Things I've learned about myself while playing OOTP

[RchW]

Originally Posted by Déjà Bru

Why 13, 3, and 2? Can you explain that succinctly or do you just accept those numbers because an expert told you to? So, "constant" is not constant but is "generally" something that in itself relies upon previous calculations of the same statistic. And you wonder why you miss the "subjective" part?

Wolf, Josh, enjoy the game. Thank goodness it provides stats for all of us.

It's not complicated at all. Definitely not subjective with respect to comparing players to each other. The 13, 3 , and 2 are not constants but factors that allow the calculation to produce a number that is usable in the range of ERA. The ERA scale is familiar to baseball fans so it's helpful to use a number that has a familiar range. Factors are used in mathematics and data entry all the time. I hate typing decimal points so I always use whole numbers in my head or in excel so that 1.048 is 1048 and then apply the decimal at the end of any calculation. Let me give you an example FIP calc.

Consider R A Dickey. in 2013 he pitched 224 innings allowed 35 HR gave up 81 BB plus HBP and struck out 177.

So 13 X HR = 455, 3 X BBHBP = 243 and 2 X K = 354

455+243-354 = 344

344/224 = 1.535714285714286 or 1.536. This is rFIP or raw FIP

That number means very little due to the scale and even less when comparing pitchers to each other, so each year a cFIP (the constant) is derived by calculating rFIP on MLB totals for HR BB HPB and K and subtracting that from league average ERA

In 2013 MLB rFIP is 0.818 and the league average ERA is 3.87.

So 3.87 - 0.818 = 3.052 which is cFIP for 2013 MLB. Since this is directly related to league ERA there is nothing subjective about it.

Take = Dickey's rFIP + cFIP 1.536 + 3.052 = 4.588 which is his FIP for 2013. That number makes sense because it sits in a familiar ERA scale. We know it's not very good especially when we compare it to the leaders at 2.39. It also matches much closer to his career FIP vs the 3 good years he had at Citi field.

The key points are;

Using factors to produce a usable number via calculation is perfectly fine. This is not subjective

The constant used is not just plucked from the aether but calculated as a raw FIP result and derived from league average ERA. This is not subjective

FIP occupies the same general scale as ERA which makes comparing players very easy.

Since the raw FIP is calculated the same way for each player the raw data is not subjective.

The factors and constant are the same for each calculation ergo, not subjective.

[The Wolf]

And, in case you think that MLB teams don't use FIP over ERA, read this:

Cameron: Tim Lincecum and the slow death of ERA | SABR

Yes, I'm being sneaky. I want you all to read it.

[Le Grande Orange]

Originally Posted by The Wolf

Why do I suddenly suspect you of SABR membership?

I was a member for a couple of years, though I never delved into the player statistics side of things. Haven't been a member for quite a few years now, though I do hope to return as a member eventually (there are a number of perks that come with membership that can be quite worthwhile).

[The Game]

Originally Posted by The Wolf

Learn how to use wOBA, WRC+, WAR and FIP/xFIP to evaluate players and you will better understand baseball. In OOTP that translates to better player transactions and winning more often.

I can use dinosaur stats and still win. Did Oakland win the World Series? Boston sure didn't use sabermetrics when starting Gomez.
If a pitchers ERA is low so will his FIP. If a players Average is high so will his OBP. OBP hurts the middle IF with no power. WAR is a junk stat since no one ever has told me who the replacement player is and what he can hit. Konnerko's WAR last year was Owar -1.1 and Dwar -1.3 Dunn is the backup 1B is he better offensively then Paulie? and we know he is worse defensively. Not every replacement player is a minor league or some scrub FA.
No one has yet to provide actual proof that the sabremetrics translate into more wins then what you call dinosaur stats.

[Pdubya64]

Originally Posted by The Game

No one has yet to provide actual proof that the sabremetrics translate into more wins then what you call dinosaur stats.

While sabermetrics may not be directly translatable to wins for a team, they are still an improvement over traditional stats in attempting to "crack" the inner code of Baseball. We are on a long path started by James and McCracken to try and understand and penetrate the mysteries of the sport. Statistics by their nature are descriptions of behavior couched in averages, medians and other approximations of a set of data. The correlations may be indirect, but I believe that we are getting closer every year to a set of tools that enable teams to field the players who give them the best chance to win every game. Once that's done it is up to the players to perform to the best of their ability.

