A trade sending Brian Roberts to the Cubs appears to me looming. At the rate this off-season is going I’d be surprised if it gets done quickly, though.
The deal floating around includes Sean Gallagher, Ronny Cedeno, and another player or two. If I’m the O’s I make try to make it 2 with one of them being Eric Patterson.
Patterson is a second baseman who doesn’t have a place to play now, or after a potential trade for Roberts. Tim Dierkes of MLBTradeRumors has some interesting things to say about him.
I look at it this way:
(1) We have Brian Roberts (who has a composite projection from fantasy411 of
.285/.366/.423) and Luis Hernandez (.247/.283/.304) or
(2) Eric Patterson (.265/.327/.405) and Ronny Cedeno (.270/.314/.397).
It’s an average of .266/.325/.364 for (1) and .268/.321/.401 for (2).
There is a drop-off in defense though, which is bothersome at the middle infield positions.
On the bright-side; the O’s would then have their 2B and SS set for the next 5-6 years. Both guys are getting better, whereas Brian Roberts is at the top of his game and Luis Hernandez is never going to offer much with the bat.
As long as the 4th prospect is half-way decent I think it’s a solid deal to make. While we’re at it, why not give Eric’s big brother Corey a little bit of money to come back and be a fourth outfielder? I would say that he’s better than Tike Redman, and if he has any success the O’s can trade him at the deadline to a team that needs a quality back-up for a play-off run.
I have also heard that Cleveland has had some interest, possibly offering Jhonny Peralta (and Adam Miller?). That would be something to think long and hard about, depending on the other guys coming over. At least it seems that MacPhail will have some options.
More on this if/when it happens.
Read more ...
Friday, February 29, 2008
Over/Under
This in response to the over/under betting lines for each team’s wins in the 2008 MLB season being announced. I think this may be the general set-up for this kind of thing: a short section for quick reference and a long section for expansion.
Short: (In order of confidence) SEA – Under, BAL – Over, (small gap) OAK – Over, STL – Under, (small gap) MIL – Over, DET – Under, PHI – Under, FLA – Over, LAA – Under.
Luck does play a huge role though.
I’d put the over/under on how long I keep up with this blog at about 2 months.
Long:
Predicted wins were determined as follows:
(1) Take the teams AB,OBP, and SLG from ’07, as well as ERA
(2) Make minor adjustments to OBP and SLG based on; player additions/subtractions, (un)lucky batting averages, new parks, aging, injury, etc. (it was off the top of my head – ex. CHC went from .333 / .422 to .338 / .421 since they added OBP with their new RF and C (and maybe 2B), but lost some power in center (made up a little by the added power at C)
(3) Similar adjustments made for ERA (ex. MIL went from 4.41 to 4.35 based on less bad luck for Bush/Capuano, more innings from Gallardo, and a slightly improved bullpen)
(4) Approximated Runs Scored via AB * OBP * SLG and then dampened it a touch as it tends to overestimate (about 2% over for 2007) and Runs Allowed via ERA (with a earned to unearned adjustment)
(5) Found MY expected record with the Pythagorean formula (win% ~= RS ^ 1.83 / ( RS ^ 1.83 + RA ^1.83))
(6) Used the Baseball Prospectus projections for next year (they’re pretty much the best at is) for the teams RS and RA
(7) Averaged my RS/RA with BP’s RS/RA and found the predicted wins that I list.
(8) BP actually runs simulated season for the projections they have for each player to come up with their projected standings. I generally agree with their W/L numbers but I’m higher on the O’s (they’ve been pessimistic on various O’s players before and turned out wrong – on Markakis especially) Braves, Rockies, Royals, Phillies, Padres and Mariners than they are, and lower on the White Sox, Marlins, Angels, Mets, and Rays. They correctly predicted the DBacks winning the NL West last year, as well as the White Sox collapse, which nobody else saw coming. I didn’t suggest betting in any situation in which we disagreed on the O/U expect Atlanta . They have them at 85 and I have them at 88, though it comes out to 88 via RS/RA averages.
As always, happy to give input on any team/player/etc.
Team O/U Pred. Wins Pick Comment
ARI 87.5 86 U I wouldn’t feel great about betting here as young talent has a larger variance. They outperformed their expected W/L record based on Runs Scored/Allowed last year by 11, so 87 wins would still be an 8 game improvement in talent. The top two SP should be great and if the Big Unit can come back strong they’ll have a great rotation. SP Micah Owings could probably bat in the middle of the Giants’ order.
ATL 85.5 88 O I like the Braves. I think Renteria’s good year was balanced out by Jones’ bad one and a full year from Teixeira plus small improvements from McCann and Francoeur make them better. Should have won 88 last year. Not a slam-dunk, but solid if you were leaning this way anyway. I don’t know how Smoltz is still doing it, but that guy has a wicked slider.
BAL 66 72 O It’s only this low because of the division. A quietly solid line-up (except for SS) with average OBP scores some runs. Pitching can’t be worse then last year, and there are enough arms to go with the ones that are succeeding. It would take some serious bad luck for the team to lose 100 games. I personally think 75 would be reasonable.
BOS 94.5 94 U I wouldn’t pick here. The main contributors on offense are getting up there in years, but they can still hit, and the pitching should be very good. Buccholz is pretty much as good as he showed in that no-hitter vs. the O’s. Jonathon Papelbon’s fastball is one of the best in baseball, to lefties as well as righties.
CHC 87.5 89 O I’m fairly confident in this one, as the Cubs have a good team. A trade for Roberts would pretty much seal it for me. Zambrano’s declining control is worrisome, but Rich Hill has a big-time curveball and Marmol has some of the best late-inning stuff in baseball. Soto should provide a major upgrade at catcher, and if Pie can add some offense to his defense the line-up will be very good. I just hope Sweet Lou keeps Ryan Theriot as a bench player. He’s turning into the new David Eckstein (more on that later).
CHW 77.5 75 U I really don’t like the White Sox. I think the pitching isn’t good, and the main offense (minus Swisher, who may hit 40 in that park) is getting older. Plus their manager is one of the worst in baseball (“Let’s play Owens over Quentin because Owens is fast and will hit as well as he did last year hopefully. Quentin will just get on base more and might actually play really well if we give him a chance – Let’s bunt a lot. It doesn’t matter that we only score with homeruns”). I wouldn’t bet on this though – if Thome, Konerko, and Dye each have the years they can then they’ll score a good number of runs.
CIN 78.5 77 U Speaking of bad managers – Dusty Baker… wow. (“I don’t want people getting on base (via walk / if they aren’t fast); then they just stand out there clogging up the bases for the next hitter.” Seriously. That’s pretty much in every interview he gives. If he hadn’t had Bonds on his team he would probably not have gotten another job after the Giants.) If Baker plays the young guys this team could challenge for the division. I don’t think he will, so I don’t think they’ll be that good. Wouldn’t bet on it, though. The Jay Bruce / Joey Votto hitting combination / comedy team should be fun to watch for the next 10-15 years.
CLE 90.5 90 U They weren’t as good as their record last year, and Hafner’s down year worries me. The walks were still there but the power was down (not just HR, doubles too) and he wasn’t injured. Still, I think they’re the best team in the division, they have one of the best front offices, and they have some pitchers ready to step in if need be (Carmona’s workload is worrisome). Could win 96 again. No bet.
COL 83.5 83 U Definitely no bet. They were as good as their record last year, but I have to think the pitching will regress a bit – especially with the younger guys getting a larger workload. If Holliday goes down then their offense just won’t be that scary anymore. It was nice to see Larry Walker admit the he isn’t a Hall of Famer. He isn’t, but he still has about as good of a case as Jim Rice.
DET 94.5 89 U They’re a good team. Very good even. But I still think they’re a step below the Indians. Getting Cabrera helps the offense, but not by as much as you’d think, as Granderson, Ordonez, and Polonco should all be downgraded a tad from last year. Pudge never walked before and is getting worse with age. Sheffield might be pretty close to done. The bullpen is kind of a mess, especially if Rodney goes down, and I’m not buying too much into the starting pitching behind Verlander and Bonderman. I don’t think they’re 7 games better than last year.
FLA 68.5 73 O They lost Cabrera and Willis, but the still have Hanley Ramirez, who was one of the best offensive players in baseball last year (led the NL in Value Over Replacement Player). They got a bit unlucky last year, and I don’t think the team is that much worse (at all, even). They’re in a similar situation as the O’s – lost quality hitter and pitcher, but extra depth and non-down years from players improves their record. Better pitching is the key. Not the safest bet, as they could collapse - especially if H-Ram’s shoulder affects him – but they’re not that bad.
