We’ve added two new data grids to our Fantasy Baseball Player Rater to help you identify streaking hitters/pitchers (streaking in the non-Ferrellian sense):
Hot Hitters: This has hitting stats for the past 20 days of all hitters with 1+ AB. Besides your typical 5×5 stats, it includes BABIP, OBP, OPS, SLG, and K%. Players are ranked in descending order of their ‘Heat Index’ which is calculated using a mix of Hits, Runs, HRs, RBI, SBs, and ABs. Each player is indexed against the 156th most valuable hitter for the period (156 hitters are active on a given day in a 12-team league). While it isn’t possible for us to know if he’s available or not in your league, we provide pre-season and in-season $ estimates (based on 12 team 5×5 ESPN rosters) – the higher those values, the more likely a player is already owned.
Hot Pitchers: This has pitching stats for the past 20 days of all pitchers with 0.3 IP. Besides your typical 5×5 stats, this includes FIP, Blown Saves, Holds, K/BB, K/9, and Quality Starts. Players are ranked in descending order of their ‘Heat Index’ which is calculated using a mix of Wins, Saves, Earned Runs, Hits, Walks, Innings, and Holds. Each pitcher is indexed against the 108th most valuable pitcher for the period (108 pitchers are active on a given day in a 12-team league). Pre-season and in-season $ estimates (based on 12 team 5×5 ESPN rosters) are provided for each player to help identify players more likely to be free agents in your league.
The inaugural #1 hot hitters/pitchers are Carlos Gonzalez (edging out Josh Hamilton) and Johnny Cueto (edging out CC Sabathia).
As with our other Player Raters, the grids are sortable and you can filter based on position (including SP vs. RP). The data should update every weekday by around 10AM EST – the last column will indicate the last day’s worth of games that are included.
If you see a player missing or set at the wrong position, please mention it in the comments section of the latest post. Please note that players just called up may take a week or so to be added.
With great pride and bland post titling, I’d like to announce a Beta release of our fantasy baseball in-season player rater as well as two charts that highlight the differences between pitcher FIP vs. ERA and batter BABIP vs. AVG.
The player rater work is an adaptation of the Point Shares methodology I’ve used the last couple of years for pre-season and post-season player estimates. Here is a link to a favorable test I did earlier this year vs. ESPN’s player rater methodology. After some trial and error plus assistance from a variety of folks (Eric K at my favorite fantasy baseball escort service – EliteFantasyPlayers.com - and Doug at Dougstats.com among others), we now have a fairly automated system for updating in-season player rankings on a daily basis.
ESPN Roster format (C/1B/2B/SS/3B/5 OF/CI/MI/UTIL/9 P) – 10 Team / 12 Team / 14 Team / 15 Team / 16 Team MLB
Yahoo! Roster format (C/1B/2B/SS/3B/3 OF/2 UTIL/2 SP/2 RP/4 P) – 10 Team / 12 Team / 14 Team / 15 Team / 16 Team MLB
AL-Only (2 C/1B/2B/SS/3B/5 OF/CI/MI/UTIL/9 P) – 10 Team / 12 Team
NL-Only (2 C/1B/2B/SS/3B/5 OF/CI/MI/UTIL/9 P) – 10 Team / 12 Team
The table is ranked based on a players’ projected Point Shares (a player’s value in standings points vs. the average player with some factoring in of position). Dollar estimates are provided both for in-season as well as comparisons vs. pre-season estimates. Take the dollar estimates with a grain of salt for now – they should become more stable as the season goes on. You can filter by position (P for all pitchers, -P for all hitters) and sort by any of the columns (1 click ascending, two clicks descending).
There are two pages focused on popular hitter/pitcher stats outside of 5×5 (popularity based on our pre-season poll results). These tables are filterable/sortable as well.
Hitting – OBP, SLG, OPS, Hits, Total Bases
Pitching – Quality Starts, Holds, Losses
Lastly, there are two tables that highlight differences between pitcher FIP vs. ERA and hitter BABIP vs AVG.