In a nutshell, I think today's tools are better indicators of behavior and trends. It's a bit like herding cats, but although the benefit may be small in scale, it is none the less an improvement over the original set of Baseball statistics.

[The Game]

Originally Posted by Pdubya64

While sabremetrics may not be directly translatable to wins for a team, they are still an improvement over traditional stats in attempting to "crack" the inner code of Baseball. We are on a long path started by James and McCracken to try and understand and penetrate the mysteries of the sport. Statistics by their nature are descriptions of behavior couched in averages, medians and other approximations of a set of data. The correlations may be indirect, but I believe that we are getting closer every year to a set of tools that enable teams to field the players who give them the best chance to win every game. Once that's done it is up to the players to perform to the best of their ability.

In a nutshell, I think today's tools are better indicators of behavior and trends. It's a bit like herding cats, but although the benefit may be small in scale, it is none the less an improvement over the original set of Baseball statistics.

Best explanation I have ever heard.

[The Wolf]

Originally Posted by The Game

I can use dinosaur stats and still win. Did Oakland win the World Series? Boston sure didn't use sabermetrics when starting Gomez.
If a pitchers ERA is low so will his FIP. If a players Average is high so will his OBP. OBP hurts the middle IF with no power. WAR is a junk stat since no one ever has told me who the replacement player is and what he can hit. Konnerko's WAR last year was Owar -1.1 and Dwar -1.3 Dunn is the backup 1B is he better offensively then Paulie? and we know he is worse defensively. Not every replacement player is a minor league or some scrub FA.
No one has yet to provide actual proof that the sabremetrics translate into more wins then what you call dinosaur stats.

I'm not going to get in a fight with you, but yes, that has been proved in the MLB, and you're pretty ignorant on the subject, and almost everything you wrote was either wrong or misleading. Stick to things that you know.

[The Wolf]

The fully sabermetric teams: Boston, Oakland, Tampa Bay, and just now Houston. Oakland has Beane et al, Boston has Bill James and Tom Tippett - who used to be one of Markus's rivals with Diamond Mind Baseball - and Houston has just hired their third new sabermetrician (from Baseball Prospectus). The smarter MLB teams are using sabremetrics to understand more, make better decisions, and to win more games. You can do this as well.

Yes, you can win with dinosaur stats. But you can win MORE with modern ones, and that's the point.

[Pdubya64]

Wolf, I was listening to the latest "Behind the Dish" podcast with Keith Law at work the other day. He had Eric Karabell on as guest and one of the things they mentioned as Eric is a Phillies fan is that the Phillies finally hired a sabermetrics analyst recently.

Of course, Law immediately pointed out that while good that they finally got on the merry-go-round, it doesn't necessarily mean the front office will actually listen to them. Still, it's a win for the advance of sabermetrics that the last bastion of "old school" baseball caved.

P.S. Go easy on these guys, eh? Some people are slow to embrace change. Thanks for all the great links by the way!

[The Wolf]

Change is hard, and some people just resist it out of stubbornness and a refusal to leave their comfort zone. But the MLB, that most conservative of things, is adopting sabremetrics, which should serve as the writing on the wall.

[Pdubya64]

Originally Posted by The Wolf

The fully sabermetric teams: Boston, Oakland, Tampa Bay, and just now Houston. Oakland has Beane et al, Boston has Bill James and Tom Tippett - who used to be one of Markus's rivals with Diamond Mind Baseball - and Houston has just hired their third new sabermetrician (from Baseball Prospectus). The smarter MLB teams are using sabremetrics to understand more, make better decisions, and to win more games. You can do this as well.

Yes, you can win with dinosaur stats. But you can win MORE with modern ones, and that's the point.

The other thing is as Beane pointed out, the proverbial sabermetrics cat has been out of the bag for a number of years now. Teams are always looking for that edge to help win. That's why the whole substance on Lester's glove article got no traction. As long as you are discrete... anything goes.

Seems to me the next frontier in baseball is what the Cardinals under GM John Mozeliak are doing a bit better than Oakland and Tampa Bay. Namely, build from within, combine sabermetrics with scouts intuition and calculated risk assessment (see Trevor Rosenthal, converted IF signed for $1000) and shop players past their prime while they are still worth enough to garner additional prospects or at least a compensatory pick.