HOU 74.5 73 U Not a good team. Offense is there with Berkman, Lee, Pence, and Tejada but there’s no pitching after Oswalt and maybe Wandy Rodriguez. Michael Bourn may steal 50 bases though. 75 wins wouldn’t be at all surprising so it’s a tough bet to make. Also, the park actually has slightly favored pitchers recently, not hitters.
KCR 72.5 72 U No bet. They definitely might be better than this. I like where the team is going (though signing Guillen for that much was a stretch). Billy Butler is a great hitter, Gordon should be better, and if the give Esteban German a chance he could produce. Plus, Brian Bannister is one of the smarter pitchers around and Zach Greinke has got some wicked stuff. 50 mph curve after a fastball at 97 is really unfair. Plus they were 5 games worse than they should have been last year.
LAA 92.5 89 U The outfield is a mess. They have 5 players for 3 spots, and no one wants to DH. If Escobar doesn’t pitch well after injury it will hurt, but they have some good starting pitching. John Lackey is very underrated. I like 89 wins better for 2009 than 2008 (major deals not withstanding) but it’s not a terrible bet. They won 4 games more than expected in ’07.
LAD 87 86 U I like this team a lot. Like Cin., if they let the best players play they would be much better. Pierre should be a fourth outfielder, no question, and not letting LaRoche play third is kind of crazy. Definitely no bet.
MIL 84 87 O I picked the BrewCrew to win the central last year and they were so close. Ryan Braun is one of my favorite new players and that offense is going to be good (even with some OBP and SO problems). Picking up Cameron improved the defense in two places. The manager has talked about batting Braun 2nd, Fielder 3rd, Kendall 9th, and the pitcher 8th to get the two best hitter more at bats while having guys on base for them. Keeping Fielder 4th would be better so that his HRs aren’t wasted with no one on base, but still. It’s the kind of thinking outside the box that makes sense and helps a team pick up a game or two. Gallardo is going to be very, very good, and if Sheets pitches the whole season I could easily see playoffs (even, dare I say, a World Series trophy). [I wasn’t a Brewers fan until a couple years ago. I like teams that are young and exciting, as well as having a clear plan and quality execution. O’s over Brewers in ’10? (it’s a joke now)]
MIN 73 74 O No bet. Liriano, when healthy is astounding. How many pitchers have that good control with that many strike-outs and all those ground balls? One. Liriano. The man had a 2.16 ERA in’06! They’re not a bad team, but they lack too much offense for Mauer and Morneau (and some from Cuddyer and Young and Kubel), to make up for it. Their starting third baseman hit .210 with 1 HR last year. Why not sign Corey Patterson to steal 40 bases and play quality defense instead of rushing a player to the majors when he isn’t ready (and Gomez is pretty clearly not ready).
NYM 93.5 93 U No bet. David Wright should have been the MVP last year. He is a major talent. Jose Reyes is also talented but very overrated. He might end up being really good, but a career OBP around .330 isn’t going to cut it from a lead-of hitter, even if he steals 100 bases (which he could, if he got on more). Santana is the favorite for the Cy Young, but what the get from Pedro and Oliver Perez may determine how good they really are. John Maine is turning into a #2 starter (wish that deal hadn’t gone down). Is Delgado done, or does have another 30 HR 100 RBI season left?
NYY 93.5 95 O A-Rod, like him or hate him (I just kinda’ dislike him) is the best player in baseball. He isn’t a choke artist, he may be a jerk, but he is the best. Jeter’s defense is really, really bad. Every quality metric says the same thing – he has no range. If he planted, turned, and threw instead of leaping and spinning he would get more guys out. It’s common sense (less momentum going away from first = stronger throw). Still, Wang is a quality #2; Andy (who is some sort of hero now for admitting (after the third time he was asked) to using HGH and then changing what he thinks he knows so many times) is still valuable; Mussina (maybe my all time favorite player, and future HOF hopefully – he deserves it) will bounce back a bit; Hughes is going to be really good; Kennedy isn’t a young Mussina as people say, but as a #5 he’ll be good. The bullpen could use a little work, but if they keep Joba there all year and use him effectively (multiple innings, important situations) that’ll solve that. He has to be really good in the pen to merit keeping him out of the rotation if he only pitches an inning at a time.
I think they’re the team to beat in the East, but other than Cano and A-Rod, that offense is susceptible to some age/health issues.
OAK 73.5 77 O Another one of my favorite teams. Lost one of their best hitters and their best pitcher and everybody thinks that they’ll be awful because they don’t have pitching and the offense is thin on stars. They did get a lot of pitching depth though, and a good hitting young outfielder who has some power but may still have some plate discipline issues. Hmm, sounds familiar. If Rich Harden is healthy, then a .500 record is in reach. They can’t possibly have as many injuries as they did last year, can they? Even if they trade Blanton, I still like the over. Billy Bean isn’t the genius some make him out to be, but he’s still one of the better GMs out there. This is the first year in the last 5 that I’m not picking them to win the division. Daric Barton = young Mark Grace?
PHI 88.5 85 U I picked them last year, but I won’t do it again. I don’t trust the pitching outside of Myers and Hamels, who is one of the top pitchers in the league (though I worry about his risk of injury). The offense is really good though. I’m fairly confident here, but if it was 88 instead I would be more hesitant. They cost themselves a lot of money with they Ryan Howard arbitration situation. If they had offered $1 million more they could have saved a couple mil this year, plus he would have gotten smaller raises in the next couple years. I don’t think I’d sign him long term though. Howard at first base at age 35 might be pretty scary.
PIT 68.5 71 O Even with the discrepancy I don’t bet here. Sill, they may not be worse than the Card’s. Ian Snell at the top of the rotation isn’t a #1, but he is a solid #2 (200 K’s this year?) and there is some pitching depth. If Jason Bay can make a bit of a comeback then 72-73 wins is certainly possible. The new front office is going to take the team in the right direction, but the almost complete lack of a farm system is going to take time to overcome.
SDP 84 85 O If Greg Maddux had been on the O’s then he would definitely be my favorite player. He could pitcher forever if he wanted to, and if you don’t trust Clemens’ late career numbers, then Mad Dog is the best pitcher in recent memory and near the top all-time. Add in Jake Peavy and Chris Young, with anything at all from Mark Prior, and you have a great pitching staff, especially in that ballpark. Kevin Towers is one of the best GMs in baseball, and I’m hoping for one last good season for a guy that deserves to get into the HOF – Jim Edmonds. I like the team a lot, but I don’t know if they have enough offense to pull off a season better than 82-80, even. No bet.
SFG 71.5 71 U Worst. Offense. Ever. That might not even be an exaggeration. Bengie Molina batting cleanup? Aaron Rowand at #3, without question? I feel bad for Matt Cain and Tim Lincecum. Cain had one of the best 7-16 seasons ever last year and Lincecum is a beast – a skinny little beast – but a beast none-the-less. Barry Zito is the most expensive #4 starter ever. All that pitching is going to be wasted for a number of years – especially with how bad the front office is. It goes to show you how many mistakes having Barry Bonds can cover up. There are going to be a lot of 1-0, 2-1 losses but it wouldn’t take much for them to luck into a 74 win season. It’s not a terrible bet though.
SEA 84.5 77 U If I had to put money on any one team, it’s the M’s. I didn’t expect this until I looked at it, but the irony is really too great. The two team that I have as furthest away from their lines are the M’s and the O’s, but it’s M’s below, even with Bedard, and O’s above, even without him. They won 9 more games than they should have last year, but unlike the DBacks, they don’t have improvements coming from all of their young players and both teams added a top starter. The pitching is good (especially at Safeco) but after Bedard and Felix Hernandez, do Carlos Silva, Jarrod Washburn, and Miguel Batista really scare you? [Now I am even less scared of Batista.]They’re all very solid, but the offense has too many holes. I actually looked at the team player by player. The players who walk don’t hit for average (Sexson) or power (Vidro. Seriously, 6 HR from the DH?). If it wasn’t the case that Sexson was only unlucky last year, then they haven’t got much to offer.
After looking at this I later (independently of this) read the following: Bill James looked at what happens to teams after they outplay their expected record. He took the 100 teams who exceeded the expected most and looked at how they did the following year. The results: on average, the teams won 87 games (M’s won 88) when they should have won 78 (M’s should have won 79), and the next year they won 80 games (I have the M’s at 81 myself. BP has them at 73). Keep in mind that teams that do well generally try to improve the following year, so it’s not that the M’s are the only one to get new pitchers.
