NL Central Run Differental 2001-2008

[nate]

I guess the crash ate my post because I had more pictures. Here's a re-run:

http://www.gluethemoose.com/neen/redszone/RunDif2005-2008.png

This is the run differential for all NL Central teams from this decade. Run differential is runs scored minus runs allowed. Negative numbers are bad, mmm-kay? Notice two teams consistently below the line? Notice also a basically straight line for the Reds in the -110-ish to the -100?

Hey, at least we're not the Pirates! Everyone else, however, is on the smiling side of zero.

Here are the runs scored over the same amount of time:

http://www.gluethemoose.com/neen/redszone/RunsScored2001-2008.png

Another kind of 710-ish straight line for the Redlegs. The Astros seem to have lost some offense but the Pirates, Brewers and sadly, the Baby Bears have all gained some. The Cards are about the same.

Here are runs allowed:

http://www.gluethemoose.com/neen/redszone/RunsAllowed2001-2008.png

In this case, it's better to be lower on the scale and the Reds have trended slightly down. I think this would confirm that the pitching staff, while not great, is slightly better. The Brewers seem to have improved the most while the Pirates are 2003-2004 Reds bad.

So, seeing these charts and the teams that the Reds play most of their games against, what do you think? It seems to me that a few years ago, the NL Central was kind of a joke division but now you have 3 teams well above a zero run differential and 2 teams well below. It doesn't seem like the Reds have kept up with the Joneses.

[Scrap Irony]

Last season means little this season.

[TRF]

Last season means little this season.

huh?

Except for the fact that the teams biggest run producer is gone, most of the team is exactly the same.

Same infield. Same rotation. Pretty much the same bullpen.

New catcher, CF, and LF.

Those who learn nothing from the past are doomed to repeat it. Or something to that effect. A more modern version would be "Same as it ever was."

[Scrap Irony]

Yep, you're right. Too harsh.

However, two of eight starters are completely new, not to mention a possible fourth in LF and a possible fourth at SS. Two others are rookies. So, really, that makes two offensive players you can forecast fairly acurately from a total of eight and both of those happen to be failry volatile players to predict.

Three starters were brand new last season, meanwhile, with two of those extremely difficult to predict this early in their career. Another two year player will likely join the rotation this season, making them even more difficult to discern. Both Harang and Arroyo have shown propensities for volatile shifts in their numbers, so they, too, are hard to figure.

I do understand the Reds have sucked for the better part of a decade now. I see the trend. But past numbers mean little to a team as young and inexperienced as this one.

Too, Milwaukee has changed dramatically from the past eight years or so and Houston is in the middle of a huge paradigm shift. Neither squad is a good bet to be anything like past squads.

[nate]

Yep, you're right. Too harsh.

However, two of eight starters are completely new, not to mention a possible fourth in LF and a possible fourth at SS. Two others are rookies. So, really, that makes two offensive players you can forecast fairly acurately from a total of eight and both of those happen to be failry volatile players to predict.

Three starters were brand new last season, meanwhile, with two of those extremely difficult to predict this early in their career. Another two year player will likely join the rotation this season, making them even more difficult to discern. Both Harang and Arroyo have shown propensities for volatile shifts in their numbers, so they, too, are hard to figure.

I do understand the Reds have sucked for the better part of a decade now. I see the trend. But past numbers mean little to a team as young and inexperienced as this one.

Too, Milwaukee has changed dramatically from the past eight years or so and Houston is in the middle of a huge paradigm shift. Neither squad is a good bet to be anything like past squads.

So how do you predict the "lines" to look after this season?

Especially the first one.

[Scrap Irony]

Dunno. Depends on what Jocketty does the rest of the off-season. I'm pretty certain the pitching will be much better this season, as the trio of Harang, Arroyo, and Cueto should all see significant bumps, assuming each is healthy. The fifth starter, too, should be much improved. (I really like Owings at this point and think he's a fine low-end starter.)

The bullpen is a crapshoot. It could be great and could struggle big time. Like almost any pen in baseball, really.

Defensively, they will be improved, but how much improvement remains to be seen. I do think the OF D is going to be well above average and that will help the pitchers a great deal. Having two statues flanking Bruce or even Patterson was simply not a good idea. The years previous, with Junior in center and Dunn in LF were even worse, if possible. I'm looking forward to seeing a team with solid leather across the OF. The IF, meh. Encarnacion is a butcher, as is either Hairston or Keppinger. But all three could hit enough that it becomes acceptable. (125 OPS+ is the barometer, IMO, for that.) Phillips is fun to watch defensively and Votto is underrated by most of the board. Overall, the Reds are about average defensively, IMO, and could be much better than that.

Offensively, I think the Reds will score about as many as they did last season, at this point. Losing Dunn kills an offense, but the quartet of Bruce, EdE, Phillips, and Votto could all see significant jumps in their numbers, lessening the impact of his departure. I do expect Keppinger to bounce back a bit, but both Dickerson and Hairston will fall back to earth and hang out under the 100 OPS+ line with Taveras. If Jocketty can find a good LF (or platoons Dickerson and, say, Hinske in that spot), we may be pleasantly surprised with this squad.

[nate]

we may be pleasantly surprised with this squad.

What would make you pleasantly surprised?

[WMR]

Last season means little this season.

It's actually wonderfully predictive.

[WMR]

What would make you pleasantly surprised?

Career years out of every single scrappy veteran, all of the young guys improving, and EVERYONE staying healthy and we might just sniff the wildcard.

Chances of that happening? ...................... :lol: :laugh:

[Scrap Irony]

It's actually wonderfully predictive.

