position scarcity – hence, Uggla’s 2 SBs receive more negative credit that M. Cabrera’s above since the 2B BAO steals more than the average player.)

Counting these stats, Uggla is well ahead at 7.73 to 1.59 points, with the biggest driver being his 31 HRs which are worth 4.78 points more than Polanco’s 9 HRs.

But those HRs come at a price. Uggla’s .245 average is well below the BAO average of .277 (actually 2B’s have higher AVG than other positions so it’s even worse – examples of high batting average marginal 2Bs include Orlando Hudson’s .294, Luis Castillo’s .301, and Ronnie Belliard’s .290). Combining that bad average with his above average AB total (632), Uggla’s average would drop the average team’s AVG by .004 vs. the BAO 2B. This earns him a negative 3.28.

On the other hand, Polanco’s .341 in 587 ABs is worth a positive 4.77 points – more, in fact, than Uggla’s 31 HRs. He’s worth about an extra .004 on your team average meaning that swapping these two creates a .008 swing, a more dramatic swing than the 22 HR difference.

So while Placido Polanco is a negative on a team’s HR and SBs (and just about BAO level on RBIs), his high AVG catapults him into being a more valuable fantasy baseball contributor (6.4 to 4.4). If Uggla could just get to something like a .275 average or steal 20-30 SBs, his HR/RBIs could help catapult him up the 2B rankings (even with the anchor-like AVG, he ended up 7th most valuable 2B, well ahead of the .317 hitting ROY Dustin Pedroia).

How does position depth/scarcity affect a player’s overall value?

Position depth/scarcity plays a role from draft day through the end of the season.

During draft day, position depth/scarcity can increase/decrease a player’s value. A common practice is to ‘tier’ players at each position and try to group together similarly valued players. If there is only one player left in, say, the 2B tier and 5 similar valued players at SS, you may increase that 2B’s draft value because you can wait a round and likely get one of those shortstops.

After the draft, position depth/scarcity is used to compare the marginal benefit/loss of trading or adding/dropping one player over the next – e.g., I could trade Placido Polanco and replace him with little to no dropoff in any stat except AVG.

To factor this into our analysis, we extended our Best Available Option (BAO) concept to each position. We started with 10 rostered players for catchers and infield positions and 50 outfielders. We split the 1B/3B and 2B/SS positions equally and then divided up the utility position based on instinct and position depth (30% 1B, 2.5% 2B, 2.5% SS, 5% 3B, 0% C, 40% OF, 20% DH). We created composite stats for BAOs at each position – so for catcher, we took the 11th best AVG, 11th best HRs, etc. We then credited point totals based on the BAO at the position (“Position Points”) and averaged them with our average hitter BAO (“Player Points”). (Note: Since team rankings are position-agnostic – you don’t get more credit if it’s a middle infielder who hits a HR – there is a need to balance position depth/scarcity with overall stats. To keep it simple, we weighted it 50/50).

Below are the BAO stats per position (R / HR / RBI / SB / AVG) and some close statistical fits:

C – 47 / 13 / 57 / 2 / 0.273 (Paul Lo Duca, Johnny Estrada, AJ Pierzynski)
1B – 63 / 18 / 68 / 1 / 0.279 (Matt Stairs, Conor Jackson, Aubrey Huff)
2B – 79 / 11 / 61 / 9 / 0.288 (Orlando Hudson, Brendan Harris, Mark DeRosa)
SS – 72 / 11/ 60 / 11 / 0.279 (Brendan Harris, Jack Wilson)
3B – 70 / 18 / 72 / 4 / 0.279 (Kevin Kouzmanoff, Mark Reynolds, Aubrey Huff)
OF – 67 / 14 / 65 / 6 / 0.273 (Luis Gonzalez, Austin Kearns, JD Drew)

The most interesting about these BAO totals is how relatively close they are. The corner positions have a slight advantage in power and the middle infield spots have a slight advantage for runs, SBs and average. Catchers are weakest – particularly in Runs as catchers play less games and are disproportionately hitting 6th to 9th (less run opportunities).

Perhaps most surprisingly, the OF position looks no better than the middle infield positions. Wouldn’t you expect OF was a deeper position than middle infield? Isn’t BJ Upton more valuable as a 2B than an OF? Short answer: not really.

Here’s why: You’ve got roughly 15 2B, 15 SS, and somewhere between 52-57 outfielders on league rosters (OF are often used for UTIL positions). Looking at MLB rosters, you have roughly 30 starting 2B, 30 starting SS, and 90 starting OFs. FLB rosters, thus, are cutting deeper into the percentage of starting OFs vs. 2B/SS.

In addition, 2B/SS have added some pop over the years. 29 middle infielders hit at least 12 HRs. Granted, some had bad averages (Bill Hall, Juan Uribe, Stephen Drew), but the perception of those positions being power-challenged is outdated. (What IS true, though, is that it’s rare to find a middle infielder with 30+ HR power).

Outfielders, on the other hand, aren’t that deep. Only about 55 hit 15 or more home runs and that includes some players that might be at other positions (Berkman, Upton, Stairs) and the weakest ones look an awful lot like Luis Gonzalez and Austin Kearns (the BAO matches).

So while we did factor position depth/scarcity into our analysis, it really didn’t play a major role for hitters. The greatest impact was at catcher where the troika of great catchers in 2007 (Jorge Posada, V-Mart, Russell Martin) got about a 2 point boost because the Catcher position was the weakest in terms of BAO.