They were very lucky last year with no explanation whatsoever, and they just aren’t that talented.
At least the O’s players have some upside. With the M’s it’s mostly downside (yeah, I’m sure Bedard will K 11 per 9 innings again). This isn’t 100%, but I think the A’s have the better team. Maybe even the O’s too. Wouldn’t that be something?
[The guy at USS Mariner, an M’s blog, has the team winning 77 games with a standard deviation of 71-84 wins. Interestingly, he also has the A’s as the division favorites over the Angels 47% to 42% with Texas about even with Seattle . 95% of his simulations had the team with 86 wins or under, 77% at 82 or under and 27% with 74 or under. The best-case was 93 wins. The problem wasn’t pitching (which their GM addressed) but a terrible offense and a bad defense. He said “Since I ran the season, I’ve stared at the results and tried to find a reason to not write this post. Some thing that would invalidate the results, or that would give me an excuse to change something and go back to do it all over with even more pro-Mariner assumptions. But there isn’t…If you start from last year’s team and make adjustments, it’s easy to come up with another five, ten, sixteen wins. But starting from scratch, using reasonable assumptions, the picture looks much bleaker.”] Even real slam-dunks miss sometimes, if the ball gets stuck or bounces off the rim, but I’d call this my “shoe-in” or “lock” or whatever other term they use.
STL 77 73 U A bad team. If Pujols goes down then they’re done. The scary thing is; Pujols has been playing with injuries most of his career. What would he have done if healthy? They should have been a 71 win team last year, but somehow won 78 games. At least the fans don’t need to deal with David Eckstein articles anymore. Yes he’s small. And really white. We get it. Even if he tries really hard he still isn’t very good. He gets on base OK. That’s it. He’s just not good, no matter how scrappy he is. (And don’t even get me started on Darin Erstad. Who cares that he was a punter for his college football team? That doesn’t make him good at baseball. That doesn’t even make him that tough. He was the punter.) Anyway, I like the under a lot. I really would be surprised if the were over 77.
TEX 74.5 73 U I like the direction the team is heading, but it’s not there yet. I wouldn’t bet on this one though, in either direction.
TOR 85 83 U I don’t think I’d bet here. At 86 I might, but not 85. Dustin McGowan is a quality pitcher (he had the highest average fastball velocity among starters last year; 96.1 mph I believe it was). It’s hard to tell what they’ll get from Vernon Wells, and that contract doesn’t look good if he’s merely “good”. Alex Rios is the best defensive RF in the league, and Aaron Hill might surprise at second base. A shame they won’t let Adam Lind play, though I do love seeing Matt Stairs around. The guy kind of looks like a lumberjack he makes his own bat out of a tree that he chopped down. I doubt they’ll challenge the Sox and Yanks much - they should be more concerned with Tampa Bay next year.
TBR (Since its Rays instead of Devil Rays TBD should change to TBR right?) No O/U given, but predicting 79 wins. That’s right, 79. If they signed Bonds it would be over .500 (as long as Kazmir isn’t hurt). Kazmir/Shields/Garza/McGee/Davis/Sonnastine/Price/… whoever is going to be a very good rotation. Maybe not this year, but soon. They have some actual major leaguers in the bullpen now. Pena probably won’t repeat last year average wise, but the power and on-base skills are legit (though 46HR is a bit much). The defense should go from bad ( Upton made ~12 errors in 48 games at second) to good (new SS Bartlett is one of the better defenders in baseball), and Evan Longoria can seriously hit. If they weren’t in the AL East I would be rooting for them more, but their front office is finally on-the-ball and they should have their eyes set on the division crown in the near future (especially if they can afford to keep their best players). If the line is as low 76 wins I’m in, as I’ve seen predictions as high as 89 (as a median).
WAS 71.5 71 U No bet. They overachieved last year. The team is improving but the rotation is still lacking behind Shawn Hill and John Patterson (hopefully) and the lineup is improved but still nothing great. Dmitri Young playing over Nick Johnson is a waste. If the new park is as friendly is it sounds to be Lastings Milledge could go 20/20 next year. Wily Mo Pena might go 30/150 (that’s homeruns/strikeouts). Zimmerman is good and going to be very good, but he definitely doesn’t deserve the David Wright money that he’s asking for (yet, at least). Manny Acta is one of the smartest managers around though.
There’s another bet that is possible. It involves “clutch” hitting. One can bet on “clutch” hitting in 2008 by specifying a group of “clutch” players and a group of “choke” players, as well as a situation (ex. after the 7th inning and tied, or whatever). At the end of the year the groups are compared. Whichever one had better relative performance (via batting average) in the given situation wins. There are 2-1 odds, though, against there being a difference. If you’re 67% sure that you can hand-pick player(s) and they’ll be more “clutch” than your hand-picked “chokers” then let me know. It can even be one “clutch” guy vs. a bunch of “chokers” or whatever. Derek Jeter vs. A-Rod with the game on the line? David Ortiz vs. Neifi Perez, Eduardo Perez, all of the Perez’s? The stipulations need to be approved (can’t define clutch as when an NL guy hits against a bad pitcher or an AL guy hits against a good pitcher and have the groups be NL and AL guys, etc.) but if you believe “clutch” exists, you should be able to point it out.
Read more ...Player Valuation Primer
This will borrow heavily from the excellent introduction by Dave Cameron on FanGraphs of their Win Values stat (located below - I'm mostly summarizing, but I highly recommend going through their explanation), as well as Tom Tango's explanations on his blog.
Position Players:
Batting, Fielding, Position, Replacement, Converting Runs To Wins, Dollars, Extra.
Pitchers:
Intro, FIP, Replacement, Run Environments, Runs To Wins, Park Adjustments, Calculations.
Measure of Value:
Wins are the goal for a team, and so the number of wins that a player adds to a team should be the goal we strive for in valuing them. The various metrics are measured in runs, so a runs to wins conversion is required.
The relationship between runs and wins on a team level is seen using the Pythagorean Winning Percentage Formula (Winning % = (Runs Scored ^ 2) / (Runs Scored ^ 2 + Runs Allowed ^ 2), though the PthyagPat formula is slightly more accurate as it adjusts dynamically for the run scoring environment.) A team that scores 800 runs and allows 800 runs will have a .500 winning %, and so go 81-81. Changing either runs scored or runs allowed by 10 would result in the final total changing by about 1 win, so that's what is used. 10 runs ~ 1 win.
Position Players:
Batting: The nice thing about wOBA is that it gives a fairly complete measure of offensive production using (adjusted) linear weights of the run value of it's component stats. That means we can go from wOBA to the value in runs (and thus wins) that a player contributes with the bat pretty quickly.
With an assumed league-average wOBA of .335, we have Batting Wins = (wOBA - .335) / 1.15 * PA / 10. This converts wOBA above-average to runs above average (that's the 1.15) and then to wins above average (the 10). A full season's worth of PA (700) is can be used to start out and then playing time would be adjusted later.
Example: 2009 Nick Markakis (lets just say) has a wOBA of about .395. His value with the bat would be about (.395 - .335) / 1.15 * 700 / 10 = 3.65 wins. He would add about 3.65 wins to the team over what an average hitter would with his bat, given 700 PA. (For less PA just multiply by PA/700).
Fielding: There are a number of ways to evaluate the defensive contributions of a player, but FanGraphs uses UZR with value from outfield throwing and double play turning also available. These are in runs above average for players at the given position, and so can be converted to wins by dividing by 10. For catchers there's even more work to be done (how much is calling a "good game" worth?).
Example: 2009 Nick Markakis has slightly above average range in right, so we say he saves about 2.5 runs by getting to balls that an average RF fielder wouldn't. We also say he has a great arm, and so saves 5 runs by throwing out runners as well as keeping them from advancing due to fear of being thrown out above what an average fielder would. Dividing by 10, we have Nick as being worth 0.75 wins above average with his glove (and arm).