The pitcher table is sorted based on the ‘luckiest’ pitchers – i.e. pitchers ranked in descending order based on the difference between their FIP and their ERA. For those wondering why I chose FIP vs. xFIP, I do not have access to the league-average fly ball to home run ratio nor pitcher HR:FB ratio. You may also find that my FIP estimates are slightly off from other sources – this is mainly because I cannot currently separate out intentional from non-intentional walks but it can also be due to how the ‘constant’ is applied to bring the league average FIP in the 3.20 range.
The hitter table is sorted based on the ‘luckiest’ hitters - i.e. hitters ranked in descending order based on the difference between their current AVG and their expected AVG. A hitter’s expected AVG is calculated by applying a hitter’s 3-year BABIP to their in-season performance. 3-year BABIP was used as this stat does vary per hitter based on various factors (line drive rate, their speed, GB to FB ratio, etc.) but a hitter’s BABIP tends to be steady in the long run. Hitters with less than 100 AB in the previous 3 years are given the league average BABIP of .300.
I’ll do my best to keep these tables updated daily (generally by 10 AM EST). The last column of each chart reflects the last games included so it will be transparent when it has not been updated for a couple days. While I will do my best to keep on top of the moving pieces, please do not hesitate to provide the following information in the comments section of Grey and/or my posts:
Any missing players from the tables (for now, I’m including any hitter/pitcher with 1+ AB or 0.1+ IP. That minimum threshold will likely increase as the year goes on.
Any position eligibility changes based on 10 game in-season eligibility (I know Yahoo! is 5 games but prefer to make one change across both). For hitters where position eligibility seems imminent (e.g., Jesus Montero at catcher), I include the additional position and add an asterisk at the end of it.
Any wonky data or functionality
Other potential FAQ:
Will you ever have a ‘rest of season’ player rater?
Maybe. Would be dependent on a respected projection source providing an uploadable file that is 1) updated on a regular basis, 2) accounts for expected playing time, and 3) is free.
Will you create a dynamic player rater to reflect any conceivable league format?
Not planning on it.
Was your wife turned on by this accomplishment?
Nope. She prefers it when I go Don Draper and fix shit around the house in a white t-shirt.
As some of you know, we developed our own Player Rater methodology called Point Shares about a year ago. Since then, it’s been one big poontrain….zooming past Statgeek Station. Perhaps it’s because my hat and eyewear aren’t goofy enough?
Anyway, we’ve done some informal comparisons in the past w/ ESPN but – after having a prolonged, dorktastic debate – 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:
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…
Not sure how many of you knuckleheads explore this site, but in the top header under ’08 Rankings, which has the 2008 Fantasy Baseball Rankings, our Fantasy Baseball 10 Team Player Rater and our Fantasy Baseball 12 Team Player Rater. So now instead of downloading a clumsy Excel spreadsheet, you now have it all at your fingertips right onsite. Under ’08 Rankings, you also have the Best Fantasy Values for 10 team leagues and Best Fantasy Values for 12 team leagues. So what gives? Did Christmas/Chanukah/You Name It come early? You better believe it. No, the pleasure is all mine. No, mine. Mine! If you need an explanation on what the player raters are or how to use them, look here: Fantasy Baseball Player Rater — that will send you deeper into the player rater rabbit hole and you’ll come out a week later much wiser. The comments are off on this post. Scroll down to the next post to drop some praise on Rudy, this is all his doing. (Or scroll up if you’re finding this after today — the, um, day this was posted.)
Back in the pre-season, we launched a new player rater methodology called Point Shares to estimate fantasy baseball player value. There aren’t a lot of Player Raters to be found other than ESPN (Y! and CBSSports.com don’t have ones) but we feel ours is better because it factors in variables like a player’s position (e.g., Hanley Ramirez’s 33 HR is worth more than David Wright’s) and the point totals actually represent something.
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).