So Hanley Ramirez and Jimmy Rollins had extremely valuable fantasy years but the fact they played SS really didn’t add any significant value (maybe +2-3%).

How does our approach to hitter value compare against the ESPN Player Rater?

ESPN has a much simpler approach for estimating hitter value than the approach we have described above. It creates a cap at 5 points and a floor at 0 points. 5 points are awarded to the MLB leader in the stat and then each other player’s total is divided into the leader’s total and then multiplied by 5 to get their total – e.g., A-Rod led with 54 homers. David Wright had 30. He received 30/54 (.556) * 5 = 2.78 points in HR. Average is done in a slightly more complex way but the lowest possible total is zero (even if the player’s average has negative value).

From a macro-perspective, this simplistic approach works fine. The top hitters are going to appear near the top, the okay hitters in the middle, the bad hitters on the bottom. At a micro-perspective, we think ESPN’s simplistic approach has greater flaws vs. our approach. These flaws are less for hitters than pitchers, though, as the greater issues arise around ratio/average based stats and pitchers have two (ERA, WHIP) vs. one for hitters (AVG).

In a previous article, we identified four issues with ESPN Player Rater for valuing pitchers

1) Capping High Points at 5
2) Positive Ratio/Average Contributions Are Undercredited
3) Negative Contributions Aren’t Penalized
4) Overcrediting of Slightly Above Average Performance

These four issues all play a role for valuing hitters but #2 and #3 are not as major an issue because ERA/WHIP are more polarizing than AVG. For example, even low value hitters may hit .290 but only a great starting pitcher can manage an ERA near 3.00 ERA.

An additional issue we’ve found is:

5) The league leader used as the points base distorts the distribution of points – While the leader in Runs and RBIs is relatively close to the other leaders (no one had, say, 200 Runs or RBIs), A-Rod’s 54 HRs and Reye’s otherworldly 78 SBs set a very high bar for 5 points. This creates odd situations where Eric Byrnes 50 SBs (tied for 4th in majors) is worth less in ESPN Player Points than his 103 Runs (outside the top 20) and Jimmy Rollins’ 30 HRs (tied for 20th) are worth less than his 94 RBIs (tied for 42nd).

Here is the assessment on a stat by stat basis:

Runs – Overcredits for all players. For above average performance, Issue #4 plays a role (the Best Available Option’s 67 Runs warrants 2.3 points). For below average performance, Issue #3 starts taking effect (less than 67 runs should warrant negative points). An additional issue throughout is that runs are so plentiful across players that the value of a run is less than other stats (A-Rod’s 143 runs warrant 4.95 points in our estimation vs. 8.29 for his 54 HRs)

Home Runs – Undercredits great performance like A-Rod and Fielder (Issue #1). Issue #5 plays a role in underestimating the value of everyone at 25+ Homers. Players between about 15-24 HRs are slightly inflated based on Issue #4. Anyone below the BAO average of 14 are overestimated based on Issue #3.

RBIs – Undercredits the great performances like A-Rod and Matt Holliday (Issue #1). Overcredits above average performance (Issue #4). Undercredits below average performance (Issue #3). Issue #4 affects more hitters than Issue #3 (which is limited to speedsters and some 2B/SS – examples are Reyes’s 57 RBIs and Pierre’s 41RBIs)

SBs – This is the category where Issues #1 and #5 play a huge role in underestimating SB value. We have Jose Reyes’ 78 SBs at a whopping 11.5 points – the most points awarded for any offensive category. Teammate David Wright’s 34 SBs earned him a respectable 4.8 points (equivalent to Holliday’s 36 HRs and Vlad’s 125 RBIs). This underestimation affects hitter values all the way down to about 10 SBs. Issue #3 plays a very minor role – greatest for 2B/SS as speed is most common in that category (Freddy Sanchez’s 0 SBs earned him a negative 1.19).

AVG – Issue #1 only affects the top 3 hitters as Magglio, Ichiro, and Matt Holliday’s averages warranted 6+ points in our ratings. Issue #2 plays a role for the rest of those with averages above .330. Issue #4 plays a role in overestimating the value of hitters lower than .330 but greater than BAO (e.g., Luis Gonzalez’s pedestrian .278 warrants 1.99 ESPN points where it should be worth zero). For low average hitters, Issue #3 plays a role in greatly overestimating their value as they should have negative value. Uggla’s aforementioned average of .245 gets .86 ESPN points compared to our -3.28 points.

Amazingly, though, the cumulative effect of these issues seems to have little bearing on the ranking of hitters. We agree with the top 10 OFs from ESPN Player Rater with slightly different ordering. The top 10 2B match down to the order. The differences play more of a role in total player rankings – below are some examples of players differently valued (Our Ranking, ESPN Ranking).

Eric Byrnes (25, 43)
Jorge Posada (58, 92)
Juan Pierre (78, 117)
Derek Jeter (86, 106)

It’s worth noting that almost every hitter is higher valued in our rankings vs. ESPN because ESPN overvalues pitchers out of the top 20 and this pushes down all the hitters.

So while we find faults in ESPN’s methodology, we can’t fault using ESPN Player Rater to understand hitter position rankings. It works surprisingly well for hitters given its simplistic approach – it’s possible that its flaws are a bigger issue as you move down the player rankings. That said, we would caution against using the combined hitter and pitcher rankings given the flaws we’ve seen with their valuing and ranking of pitchers.