Position: It's a lot easier to find a guy with the skills to play first-base (catch the ball when thrown to you, largely) than it is to find a guy with the skills to play short (range, arm, etc). That means a guy who can handle short is valuable - all else being equal - than a guy who can only handle first-baseman. By looking at players that played multiple position, Tom Tango was available to develop an adjustment to show the relationship between players at all of the positions. For example: when an average shortstop (+0 runs) moves to second-base, he plays +5 run defense. A good left-fielder (+10 runs) could move to center and be about an average center-fielder (+0 runs). And so on. Therefore, the interrelationships between the positions can be adjusted using the following (assuming a full season at the position):
C: + 12.5 runs
1B: - 12.5 runs
2B: + 2.5 runs
3B: + 2.5 runs
SS: + 7.5 runs
LF: - 7.5 runs
CF: + 2.5 runs
RF: - 7.5 runs
DH: - 17.5 runs
Example: 2009 Nick Markakis will play RF, so that's - 7.5 run. If he could play center as well as he plays right then he'd be worth 10 more runs to the team.
We can now say how valuable a player is relative to average. Nick Markakis is (given a full season) 3.65 wins with the bat plus 7.5 wins with the glove minus 7.5 wins for being limited (relatively speaking) to right-field. That's a total of 3.65 wins above average.
Replacement Level: Instead of comparing to average, we would like to compare a player to the guy that would take his spot if he wasn't available - a guy that's just wandering around in the minors looking for a chance - a replacement player. These are guys that are available for the league minimum and any team has a shot at; guys like Justin Christian, Terry Tiffy, and Brandon Fahey. Now in reality, this would depend on the team's bench and what players they have available, but we're going for a general level. A replacement level adjustment is about 22.5 runs. That is, an average player is about 22.5 runs better overall than the Brandon Fahey's of the world. This value is different, however, in the two leagues. The AL has better players, on average, than the NL, and so the adjustment is 25 runs for AL players and 20 runs for NL players. The runs is again converted to wins by diving by 10.
Example: 2009 Nick Markakis is 3.65 wins above average, which makes him (as an AL player) 6.15 wins above replacement. If the O's play Justin Christian in right-field all season instead of Nick Markakis, they'd be worse by close to 6 wins.
Playing Time: There aren't a lot of Cal Ripken Jr.'s around anymore, so one needs to adjust the win values (that are for 700 PA, or a full season in the field) for how much a player actually contributes.
For Example: 2009 Nick Markakis gets 650 PA (and play an equal proportion of innings in right), so he should be worth (650/700) * 6.15 = 5.7 wins. 2009 Nick Markakis is worth 5.7 wins (about 57 runs) more than a replacement level player. That's 5.7 WAR, for short.
Extras: One can (and probably should) add in other things like base-running, but Batting, Fielding, Position, and Playing Time gets the majority of the player's value down.
Pitchers:
Rate of Runs Allowed: We want to know how good a pitcher is, so the proxy for that is how many runs he is responsible for (though not necessarily directly). ERA has some problems with were the responsibility for having given up a run goes, so either FIP or tRA (I prefer the latter converted to ER from R, but they're very similar) do the job as a stand-in. Apply all context adjustments (league, park, etc.) where necessary.
Example: 2009 Jeremy Guthrie has a 4.15 "ERA" (from about a 4.50 tRA).
Replacement Level: Like with the position players, we want to know how much the pitcher actually adds to the team over the guy who'd be there in his place (your Steve Trachsel's of the world). Since it's easier to pitch out of the pen, there's a difference between starters and relievers, in addition to the AL/NL split.
The contribution is distinguished by winning percentage, with a replacement level starter expected to win 38% of his games given league average offense, bullpen, and opponent. With a average starter, offense, and opponent, a replacement level bullpen should win about 47% of their games.
"ERA" to W% Conversion: Since the run scoring environment in which a pitcher plays effects how low of an "ERA" he'll need to maintain a certain W%, an adjustment is needed. Using the league-average ERA and the PythagenPat formula, an individual pitcher's W% can be calculated.
For Example: 2009 Guthrie's 4.15 "ERA" with a league-average ERA of 4.30 results in a W% of 51.7%. His "ERA" is slightly better than average and so he'll win a little more than half his games.
[Step by step: (4.15 + 4.30) / .92 to get total run (the .92 is for earned runs to runs) environment of 9.18 runs. PthagenPat; 9.18 ^ .28 = 1.86. Wins/Losses = (4.30/4.15) ^ 1.86 = 1.068. W% = Wins / Wins+Losses = 1.068 / 1.068+1 = 0.517 = 51.7%.]
W% to Wins: To find how many wins above a replacement level player a pitcher is worth, lets find how many more game she's expected to win. The number of full games he's expected to pitch is IP / 9. Then multiply by the percent of games he's expected to win, above what a replacement level pitcher would.
Example: 2009 Guthrie pitches 20 games (180 IP / 9) with an expected winning percentage above replacement of 14.7 % (.517 - .370 for being an AL starter). That's 2.9 WAR.
Leverage: There's an additional adjustment made for relievers, depending on how important (high leverage, based on score, inning, and base/out situation) their innings are. A closer with a 3.00 ERA is going to be more valuable than a mop-up man with a 3.00 ERA, all else being equal. A relievers base WAR is multiplied by their leverage index (1.0 is average; 1.8 is what closers are likely to see; 0.6 is for mo-up guys) to get their final WAR.
Example: 2009 Jim Johnson was a 3.80 "ERA" in 65 IP. That makes him a 0.7 WAR regular reliever (LI of 1.0) but a 0.9 WAR pitcher as the set-up man (LI of 1.3).
So there we go; we now have a way to say how valuable players are. The next step would be to adjust to dollars, by looking at what teams pay players on the free agent market and dividing how many WAR the players are worth. For 2008 it was about $4.4 M per WAR, so (assuming 10% salary inflation, which is probably high in this economy) it should be about $4.84 M per WAR for 2009.
Example: 2009 Nick Markakis is worth about 5.7 WAR, which on the free agent market would cost about $27.6 M. Read more ...
Position Players:
Batting, Fielding, Position, Replacement, Converting Runs To Wins, Dollars, Extra.
Pitchers:
Intro, FIP, Replacement, Run Environments, Runs To Wins, Park Adjustments, Calculations.
Measure of Value:
Wins are the goal for a team, and so the number of wins that a player adds to a team should be the goal we strive for in valuing them. The various metrics are measured in runs, so a runs to wins conversion is required.
The relationship between runs and wins on a team level is seen using the Pythagorean Winning Percentage Formula (Winning % = (Runs Scored ^ 2) / (Runs Scored ^ 2 + Runs Allowed ^ 2), though the PthyagPat formula is slightly more accurate as it adjusts dynamically for the run scoring environment.) A team that scores 800 runs and allows 800 runs will have a .500 winning %, and so go 81-81. Changing either runs scored or runs allowed by 10 would result in the final total changing by about 1 win, so that's what is used. 10 runs ~ 1 win.
Position Players:
Batting: The nice thing about wOBA is that it gives a fairly complete measure of offensive production using (adjusted) linear weights of the run value of it's component stats. That means we can go from wOBA to the value in runs (and thus wins) that a player contributes with the bat pretty quickly.
With an assumed league-average wOBA of .335, we have Batting Wins = (wOBA - .335) / 1.15 * PA / 10. This converts wOBA above-average to runs above average (that's the 1.15) and then to wins above average (the 10). A full season's worth of PA (700) is can be used to start out and then playing time would be adjusted later.
Example: 2009 Nick Markakis (lets just say) has a wOBA of about .395. His value with the bat would be about (.395 - .335) / 1.15 * 700 / 10 = 3.65 wins. He would add about 3.65 wins to the team over what an average hitter would with his bat, given 700 PA. (For less PA just multiply by PA/700).
Fielding: There are a number of ways to evaluate the defensive contributions of a player, but FanGraphs uses UZR with value from outfield throwing and double play turning also available. These are in runs above average for players at the given position, and so can be converted to wins by dividing by 10. For catchers there's even more work to be done (how much is calling a "good game" worth?).
Example: 2009 Nick Markakis has slightly above average range in right, so we say he saves about 2.5 runs by getting to balls that an average RF fielder wouldn't. We also say he has a great arm, and so saves 5 runs by throwing out runners as well as keeping them from advancing due to fear of being thrown out above what an average fielder would. Dividing by 10, we have Nick as being worth 0.75 wins above average with his glove (and arm).
