[Updated] tRA Player Cards - Now Taking Requests
by Graham MacAree on Apr 10, 2008 1:57 PM PDT
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PrintI've just set up my spreadsheet to generate player cards from 2007 with a bunch of useful information on them. However, I don't really have a sensible way of actually producing them all for easy viewing, so I thought I'd throw up a thread and ask who everyone wanted to take a look at. I'll start with someone dear to our hearts: King Felix.
(click for a clearer picture)
So, if anyone wants to see a particular player, go for it in the comments and I'll put a player card up. I'm bored of revision.
Note: Although I've done my best to make tRA as accurate as possible, all information has been collected by hand and thus typos are inevitable. If you see a mistake somewhere, please point it out.
Updates: Fixed a little bug in the regression algorithm that seems to be hitting the small sample size-types pretty hard, hasn't affected anyone interesting very much as far as I can tell. I've replaced Excel's automatic percentile ranking with a z-score-->% system which doesn't fit the data -quite- as well but puts the mean on the 50% mark, which I like. Also, BIP% column now in the table, pie chart's a bit bigger, and a sample size indicator is to the right of the first graph. I'm still taking requests, too.
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Here's a question
Are all the percentiles based on descending totals? That is, the 99th percentile pitcher in OFB% is the pitcher who allows the most flyballs right?
What do you think about making a judgment on each stat whether more or less is better and doing percentiles that way?
Here are some answers
the 99th percentile pitcher in OFB% is the pitcher who allows the most flyballs right?
Yep
What do you think about making a judgment on each stat whether more or less is better and doing percentiles that way?
I did consider this.
But then I ran into the batted ball types, and I honestly couldn't decide which way GB and OFB should go. Obviously, GB/FB ratio is important, but it's important for limiting HR more than anything else; straight outfield flies are better for pitchers in terms of runs and outs than ground balls.
After puzzling that over for a while I just decided that a straight descending percentile would be the best way of doing it, and I changed the rest back to be consistent across the board
by Graham MacAree on Apr 10, 2008 2:09 PM PDT up reply actions
Better colors.
What about R. Soriano. Let's see what we missed out on.
...and now I'm here
Huh...
Not as good as I thought, though clearly still awesome. The regression looks like it will kill his stats, though, unless I'm reading it incorrectly. LD% from 29 to 45? BB% from 12 to 21?
As far as colors go, I'm just not a fan of earth toned/dulled colors, especially in the graph. But they are fine for now.
...and now I'm here
That's % rank in the league
He actually gets better from regression due to a huuuge drop in home runs.
by Graham MacAree on Apr 10, 2008 2:27 PM PDT up reply actions
Ah, you're right. I didn't look that far over.
Though I prefer my way of thinking, since he's not on our team.
...and now I'm here
He is on the 15 day DL at the moment BTW.
And to think, I could have chosen to support the Yankees or Red Sox...
by EnglishMariner on Apr 10, 2008 2:25 PM PDT up reply actions
Brent Lillibr....oh, never mind. Not a pitcher.
How about GS52?
Nice Guys Finish Third - Hopelessly lost, but makin' good time.
Hahaha
His GB% is hilariously low.
I reject your reality and substitute my own!
by Phil Hatzenbuehler on Apr 10, 2008 2:27 PM PDT up reply actions
Tim Lincecum, Andrew Miller
and next to them, Brandon Morrow
So the lesson from this excercise
is that Tim Lincecum is really fucking good.
by seattlebruin on Apr 10, 2008 2:39 PM PDT up reply actions
Our friend, Jered Weaver
plus:
Cupcakes
Zito
Sean Green
Pat Neshek
Ok
Weaver actually looks pretty good, although he's in line for a regression.
Cupcakes
Zito
Neshek
Green
by Graham MacAree on Apr 10, 2008 2:35 PM PDT up reply actions
I rec'd this diary.
Everybody else should do the same.
I reject your reality and substitute my own!
by Phil Hatzenbuehler on Apr 10, 2008 2:28 PM PDT reply actions
I am recommending this FanPost
I support Graham's quest to find more efficient ways to measure pitchers. As long as they prove that Jon Garland sucks.
by seattlebruin on Apr 10, 2008 2:34 PM PDT up reply actions
Garland, you say?
Here he is. That one makes me smile.
by Graham MacAree on Apr 10, 2008 2:38 PM PDT up reply actions
Holy fuck
How is he successful? He doesn't strike anyone out and is in the bottom 10% of LD% even WITH REGRESSION?? Wow...