Some teams like the Dodgers and Yankees will still spend ludicrous money because they have it, but to me it feels like the rest of the league looks at Boston, Oakland, St. Louis, Tampa Bay and Pittsburgh and wonder if they can make it work for them. *Oh, and pretty soon the Old Guard will be in the ground and the league will become Sabermetrics dominated due to the people in positions of authority.

Exciting times indeed!

[The Wolf]

Exciting times indeed. When Baseball Prospectus, which used to be the absolute cutting edge of sabermetrics online, suddenly can't keep its writing staff because they are being hired by the MLB, it's definitely exciting times.

[themonk]

I'm not really much of an expert like many of you are, guys, since I've only learned baseball and OOTP 4 years ago. But my 2 cents worth of opinion, especially after reading "Moneyball," is that MLB teams should start paying attention to sabermetrics. Otherwise, they'll end up as dinosaurs...

[The Game]

Originally Posted by themonk

I'm not really much of an expert like many of you are, guys, since I've only learned baseball and OOTP 4 years ago. But my 2 cents worth of opinion, especially after reading "Moneyball," is that MLB teams should start paying attention to sabermetrics. Otherwise, they'll end up as dinosaurs...

Teams can still win using dinosaur stats. The sabermetric stats still are bad if the player has a high ERA, low BB, low avg, low OBP. They are good if the pitcher has high wins, low ERA, high avg, high RBI. Look at the top 5 players in WAR there stats are good across the board. look at the top 5 worst players in WAR there stats are bad across the board. No bad player is going to have a low FIP or isn't going to be good in some some other sabermetric stat.

[pjh5165]

Originally Posted by The Game

Teams can still win using dinosaur stats. The sabermetric stats still are bad if the player has a high ERA, low BB, low avg, low OBP. They are good if the pitcher has high wins, low ERA, high avg, high RBI. Look at the top 5 players in WAR there stats are good across the board. look at the top 5 worst players in WAR there stats are bad across the board. No bad player is going to have a low FIP or isn't going to be good in some some other sabermetric stat.

This is true to an extent, but that isn't really the point of sabermetrics. The biggest way I see sabr stats being useful is prediction of improvement and regression. Just look at some of the 2012 ERA leaders and their FIP.

Wainwright - 3.94 ERA 3.10 FIP
Scherzer - 3.74 ERA, 3.27 FIP
Darvish - 3.90 ERA, 3.29 FIP
Cain - 2.79 ERA, 3.40 FIP
Dickey - 2.73 ERA, 3.27 FIP
Lohse - 2.86 ERA, 3.51 FIP

Granted it's not a big sample size, but just look at how these compare to their 2013 seasons.

Wainwright, Scherzer, and Darvish improved while Cain, Dickey, and Lohse fell off. It's not a huge difference, but sabermetric stats are far more useful than dinosaur stats for predicting how luck is affecting proven players like the ones above and for figuring out what to expect from them in the future.

[The Wolf]

Originally Posted by The Game

Teams can still win using dinosaur stats. The sabermetric stats still are bad if the player has a high ERA, low BB, low avg, low OBP. They are good if the pitcher has high wins, low ERA, high avg, high RBI. Look at the top 5 players in WAR there stats are good across the board. look at the top 5 worst players in WAR there stats are bad across the board. No bad player is going to have a low FIP or isn't going to be good in some some other sabermetric stat.

Go read through the links I posted and learn better.

[cephasjames]

Originally Posted by Déjà Bru

As much as I think I would like developing a fictional league along historical MLB lines, I find that approach to be tedious in maintaining logos and uniforms, financials and strategy, etc.

It is. While I do this, I have "goofed" it up many times and started over many times. My biggest dream about this game now is to be able to create a programmed pre-planned history that plays out all on it's own like the game currently does with the MLB. I would spend hours and hours working on that XML document that would allow that to happen.

Originally Posted by Bluenoser

the thing that brought this game to life for me, is FaceGen and the Uni/Logo flexibility.

When I could actually look at fictional players and give teams cool logos and unis was when immersion went to a whole new level.

When FaceGen was added this game became so much more than it had ever been. To be able to see the faces of the players is such a big part of what I love about this game.

Originally Posted by Hockey13Playa

This is an awesomeeeeee thread.

I agree!