Position: It's a lot easier to find a guy with the skills to play first-base (catch the ball when thrown to you, largely) than it is to find a guy with the skills to play short (range, arm, etc). That means a guy who can handle short is valuable - all else being equal - than a guy who can only handle first-baseman. By looking at players that played multiple position, Tom Tango was available to develop an adjustment to show the relationship between players at all of the positions. For example: when an average shortstop (+0 runs) moves to second-base, he plays +5 run defense. A good left-fielder (+10 runs) could move to center and be about an average center-fielder (+0 runs). And so on. Therefore, the interrelationships between the positions can be adjusted using the following (assuming a full season at the position):
C: + 12.5 runs
1B: - 12.5 runs
2B: + 2.5 runs
3B: + 2.5 runs
SS: + 7.5 runs
LF: - 7.5 runs
CF: + 2.5 runs
RF: - 7.5 runs
DH: - 17.5 runs
Example: 2009 Nick Markakis will play RF, so that's - 7.5 run. If he could play center as well as he plays right then he'd be worth 10 more runs to the team.
We can now say how valuable a player is relative to average. Nick Markakis is (given a full season) 3.65 wins with the bat plus 7.5 wins with the glove minus 7.5 wins for being limited (relatively speaking) to right-field. That's a total of 3.65 wins above average.
Replacement Level: Instead of comparing to average, we would like to compare a player to the guy that would take his spot if he wasn't available - a guy that's just wandering around in the minors looking for a chance - a replacement player. These are guys that are available for the league minimum and any team has a shot at; guys like Justin Christian, Terry Tiffy, and Brandon Fahey. Now in reality, this would depend on the team's bench and what players they have available, but we're going for a general level. A replacement level adjustment is about 22.5 runs. That is, an average player is about 22.5 runs better overall than the Brandon Fahey's of the world. This value is different, however, in the two leagues. The AL has better players, on average, than the NL, and so the adjustment is 25 runs for AL players and 20 runs for NL players. The runs is again converted to wins by diving by 10.
Example: 2009 Nick Markakis is 3.65 wins above average, which makes him (as an AL player) 6.15 wins above replacement. If the O's play Justin Christian in right-field all season instead of Nick Markakis, they'd be worse by close to 6 wins.
Playing Time: There aren't a lot of Cal Ripken Jr.'s around anymore, so one needs to adjust the win values (that are for 700 PA, or a full season in the field) for how much a player actually contributes.
For Example: 2009 Nick Markakis gets 650 PA (and play an equal proportion of innings in right), so he should be worth (650/700) * 6.15 = 5.7 wins. 2009 Nick Markakis is worth 5.7 wins (about 57 runs) more than a replacement level player. That's 5.7 WAR, for short.
Extras: One can (and probably should) add in other things like base-running, but Batting, Fielding, Position, and Playing Time gets the majority of the player's value down.
Pitchers:
Rate of Runs Allowed: We want to know how good a pitcher is, so the proxy for that is how many runs he is responsible for (though not necessarily directly). ERA has some problems with were the responsibility for having given up a run goes, so either FIP or tRA (I prefer the latter converted to ER from R, but they're very similar) do the job as a stand-in. Apply all context adjustments (league, park, etc.) where necessary.
Example: 2009 Jeremy Guthrie has a 4.15 "ERA" (from about a 4.50 tRA).
Replacement Level: Like with the position players, we want to know how much the pitcher actually adds to the team over the guy who'd be there in his place (your Steve Trachsel's of the world). Since it's easier to pitch out of the pen, there's a difference between starters and relievers, in addition to the AL/NL split.
The contribution is distinguished by winning percentage, with a replacement level starter expected to win 38% of his games given league average offense, bullpen, and opponent. With a average starter, offense, and opponent, a replacement level bullpen should win about 47% of their games.
"ERA" to W% Conversion: Since the run scoring environment in which a pitcher plays effects how low of an "ERA" he'll need to maintain a certain W%, an adjustment is needed. Using the league-average ERA and the PythagenPat formula, an individual pitcher's W% can be calculated.
For Example: 2009 Guthrie's 4.15 "ERA" with a league-average ERA of 4.30 results in a W% of 51.7%. His "ERA" is slightly better than average and so he'll win a little more than half his games.
[Step by step: (4.15 + 4.30) / .92 to get total run (the .92 is for earned runs to runs) environment of 9.18 runs. PthagenPat; 9.18 ^ .28 = 1.86. Wins/Losses = (4.30/4.15) ^ 1.86 = 1.068. W% = Wins / Wins+Losses = 1.068 / 1.068+1 = 0.517 = 51.7%.]
W% to Wins: To find how many wins above a replacement level player a pitcher is worth, lets find how many more game she's expected to win. The number of full games he's expected to pitch is IP / 9. Then multiply by the percent of games he's expected to win, above what a replacement level pitcher would.
Example: 2009 Guthrie pitches 20 games (180 IP / 9) with an expected winning percentage above replacement of 14.7 % (.517 - .370 for being an AL starter). That's 2.9 WAR.
Leverage: There's an additional adjustment made for relievers, depending on how important (high leverage, based on score, inning, and base/out situation) their innings are. A closer with a 3.00 ERA is going to be more valuable than a mop-up man with a 3.00 ERA, all else being equal. A relievers base WAR is multiplied by their leverage index (1.0 is average; 1.8 is what closers are likely to see; 0.6 is for mo-up guys) to get their final WAR.
Example: 2009 Jim Johnson was a 3.80 "ERA" in 65 IP. That makes him a 0.7 WAR regular reliever (LI of 1.0) but a 0.9 WAR pitcher as the set-up man (LI of 1.3).
So there we go; we now have a way to say how valuable players are. The next step would be to adjust to dollars, by looking at what teams pay players on the free agent market and dividing how many WAR the players are worth. For 2008 it was about $4.4 M per WAR, so (assuming 10% salary inflation, which is probably high in this economy) it should be about $4.84 M per WAR for 2009.
Example: 2009 Nick Markakis is worth about 5.7 WAR, which on the free agent market would cost about $27.6 M. Read more ...
Stat Primer
I know the level of discource on here (writing quality not withstanding) is somewhat higher than what your average fan is used to. Therefore I thought it would be handy if I went over some stats I reference.
Offense:
Batting Average (BA): This used to be the #1 place a person would look to see how good a player is - not so anymore. Batting average's main flaw is the level to which it is luck dependent. How many times have you seen a guy go 0 for 4 in a game with four line-drives hit right at people; or go 3 for 4 with two bloops over the infield and a "seeing-eye" grounder just by the shortstop? BA is important in that a guy who is able to consistently hit for a high average (like Albert Pujols, Vlad Guerrero, or Ichiro) was good bat-control skills, which makes him a better hitter. An "empty" batting average occurs when a guy hits .300 (or some other high mark) but that goes along with few walks and little power (Juan Pierre) which severely dampens the overall effectiveness of the player as an offensive force. BA gives you some info. about a player and - all else being equal - it's better for it to be higher, but it doesn't tell you too much about a player's overall value.
BA: [.300 and above is good, .250 and below is not.]
Batting Average on Balls In Play (BABIP): This goes right along with the luck aspect of batting average. It is calculated by [Hits - Home Runs] / [At Bats - Home Runs - Strike Outs + Sacrifice Flies]. It shows how often a play that is put in play by the batter ends up being a hit. The league average for BABIP is around .300. That means that a player who hits .330 but has a BABIP of .400 has probably gotten lucky ( a lot more balls are falling in than can be expected) and his BA is likely to go down. Similarly, a player who hits .250 but has a BABIP of .210 has been unlucky, and his BA is expected to go up. Batters do have some control over this statistic (Ichiro, for example, has higher a BABIP because he uses his speed to beat out infield hits) and so it is useful to look at a particular player's career BABIP numbers, but in general it serves as a useful way to look at BA in some context. There are many studies looking at which factors go into BABIP so that a better understanding of lucky/unlucky can be developed.
BABIP: [.340 and above is good, .230 and below is not.]
Line Drive Percentage (LD%): LD% is important since line drives result in hits much more often then ground balls or fly balls and so a better hitter (Pujols) who hits more line drives is likely to then have a higher BABIP (and thus BA, all else being equal) that isn't as luck-based. Intuitively; if a guy is always hitting the ball hard he's probably a pretty good hitter.
LD%: [.200 and above is good; .150 and below is not.]
Home Run per Fly Ball (HR/FB): It's a measure of both power and luck. If a player sees a drop in HR/FB then it could indicate a loss of power. By actually looking at the distances of balls hit, this can be corroborated (if all HRs were shorter) or possibly negated (if there were several balls that just missed, by still a good number of long ones). On the other hand, a HR/FB rate much higher than a player's established career baseline could indicate a flukey HR season that won't be repeated.