No, it's really not. While the usual suspects, so to speak, are predictably good year after year, most teams run in cycles that often show little to no warning.

Often, teams with an influx of new or nearly new talent go on a five or six year streak wherein they're competitive within their division or league.

Some commonalities include:

1. Two or three young hitters (re, 1-3 years in league) blossom together, making the leap from god hitters to All Star or near All Star level.
2. Talented TOR pitcher(s) take the next step to become dominant.
3. Free agent signing or trade acquisition allows for perfect storm of veteran leadership and young talent.
4. One Hall of Famer slugger takes a team on his back for a five or six year period, willing them to win, making the team more exciting, attractive to free agents, and acquisitions.

I had planned on making a fairly large post out of this later, probably in March, but, after just a little research, I realized the number of teams this happens to year after year. That's too much for one guy to do. Just over the past decade, for example, we've seen virtually all the mid-market teams and just over 2/3 of the small market teams make at least a three-year run at respectability.

A quick glance at the just the last ten years shows only seven teams haven't enjoyed sustained success. Of those, one (Baltimore), for every intents and purpose, is large market, but horribly mismanaged at the very top.

Another, Washington, is mid-market now, with an outside shot at being a big boy soon, though that certainly remains to be seen. Texas, too, is probably mid-market and could be just starting their run.

The others are smaller markets, with the NL Central's two teams (Cincinnati and Pittsburgh), the AL Central's one (Kansas City), and the AL East's one (Tampa Bay, though obviously the Rays may be in the midst of theirs).

Of the remaining teams, just under a third (7) gave warning of what was to come with some sort of slow incline of improvement. The rest shot up the ladder one year and stayed until their talent got too old, too expensive, or too broken to continue.

[Scrap Irony]

What would make you pleasantly surprised?

As far as finishing within the league or run differential?

The league, second place would make me pretty happy and, IMO, is doable, assuming specific players improve and Jocketty makes a deal or two.

As for run differential, I don't think anyone can answer that until the off-season is over and all deals have been made.

In short, dunno

[*BaseClogger*]

It's actually wonderfully predictive.

MLB 2007 W/L and 2008 W/L have a .25 correlation and .06 correlation squared...

[Scrap Irony]

Which would mean, and correct me if I'm wrong, as I'm an English teacher and Stats class was eons ago, it has some validity, but it's not the end-all, be-all of predictive success.

Too, I'd love to see the numbers, if possble of large market, mid-market, and small market predictions via run differential from season to season. Perhaps see if small market run differential differs more than mid-market which, in turn, differs more than large market.

[pahster]

MLB 2007 W/L and 2008 W/L have a .25 correlation and .06 correlation squared...

Are you talking about R-squared?

[*BaseClogger*]

Which would mean, and correct me if I'm wrong, as I'm an English teacher and Stats class was eons ago, it has some validity, but it's not the end-all, be-all of predictive success.

Too, I'd love to see the numbers, if possble of large market, mid-market, and small market predictions via run differential from season to season. Perhaps see if small market run differential differs more than mid-market which, in turn, differs more than large market.

Nah, close to 1 or -1 would mean strong correlation but near 0 means little relationship...

[*BaseClogger*]

Are you talking about R-squared?

Yeah, my bad it's been a while haha and I couldn't remember what letter it was. R-squared is correlation squared, right?

[WMR]

Maybe not league wide but that wasn't really my point. If you take a team's run differential from a previous season and factor in how many runs their players are likely to create in the current season (making changes for players added and players subtracted), run differential from season to season is an excellent tool towards determining the run differential for a season yet to be played.

[*BaseClogger*]

Maybe not league wide but that wasn't really my point. If you take a team's run differential from a previous season and factor in how many runs their players are likely to create in the current season (making changes for players added and players subtracted), run differential from season to season is an excellent tool towards determining the run differential for a season yet to be played.

But then you aren't purely using last seen to make a prediction, are you?

[pahster]

Yeah, my bad it's been a while haha and I couldn't remember what letter it was. R-squared is correlation squared, right?

R-squared (the coefficient of determination) is an estimator that tells us how much of the variance in the dependent variable is explained by the independent variable(s) in a regression model. r-squared (which is sometimes called squared correlation), on the other hand is a measure of the proportion of variance shared by two variables. The former has predictive power and latter doesn't.

[WMR]

But then you aren't purely using last seen to make a prediction, are you?

Right. I should've been more clear what I was typing about. :p:

[*BaseClogger*]

R-squared (the coefficient of determination) is an estimator that tells us how much of the variance in the dependent variable is explained by the independent variable(s) in a regression model. r-squared (which is sometimes called squared correlation), on the other hand is a measure of the proportion of variance shared by two variables. The former has predictive power and latter doesn't.

Alright, so how would you go about fixing my goof?

[pahster]

Alright, so how would you go about fixing my goof?

I don't remember seeing a goof, I just wasn't sure what you meant by correlation squared.

[*BaseClogger*]

I don't remember seeing a goof, I just wasn't sure what you meant by correlation squared.

Okay but I mean isn't it pretty self-explanatory... it's correlation squared?

[pahster]

Okay but I mean isn't it pretty self-explanatory... it's correlation squared?

Yeah, but it's not something that's normally reported, at least in my field. Squared correlation doesn't really tell us anything useful so I thought maybe you meant R-squared.

[*BaseClogger*]

Yeah, but it's not something that's normally reported, at least in my field. Squared correlation doesn't really tell us anything useful so I thought maybe you meant R-squared.

Gotcha. Now that I've had some time to think about it R-squared is what I was going for, but have forgotten how to calculate. Thanks for clearing things up... :thumbup: