SB Nation User Blog: 5Tool

Anderson's Step Forward - Dave Cameron (Fangraphs)

5Tool — Fri, 28 Aug 2009 01:40:51 -0000

Anderson's Step Forward - Dave Cameron (Fangraphs)

I'm not sure if this has been posted already, but here is a quick analysis of Brett Anderson's current success.

Old Rajai, new success?

5Tool — Sun, 09 Aug 2009 16:55:47 -0000

I'm not sure how useful this is, but if anyone was wondering what the odds were of the "Old Rajai" batting as well as he is now without having improved at all, but by just being lucky, I did some quick math.

Assuming he is a .265 batter (his career BA) then there is a 5.6% chance he would have at least 20 hits over the 57 AB's since the break.

Assuming he is a .288 batter (his '09 BA thus far) there is an 11.7% chance.

Assuming he is a .257 batter (his first half BA) there is a 4.1% chance.

They way I calculated this was based on his pre-game, 8/08/09 BA, versus various other past performances. I used BA because that is binomial (hit or out) and thus much easier to calculate. Luckily, Rajai's batting average has increased by nearly the same degree as his OPS (1.37 vs 1.36) so this crude formula should do the trick. As for the math, I am using the binomcdf formula on TI calculators, subtracted from 1.

Things to keep in mind:

This does not factor in his increased SLG which has increased nearly 50%.

Nor does it account for his improved number of walks, which I considered counting as hits, but decided not to.

The percentages above represent his probability of having a .351 or greater BA and thus is greater than his probability of having exactly a .351 BA.

In general, if something occurs at a rate less than 5% it is considered unlikely.

In general, 50 independant events is sufficient to draw conclusions from, we are working with 57 AB's, and it is debatably if these are truly independant events or if streakyness is a factor, due to increased confidence, for example.

His July and August BA is better than his 2nd half BA and includes more AB's, so it may be more useful, although I thought that there might be something more significant about doing it this way because of the break.

This is post is not meant to discount Rajai's 2nd half achievements in anyway, I was just curious, and thought others might be too.

Embree gets pitch-less win

5Tool — Wed, 08 Jul 2009 17:18:56 -0000

Embree gets pitch-less win

Just thought this was amusing. Alan Embree gets credited for the win against the Nationals without ever throwing a pitch.

SLG and Speed

5Tool — Fri, 03 Jul 2009 03:06:19 -0000

Who would you rather have in your lineup, a fast player who can extend many a single to a double or a slow player, who regardless, has a the same SLG as the fast player?

The first player cannot advance runners as well, but is more easily advanced. The second player advances runners well, but cannot be advanced as easily.

Obviously one would be a better clean up hitter and the other a lead off hitter, but for the moment my question is, who do you think is worth more runs per game assuming you have 8 other average batters on the team? Offense only please.

Let's end OPS

5Tool — Thu, 02 Jul 2009 17:11:51 -0000

With all of the talk of the fast approaching trade-deadline everyone is starting to compare our players with other players in the hopes of acquiring some new talent ,and that's great. However, the way in which it is being done seams mostly based around comparing OPS, for batters at least, and quite frankly, OPS is dumb. Sure its better than batting average, and sure it takes the two most important components of hitting, how often you a batter reaches base, and how many they reach in the process, but it is very sloppy and has two major problems:

Slugging percentage is inappropriately weighted in terms of their actual run values for singles, doubles, triples...
As mentioned in Moneyball, OBP gets much less credit than it deserves as OPS is dominated by slugging percentage. (OBP should be doubled for OPS to be more accurate.)

Basically, OPS is flawed. It doesn't inherently mean anything, it's just two stats put together. It's not terrible, but why use a statistic you know is wrong? And certainly, when you're trying to predict the moves of Beane, it is foolish to use a statistic that he said was wrong back in 2004. I know its nice using a statistic that everyone already knows, but thats what they said about batting average. If its any indication at all that OPS is outdated, just look at the media, even they are using it.

So, what should be used instead? There are tons of statistics to choose from and they all have their reasons, but for everyone who wants a simple transition out of OPS, wOBA is basically a properly tuned version of OPS, and for convenience sake, it is pegged to OBP, so if you're wondering what a good wOBA is, well, its the same scale of OBP so you don't have to explain what the number means.

A's Offensive Woes

5Tool — Tue, 19 May 2009 03:54:53 -0000

I am an A's fan, but this season has been impossible to watch. The offense, which was supposed to be the backbone of the team has been underpreforming epically.

OPS wise, the offensive numbers are as follows from 2008-2009 for the nine most frequently batting players this season:

Ryan Sweeney: 733-643

Kurt Suzuki: 716-828

Jack Cust: 851-794

Bobby Crosby: 645-664

Mark Ellis: 694-503

Orlando Cabrera: 705-584

Jason Giambi: 875-659

Matt Holliday: 947-734

Travis Buck: 723- 545

That's a net loss of 944 between last year and this year, or an average of 104.8 a player, it's like the team gave away an all-star DH. Obviously certain players could have been predicted to preform worse from last year to this year such as Jason Giambi and Matt Holliday, but could a drop of 216/213 OPS really have been predicted, or is Billy Beane loosing his edge?

Anyway, I just wanted to see if anybody thought that this is just some beginning of the season underproduction or if this catastrophe of an offense could have been avoided.

Evaluating BA and OPS

5Tool — Thu, 09 Apr 2009 20:02:38 -0000

I recently checked around the internet to find mathematical evaluations of team Batting Average and On-base percentage plus slugging percentage in determining team run totals, to no avail, so I figured I would do it myself. Because of time constraints I only pooled two seasons of data, 2004 and 2008, but that is more than the minimum 30 required to do the test. I started by finding the linear regression of both BA and OPS as dependents against runs:

'04 BA vs Runs:

Regression Line= -417+4422X R=.869 R^2=.475

'08 BA vs Runs:

Regression Line= -1049+6873.786X R=.803 R^2=.646

'04 OPS vs Runs:

Regression Line= -986+2315X R=.971 R^2= .943

'08 OPS vs Runs:

Regression Line= -730+19971X R=.948 R^2=.898

Totals: BA R=.746 BA R^2=.561; OPS R=.96 OPS R^2=.921

* Because I did this on my calculator and not on Excel I don't have the graphs available to show, sorry.

From here, we can easily see that although BA does predict runs, it is not nearly as significant as OPS which does so at an outstanding rate.

If we were to use hypothesis testing to evaluate this claim we would find that the Test statistic for BA is 8.861 compared to 26.894 for OPS, both over the approximately 2 critical point, causing us to fail to reject both, although showing how much more confident we can be in OPS as a predictor.

In conclusion, it is my analysis that although batting average does have a correlation with runs it is not a particularly strong one, especially compared to OPS which, at least in 2004 and 2008 had a very strong correlation to runs produced.