On-Base Percentage (OBP): This is, in general, the most important statistic for determining a player's value to an offense. The objective of the batter is to not make an out - outs are a scarce resource, and as soon as you use up 27 (usually) you don't get any more chances to score runs. OBP shows you how good a player is at not making outs. Having a high OBP (via walks) also indicates a patient approach and good pitch-recognition skills. These things allow a hitter to not only walk more often, but to be better able to identify good pitches to hit (swing at strikes, not at balls) and not to make "bad" outs (bad in the sense that they have little chance to become hits - pop-ups, easy grounders, and of course strike-outs). Team OBP correlates very highly to scoring runs, as the first part of scoring is getting guys on base.
OBP: [.360 and above is good; .330 and below is not.]
Slugging Percentage (SLG): This is, in general, the second most important statistics for determining a player's offensive value. It is a way to measure the efficiency of a players at bats (not plate appearances). The higher the SLG, the more bases a player accumulates and the closer he is to scoring a run (and is better at driving them in). Hitting a HR results in at least one run automatically; a triple will generally score all runners on the bases and put the batter just 90 ft. away from home plate himself; and so on. Therefore, a player with a high SLG is able to contribute to the second thing necessary to score runs - advancement.
SLG: [.450 and above is good; .400 and below is not.]
Triple Slash (BA / OBP / SLG): Showing all three stats like this gives a quick picture at the hitter's skills. .300/.340/.370 is a Juan Pierre type hitter; .240/.380/.500 is a Adam Dunn type; .260/.310/.480 is a Mike Jacobs type; and so on.
Isolated Power (ISO): It's SLG minus BA, and gives an idea of how much power a player has by looking at the number of extra bases per at bat. A guy can have a SLG of .450 as a product of hitting .350 with a lot of singles and only a little bit of power (.100 ISO), or he can hit .250 with a lot of doubles/triples/homers (.200 ISO). League average is around .150. [Baseball Prospectus has a modified version of ISO that counts triples the same as doubles, since stretching a double into a triple is more a product of speed than power.]
ISO: [.215 and above is good; .110 and below is not.]
On-Base Plus Slugging Percentage (OPS): While not completely, OPS does a great job of quickly giving a player's total offensive contributions. High OPS means a player is good in both areas of getting on base and advancement, or exceptional at one of the two. It does weight OBP and SLG the same, which is an issue.
OPS: [.800 and above is good; .700 and below is not.]
OPS+: The "+" indicates that the player's OPS has been adjusted for context (their home park, for example) and then compared to the rest of the league. An OPS+ of 100 indicates league average. An OPS+ of 110 means a players adjusted OPS is 10% above league average. This allows players from different eras (when pitching was dominant vs. when hitters had the upper hand) by comparing them to everyone they played with. It still has the same weighting issue as OPS.
Walks, or Base on Balls (BB): A player with a good walk rate can maintain a high OBP even when his BA is low (whether because of ability or bad luck). As mentioned with OBP, patience and pitch-recognition are valuable all the time, not just when taking a base on balls. BB% is the rate at which a player walks.
BB%: [12% and above is good; 7% and below is not.]
Strike-Outs (K): In general, a K is just like any other out. Players who K a lot can still be very productive hitters. A high K rate does make it harder to have a high BA as there are less balls being put in play that can result in hits. Also, a K does not help advance runners, whereas a ground ball can (though it can result in a double play also - one out is bad; two is much worse). For younger players a high K rate could indicate a problem in their swing (can't handle inside pitches, for example), poor pitch recognition (swings at breaking balls in the dirt), or a propensity to swing for the fences (which tends to show up in how often they pull the ball also). These things can keep a player from having success at the major league level if they aren't corrected. K% is the rate at which a player strikes out.
K%: [13% and below is good; 23% and above is not.]
Stolen Bases (SB): Stealing bases at a rate below 70% actually costs a team runs. When looking at the value of having a player (starting at first base with none out) at second with none out or on the bench with one out, being caught has a change in magnitude (of expected run scoring) 70% larger than being safe. This can be found by looking at a run expectancy matrix. For 2005 it looked like this:
OUTS
RUNNERS 0 1 2
--- 0.5165 0.2796 0.1075
1-- 0.8968 0.5487 0.2370
-2- 1.1385 0.6911 0.3502
12- 1.4693 0.9143 0.4433
--3 1.5120 0.9795 0.3718
1-3 1.8228 1.1830 0.4931
-23 2.0363 1.4144 0.6073
123 2.3109 1.5279 0.7485
So with a runner on first and no outs, a team from 2005 scored an average of 0.8968 runs. (These values tend to be pretty close in recent years. In 2006 it might have been .9001 runs or something like that.) Having the runner steal second successfully will result in E(R) going up by 0.2417 to 1.1385. If he is caught, it goes down by 0.6172 to 0.2796. Therefore a player needed to be successful 71.9% of the time (0.6172 / [0.6172 + 0.2417] ) for it to be worth it. [It's actually been more like 74% recently.] Guys that are gooding at stealing bases help their team by running selectively; guys that aren't good at stealing bases should usually stay put (even if they're fast).
Runs (R) and Runs Batted In (RBI): I mention these as they give an idea of how a hitter is doing, even though they say very little about his actual abilities. Not particularly good hitters can have 100 RBI (Jay Gibbons) or score 100 runs (Juan Pierre) almost entirely because of opportunities they get. Jay Gibbons hit 4th and had many chances to hit with men on base. Juan Pierre bats first and so gets on base more times than other hitters (even though his OBP is lower) and so has more chances to have someone drive him in. They are very team dependent stats, and tell you little about a player's value.
Weighted On-Base Average (wOBA): It combines OBP and SLG basically using linear weights.
The nice thing about baseball is that everything that happens on the field has happened that way hundreds of times before (in a non-context dependent sense - a single to right; not a player's 3000th hit on a single to right). That means we can look and see how much any given event helps a team score runs. For example, on average, a double increases a team's expected runs scored by about 1.08 (relative to making an out). For a walk it's about 0.62 runs. Linear weights multiplies the value of each event by how many of them a player accumulated. Tom Tango (and co.) took these values for a bunch of stats, scaled them to OBP, and then divided by plate appearance to get a rate stat. That way, wOBA is on the same scale as OBP (since they're linear), so a wOBA of .340 is about average. Expect it gives a more complete measure of offensive prodiction.
wOBA: [.370 and above is good; .300 and below is not.]
Pitching:
Hits Allowed (H): This can give some idea of the effectiveness of a pitcher, but just like BA for offense it is also dependent on luck, as well as a team's defense. A pitcher with a high BABIP against is giving up more hits than he should (the BABIP should be compared to the team average, not the league as this normalizes it for the defense he pitches in front of). A pitcher who has a good season based on giving up few hits while having a very low BABIP should be expected to regress in the future. Some pitchers, through deception or pitch selection or what have you, have been able to keep their BABIP lower than would be expected (by giving up less line drives, generally). Thus, it is a good idea to look at career BABIP also.
BABIP: [.275 and below is good; .325 and above is not.]
Walks, or Base on Balls (BB): A pitcher with high walk totals is not only going to allow more men on base, he is usually going to be less effective when not walking guys and he'll have to throw more pitches (and thus pitch less innings). Pitchers whose pitches are not very effective themselves (they have bad "stuff") need to limit their walk rate (BB/9 - walks per nine innings pitched) to be able to have success at the major league level. A high BB/9 will not doom a pitcher, but it makes the margin for error in other parts of his game very small. If a guy can't get on base he can't score.
BB/9: [2.5 and below is good; 4.5 and above is not.]
Strike-Outs (K): Every batter that a pitcher K's is one that can't get a hit. A high K rate (K/9) means a pitcher is being successful more often than not, and a low K rate means that a pitcher is in trouble without some other saving grace. Like BB/9, a bad K/9 can be made up for - it requires very good control (low BB/9) or the ability to get ground balls (to prevent extra-base hits). Many sinker-ball pitchers have low K/9 but are still successful - it is just a fine line that they walk with their control and infield defense being very important.
K/9: [7.5 and above is good; 5.5 and below is not.]
Walks and Hits per Inning Pitched (WHIP): This is a quick way to see how many runners a pitcher is allowing. Don't give up hits and don't walk guys, and it makes it tough for the opposition to score.
WHIP: [1.20 and below is good; 1.40 and above is not.]
Home Runs (HR): A pitcher who gives up a lot of home runs will, in general (Johan Santana seems to be doing OK), give up a lot of runs. Keeping the ball in the park forces a team to put together strings of hits (and walks) to score runs, which is much more difficult. This is park dependent though, as giving up 1 HR/9 at the Cell in Chicago is very different from giving up 1 HR/9 in Petco.