[The Game]

Originally Posted by pjh5165

This is true to an extent, but that isn't really the point of sabermetrics. The biggest way I see sabr stats being useful is prediction of improvement and regression. Just look at some of the 2012 ERA leaders and their FIP.

Wainwright - 3.94 ERA 3.10 FIP
Scherzer - 3.74 ERA, 3.27 FIP
Darvish - 3.90 ERA, 3.29 FIP
Cain - 2.79 ERA, 3.40 FIP
Dickey - 2.73 ERA, 3.27 FIP
Lohse - 2.86 ERA, 3.51 FIP

Granted it's not a big sample size, but just look at how these compare to their 2013 seasons.

Wainwright, Scherzer, and Darvish improved while Cain, Dickey, and Lohse fell off. It's not a huge difference, but sabermetric stats are far more useful than dinosaur stats for predicting how luck is affecting proven players like the ones above and for figuring out what to expect from them in the future.

Cain's FIP last 3 seasons 3.93, 3.40, 2.91 So he should have done better after 2011 not gotten worse.
Dickey 4.58, 3.27 3.77 shouldn't he have gotten worse after 2011 and not won 20 game with a 2.71 ERA in 2012?
Lohse 4.08, 3.51, 3.67 well he just sucks anyway.
Dickey & Lohse both went to bad teams in 2013. FIP is a crapshoot.
Scherzer had a 4.14 FIP in 2011 and improved the next 2 seasons how do you explain that? His BB/9 & BABIP both went up in 2012. K/9 & GB% both went down in 2012. Explain Wolf.
Yu has been pretty consistent across the board in his 3 seasons in all categories.

[The Wolf]

Originally Posted by The Game

Cain's FIP last 3 seasons 3.93, 3.40, 2.91 So he should have done better after 2011 not gotten worse.
Dickey 4.58, 3.27 3.77 shouldn't he have gotten worse after 2011 and not won 20 game with a 2.71 ERA in 2012?
Lohse 4.08, 3.51, 3.67 well he just sucks anyway.
Dickey & Lohse both went to bad teams in 2013. FIP is a crapshoot.
Scherzer had a 4.14 FIP in 2011 and improved the next 2 seasons how do you explain that? His BB/9 & BABIP both went up in 2012. K/9 & GB% both went down in 2012. Explain Wolf.
Yu has been pretty consistent across the board in his 3 seasons in all categories.

Go read and learn. Come back when you understand about what statistics correlate year to year and how much and which ones are better predictors. Also pay particular attention to outliers.

[pjh5165]

Originally Posted by The Game

Cain's FIP last 3 seasons 3.93, 3.40, 2.91 So he should have done better after 2011 not gotten worse.

Cain 2011 - 2.88 ERA, 2.91 FIP
Cain 2012 - 2.79 ERA, 3.40 FIP
Cain 2013 - 4.00 ERA, 3.93 FIP

He had a great year in 2011, no doubt. What I'm saying is that after 2012, he looked like a great pitcher on the surface with back to back ERAs of 2.88 and 2.79. Looking deeper at the FIP, however, shows that Cain actually regressed between the 2011 and 2012 season, so there were warning signs that he would not continue to pitch in the 2.75-3.00 ERA range. And he didn't.

Originally Posted by The Game

Dickey 4.58, 3.27 3.77 shouldn't he have gotten worse after 2011 and not won 20 game with a 2.71 ERA in 2012?

Looking at Dickey's stats, he has consistently outpitched his FIP through his career. I'm not even going to say that sabr could have predicted his great 2012 season or him falling off a cliff in 2013, although his 3.27 FIP in 2012 showed that his 2.73 ERA was reasonably lucky.

Originally Posted by The Game

Lohse 4.08, 3.51, 3.67 well he just sucks anyway.
Dickey & Lohse both went to bad teams in 2013. FIP is a crapshoot.

Lohse's last 3 FIPs show that he is around a 3.65 or 3.75 ERA pitcher. He posted a 3.35 ERA this year (still lucky) which is a pretty good amount higher than his 2.86 in 2012.

Originally Posted by The Game

Scherzer had a 4.14 FIP in 2011 and improved the next 2 seasons how do you explain that? His BB/9 & BABIP both went up in 2012. K/9 & GB% both went down in 2012. Explain Wolf.

I think Scherzer just became a better pitcher, and then added that cutter in 2013. He may not be the best example I could have chosen.