HR/9: [0.70 and below is good; 1.35 and above is not.]
Ground Ball Percentage (GB%): You can't hit a grounder for a HR, so it helps in that respect. All extra base hits are less frequent on groundballs, in fact. It results in more outs than line drives, and also more double plays. Brandon Webb would appreciate having a good defensive infield behind him.
Earned Run Average (ERA): ERA is dependent on luck - not only how many hits a pitcher gives up but their distribution. Also, the earned run vs. unearned run disparity doesn't make that much sense anymore and so it isn't even a good measure of how many runs a pitcher gives up. Another problem occurs when relief pitchers allow runners a starter puts on to score. It is park and defense dependent and generally not very useful for saying much about a pitcher's abilities. It does give a general idea though.
ERA: [3.50 and below is good; 5.00 and above is not.]
ERA+: Like OPS+, this adjusts ERA for home park, and compares it to the league average.
Feilding Independent Pitching (FIP): Looks at the things a pitcher controls more directly (strike-outs, walks, and home runs) and scales it to ERA. It takes out a lot of the luck from balls in play (though not flukey HR rates - there's xFIP which gives expected FIP given a regressed HR rate).
FIP: [3.50 and below is good; 5.00 and above is not.]
tRA: "Developed by Graham MacAree... tRA involves assigning run and out values to all events under a pitcher's control and coming up with an expected number of runs allowed and outs generated in a defense and park neutral environment. tRA is on a R/9 scale and does not involve any regression of the rates so while it should be more useful at determining a pitcher's true talent level, the best method for pitching projection is to use tRA*, the regressed version of tRA." - StatCorner.com
tRA is calculated in a manner similar to wOBA in that it assigns run values to different events (a K saves about 0.11 runs, while a BB costs about 0.33 runs, a line drive allowed costs about 0.38 runs, and so on). Then the number of runs a pitcher is expected to give up is divided by the numbers of outs he is expected to get, and then multiplied by 27 to give the expected numbers of runs allowed per 9 innings. So one can think of it kind of like ERA (except without the whole earned/unearned thing so it's about 8% higher).
tRA: [3.75 and below is good; 5.50 and above is not.]
tRA+: Adjusted tRA, like OPS+ and ERA+.
FanGraphs also has info. on what pitches a guy throws, how often he throws them, and their velocity. And - for both pitchers and hitters - the percent of pitches thrown in and out of the strike zone; the percent (also split out) that are swung at; and the contact rate (also split out). They are putting out a ton of useful stats.
Defense:
This is the part of the game where the usefullness of stats is still catching up. There are a lot of places to go to get data regarding defensive value, including Plus/Minus from the Fielding Bible; Ultimate Zone Rating (plus arm and double play turning stats) from FanGraphs; the Probablistic Model of Range from BaseballMusings; the Fans' Scouting Reports complied by Tom Tango at TheBook; and a whole host of other sources. Read more ...
Offense:
Batting Average (BA): This used to be the #1 place a person would look to see how good a player is - not so anymore. Batting average's main flaw is the level to which it is luck dependent. How many times have you seen a guy go 0 for 4 in a game with four line-drives hit right at people; or go 3 for 4 with two bloops over the infield and a "seeing-eye" grounder just by the shortstop? BA is important in that a guy who is able to consistently hit for a high average (like Albert Pujols, Vlad Guerrero, or Ichiro) was good bat-control skills, which makes him a better hitter. An "empty" batting average occurs when a guy hits .300 (or some other high mark) but that goes along with few walks and little power (Juan Pierre) which severely dampens the overall effectiveness of the player as an offensive force. BA gives you some info. about a player and - all else being equal - it's better for it to be higher, but it doesn't tell you too much about a player's overall value.
BA: [.300 and above is good, .250 and below is not.]
Batting Average on Balls In Play (BABIP): This goes right along with the luck aspect of batting average. It is calculated by [Hits - Home Runs] / [At Bats - Home Runs - Strike Outs + Sacrifice Flies]. It shows how often a play that is put in play by the batter ends up being a hit. The league average for BABIP is around .300. That means that a player who hits .330 but has a BABIP of .400 has probably gotten lucky ( a lot more balls are falling in than can be expected) and his BA is likely to go down. Similarly, a player who hits .250 but has a BABIP of .210 has been unlucky, and his BA is expected to go up. Batters do have some control over this statistic (Ichiro, for example, has higher a BABIP because he uses his speed to beat out infield hits) and so it is useful to look at a particular player's career BABIP numbers, but in general it serves as a useful way to look at BA in some context. There are many studies looking at which factors go into BABIP so that a better understanding of lucky/unlucky can be developed.
BABIP: [.340 and above is good, .230 and below is not.]
Line Drive Percentage (LD%): LD% is important since line drives result in hits much more often then ground balls or fly balls and so a better hitter (Pujols) who hits more line drives is likely to then have a higher BABIP (and thus BA, all else being equal) that isn't as luck-based. Intuitively; if a guy is always hitting the ball hard he's probably a pretty good hitter.
LD%: [.200 and above is good; .150 and below is not.]
Home Run per Fly Ball (HR/FB): It's a measure of both power and luck. If a player sees a drop in HR/FB then it could indicate a loss of power. By actually looking at the distances of balls hit, this can be corroborated (if all HRs were shorter) or possibly negated (if there were several balls that just missed, by still a good number of long ones). On the other hand, a HR/FB rate much higher than a player's established career baseline could indicate a flukey HR season that won't be repeated.
On-Base Percentage (OBP): This is, in general, the most important statistic for determining a player's value to an offense. The objective of the batter is to not make an out - outs are a scarce resource, and as soon as you use up 27 (usually) you don't get any more chances to score runs. OBP shows you how good a player is at not making outs. Having a high OBP (via walks) also indicates a patient approach and good pitch-recognition skills. These things allow a hitter to not only walk more often, but to be better able to identify good pitches to hit (swing at strikes, not at balls) and not to make "bad" outs (bad in the sense that they have little chance to become hits - pop-ups, easy grounders, and of course strike-outs). Team OBP correlates very highly to scoring runs, as the first part of scoring is getting guys on base.
OBP: [.360 and above is good; .330 and below is not.]
Slugging Percentage (SLG): This is, in general, the second most important statistics for determining a player's offensive value. It is a way to measure the efficiency of a players at bats (not plate appearances). The higher the SLG, the more bases a player accumulates and the closer he is to scoring a run (and is better at driving them in). Hitting a HR results in at least one run automatically; a triple will generally score all runners on the bases and put the batter just 90 ft. away from home plate himself; and so on. Therefore, a player with a high SLG is able to contribute to the second thing necessary to score runs - advancement.
SLG: [.450 and above is good; .400 and below is not.]
Triple Slash (BA / OBP / SLG): Showing all three stats like this gives a quick picture at the hitter's skills. .300/.340/.370 is a Juan Pierre type hitter; .240/.380/.500 is a Adam Dunn type; .260/.310/.480 is a Mike Jacobs type; and so on.
Isolated Power (ISO): It's SLG minus BA, and gives an idea of how much power a player has by looking at the number of extra bases per at bat. A guy can have a SLG of .450 as a product of hitting .350 with a lot of singles and only a little bit of power (.100 ISO), or he can hit .250 with a lot of doubles/triples/homers (.200 ISO). League average is around .150. [Baseball Prospectus has a modified version of ISO that counts triples the same as doubles, since stretching a double into a triple is more a product of speed than power.]
ISO: [.215 and above is good; .110 and below is not.]
On-Base Plus Slugging Percentage (OPS): While not completely, OPS does a great job of quickly giving a player's total offensive contributions. High OPS means a player is good in both areas of getting on base and advancement, or exceptional at one of the two. It does weight OBP and SLG the same, which is an issue.
OPS: [.800 and above is good; .700 and below is not.]
OPS+: The "+" indicates that the player's OPS has been adjusted for context (their home park, for example) and then compared to the rest of the league. An OPS+ of 100 indicates league average. An OPS+ of 110 means a players adjusted OPS is 10% above league average. This allows players from different eras (when pitching was dominant vs. when hitters had the upper hand) by comparing them to everyone they played with. It still has the same weighting issue as OPS.
Walks, or Base on Balls (BB): A player with a good walk rate can maintain a high OBP even when his BA is low (whether because of ability or bad luck). As mentioned with OBP, patience and pitch-recognition are valuable all the time, not just when taking a base on balls. BB% is the rate at which a player walks.
BB%: [12% and above is good; 7% and below is not.]
Strike-Outs (K): In general, a K is just like any other out. Players who K a lot can still be very productive hitters. A high K rate does make it harder to have a high BA as there are less balls being put in play that can result in hits. Also, a K does not help advance runners, whereas a ground ball can (though it can result in a double play also - one out is bad; two is much worse). For younger players a high K rate could indicate a problem in their swing (can't handle inside pitches, for example), poor pitch recognition (swings at breaking balls in the dirt), or a propensity to swing for the fences (which tends to show up in how often they pull the ball also). These things can keep a player from having success at the major league level if they aren't corrected. K% is the rate at which a player strikes out.
K%: [13% and below is good; 23% and above is not.]
Stolen Bases (SB): Stealing bases at a rate below 70% actually costs a team runs. When looking at the value of having a player (starting at first base with none out) at second with none out or on the bench with one out, being caught has a change in magnitude (of expected run scoring) 70% larger than being safe. This can be found by looking at a run expectancy matrix. For 2005 it looked like this:
OUTS
RUNNERS 0 1 2
--- 0.5165 0.2796 0.1075
1-- 0.8968 0.5487 0.2370
-2- 1.1385 0.6911 0.3502
12- 1.4693 0.9143 0.4433
--3 1.5120 0.9795 0.3718
1-3 1.8228 1.1830 0.4931
-23 2.0363 1.4144 0.6073
123 2.3109 1.5279 0.7485
So with a runner on first and no outs, a team from 2005 scored an average of 0.8968 runs. (These values tend to be pretty close in recent years. In 2006 it might have been .9001 runs or something like that.) Having the runner steal second successfully will result in E(R) going up by 0.2417 to 1.1385. If he is caught, it goes down by 0.6172 to 0.2796. Therefore a player needed to be successful 71.9% of the time (0.6172 / [0.6172 + 0.2417] ) for it to be worth it. [It's actually been more like 74% recently.] Guys that are gooding at stealing bases help their team by running selectively; guys that aren't good at stealing bases should usually stay put (even if they're fast).
Runs (R) and Runs Batted In (RBI): I mention these as they give an idea of how a hitter is doing, even though they say very little about his actual abilities. Not particularly good hitters can have 100 RBI (Jay Gibbons) or score 100 runs (Juan Pierre) almost entirely because of opportunities they get. Jay Gibbons hit 4th and had many chances to hit with men on base. Juan Pierre bats first and so gets on base more times than other hitters (even though his OBP is lower) and so has more chances to have someone drive him in. They are very team dependent stats, and tell you little about a player's value.
Weighted On-Base Average (wOBA): It combines OBP and SLG basically using linear weights.
The nice thing about baseball is that everything that happens on the field has happened that way hundreds of times before (in a non-context dependent sense - a single to right; not a player's 3000th hit on a single to right). That means we can look and see how much any given event helps a team score runs. For example, on average, a double increases a team's expected runs scored by about 1.08 (relative to making an out). For a walk it's about 0.62 runs. Linear weights multiplies the value of each event by how many of them a player accumulated. Tom Tango (and co.) took these values for a bunch of stats, scaled them to OBP, and then divided by plate appearance to get a rate stat. That way, wOBA is on the same scale as OBP (since they're linear), so a wOBA of .340 is about average. Expect it gives a more complete measure of offensive prodiction.
wOBA: [.370 and above is good; .300 and below is not.]
Pitching:
Hits Allowed (H): This can give some idea of the effectiveness of a pitcher, but just like BA for offense it is also dependent on luck, as well as a team's defense. A pitcher with a high BABIP against is giving up more hits than he should (the BABIP should be compared to the team average, not the league as this normalizes it for the defense he pitches in front of). A pitcher who has a good season based on giving up few hits while having a very low BABIP should be expected to regress in the future. Some pitchers, through deception or pitch selection or what have you, have been able to keep their BABIP lower than would be expected (by giving up less line drives, generally). Thus, it is a good idea to look at career BABIP also.
BABIP: [.275 and below is good; .325 and above is not.]
Walks, or Base on Balls (BB): A pitcher with high walk totals is not only going to allow more men on base, he is usually going to be less effective when not walking guys and he'll have to throw more pitches (and thus pitch less innings). Pitchers whose pitches are not very effective themselves (they have bad "stuff") need to limit their walk rate (BB/9 - walks per nine innings pitched) to be able to have success at the major league level. A high BB/9 will not doom a pitcher, but it makes the margin for error in other parts of his game very small. If a guy can't get on base he can't score.
BB/9: [2.5 and below is good; 4.5 and above is not.]
Strike-Outs (K): Every batter that a pitcher K's is one that can't get a hit. A high K rate (K/9) means a pitcher is being successful more often than not, and a low K rate means that a pitcher is in trouble without some other saving grace. Like BB/9, a bad K/9 can be made up for - it requires very good control (low BB/9) or the ability to get ground balls (to prevent extra-base hits). Many sinker-ball pitchers have low K/9 but are still successful - it is just a fine line that they walk with their control and infield defense being very important.
K/9: [7.5 and above is good; 5.5 and below is not.]
Walks and Hits per Inning Pitched (WHIP): This is a quick way to see how many runners a pitcher is allowing. Don't give up hits and don't walk guys, and it makes it tough for the opposition to score.
WHIP: [1.20 and below is good; 1.40 and above is not.]
Home Runs (HR): A pitcher who gives up a lot of home runs will, in general (Johan Santana seems to be doing OK), give up a lot of runs. Keeping the ball in the park forces a team to put together strings of hits (and walks) to score runs, which is much more difficult. This is park dependent though, as giving up 1 HR/9 at the Cell in Chicago is very different from giving up 1 HR/9 in Petco.
HR/9: [0.70 and below is good; 1.35 and above is not.]
Ground Ball Percentage (GB%): You can't hit a grounder for a HR, so it helps in that respect. All extra base hits are less frequent on groundballs, in fact. It results in more outs than line drives, and also more double plays. Brandon Webb would appreciate having a good defensive infield behind him.
Earned Run Average (ERA): ERA is dependent on luck - not only how many hits a pitcher gives up but their distribution. Also, the earned run vs. unearned run disparity doesn't make that much sense anymore and so it isn't even a good measure of how many runs a pitcher gives up. Another problem occurs when relief pitchers allow runners a starter puts on to score. It is park and defense dependent and generally not very useful for saying much about a pitcher's abilities. It does give a general idea though.
ERA: [3.50 and below is good; 5.00 and above is not.]
ERA+: Like OPS+, this adjusts ERA for home park, and compares it to the league average.
Feilding Independent Pitching (FIP): Looks at the things a pitcher controls more directly (strike-outs, walks, and home runs) and scales it to ERA. It takes out a lot of the luck from balls in play (though not flukey HR rates - there's xFIP which gives expected FIP given a regressed HR rate).
FIP: [3.50 and below is good; 5.00 and above is not.]
tRA: "Developed by Graham MacAree... tRA involves assigning run and out values to all events under a pitcher's control and coming up with an expected number of runs allowed and outs generated in a defense and park neutral environment. tRA is on a R/9 scale and does not involve any regression of the rates so while it should be more useful at determining a pitcher's true talent level, the best method for pitching projection is to use tRA*, the regressed version of tRA." - StatCorner.com
tRA is calculated in a manner similar to wOBA in that it assigns run values to different events (a K saves about 0.11 runs, while a BB costs about 0.33 runs, a line drive allowed costs about 0.38 runs, and so on). Then the number of runs a pitcher is expected to give up is divided by the numbers of outs he is expected to get, and then multiplied by 27 to give the expected numbers of runs allowed per 9 innings. So one can think of it kind of like ERA (except without the whole earned/unearned thing so it's about 8% higher).
tRA: [3.75 and below is good; 5.50 and above is not.]
tRA+: Adjusted tRA, like OPS+ and ERA+.
FanGraphs also has info. on what pitches a guy throws, how often he throws them, and their velocity. And - for both pitchers and hitters - the percent of pitches thrown in and out of the strike zone; the percent (also split out) that are swung at; and the contact rate (also split out). They are putting out a ton of useful stats.
Defense:
This is the part of the game where the usefullness of stats is still catching up. There are a lot of places to go to get data regarding defensive value, including Plus/Minus from the Fielding Bible; Ultimate Zone Rating (plus arm and double play turning stats) from FanGraphs; the Probablistic Model of Range from BaseballMusings; the Fans' Scouting Reports complied by Tom Tango at TheBook; and a whole host of other sources. Read more ...
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