Do HoRam. That should be amusing
by seattlebruin on Apr 10, 2008 2:42 PM PDT up reply actions
Look at the HR allowed
He isn't really successful, either. Gave up 4.92 R/9 last year.
by Graham MacAree on Apr 10, 2008 2:46 PM PDT up reply actions
It looks like this is saying that Ho wouldn't be that terrible
if he would strike a few people out
by seattlebruin on Apr 10, 2008 2:47 PM PDT up reply actions
And he gave up a lot of HRs for a guy who didn't give up that many OFBs
or were his HR allowed more of the 390 ft screaming line drive types?
by seattlebruin on Apr 10, 2008 2:48 PM PDT up reply actions
I have no idea
Information of that nature was not readily available.
by Graham MacAree on Apr 10, 2008 2:50 PM PDT up reply actions
Graham
I checked the Hit Tracker database (and taught myself how to import spreadsheets... you would think I would have figured that out by now) and anyway, HoRam was no more likely or unlikely to give up line drive home runs, so it would appear to me that he simply got unlucky in his HR%
After running it through by Hit Tracker's criterion (Just Enough + Lucky, Just Enough, Plenty, No Doubter), *WARNING SMALL SAMPLE SIZE ALERT* and over last year, Ho Ram gave up 13 HRs - 1 JE/L, 5 JE, 6 PL, 1 ND, so by %s, he gave up more cheap homers than the average Mariner pitcher would have been expected to give up (by % of HRs allowed)
by seattlebruin on Apr 10, 2008 4:30 PM PDT up reply actions
Well it looks like if you regress him and he falls all the way to the 75th percentile in LD%
combined with a relatively low OFB% and a high GB%, all he would need is a few K's and all of a sudden he goes from giant albatross to eh #5 guy.
by seattlebruin on Apr 10, 2008 2:51 PM PDT up reply actions
Where'd you get the batted ball types?
I just checked out HoRam's page on fangraphs and it lists very different percentages for LD, GB, etc.
I know people classify things differently, so it may not matter - just thought I'd ask.
They're not per ball in play
They're true percentages per plate appearance. Fangraphs uses the former
by Graham MacAree on Apr 10, 2008 4:19 PM PDT up reply actions
Whoops. I called it a diary instead of a fanpost.
I reject your reality and substitute my own!
by Phil Hatzenbuehler on Apr 10, 2008 2:42 PM PDT up reply actions
I see that you're bored of revision...
...but FWIW, I would maybe have bars of zero length for 50th percentile so that a 0th percentile performance shows up with a bar the same length as a 100th percentile performance. Also, that would kinda sorta help with the problem of whether a 100th percentile performance is a large OFB% or a small OFB%, since both an extremely large or small OFB% would show up as an extreme.
It also seems kind of wrong to have the HBP% bars be as long as the K% bars, but it doesn't immediately strike me what the appropriate way to scale those would be.
Hmm
Why would it be better to just denote extreme values rather than saying which extreme it is?
The scaling problem I tried to resolve with that pie chart and the actual % per plate appearance, but you're right, it's still awkward.
by Graham MacAree on Apr 10, 2008 2:43 PM PDT up reply actions
I think what I said wasn't very clear...
You should still say which extreme it is, but instead of having no bar for a 0% performance, have a "negative bar" from midway through the graph to the bottom, and for a 100% performance, have a "positive bar" from midway to the top.
I'm thinking that, at a glance, that would make it easier to pick out what makes a pitcher unique. If a pitcher was median at everything except that he had a big GB% and small OFB%, there would be a bar extending upwards for his GB% and a bar extending downwards for his OFB%.
Ah yes, that would be a good idea
That's definitely something to consider for the new version, but I'll leave it for now as it would require quite a lot of spreadsheet poking.
Thanks for that.
by Graham MacAree on Apr 10, 2008 2:53 PM PDT up reply actions
So nevermind about my leaving it
Do you guys like this version better?
(That's Jake Peavy. He's really good)
by Graham MacAree on Apr 10, 2008 3:56 PM PDT up reply actions
Apart from forgetting to change AL SP to NL SP.
Stupid copy-paste.
by Graham MacAree on Apr 10, 2008 3:59 PM PDT up reply actions
And forgetting to hide those numbers at the bottom.
It's getting late...
by Graham MacAree on Apr 10, 2008 4:02 PM PDT up reply actions
Because I'm curious
and because it will complete the trifecta of upcoming Angels pitchers, Joe Saunders.
Also since no one asked for them yet, Bedard and Silva.
*Visiting Angels fan* Never give up, never surrender!
I'm excited for Silva
I second this one
by seattlebruin on Apr 10, 2008 2:52 PM PDT up reply actions
It's not really that bad
He gives up a lot of line drives because he allows a lot of balls in play. His LD/BIP is only in the 52nd percentile.
by Graham MacAree on Apr 11, 2008 2:25 AM PDT up reply actions
A random question
what kind of sample size would you consider reasonably significant for this type of work? x > 250 batters faced? More?
The regression algorithm takes sample size into account automatically
It might not do it very well, though. When I came up with the correlation coefficients and r^2 values I was playing with ~350ish BF, but I went and dropped that number down a bit for relievers and raised it for starters because all of the relievers were just getting pushed back to average really hard.
by Graham MacAree on Apr 10, 2008 2:56 PM PDT up reply actions
Oh holy crap
everybody act nice. And tidy up - we'll probably have guests coming over soon. I hate being on my best behavior.
Nice Guys Finish Third - Hopelessly lost, but makin' good time.
Now we just need to find a metaphorical closet to hide Coach and Corco in
they can come out when our guests leave
by seattlebruin on Apr 10, 2008 3:33 PM PDT up reply actions
I either want this to be a gay joke or an R Kelly joke
but, alas, it is neither.
Free Barry Bonds
by JI on Apr 10, 2008 8:05 PM PDT up reply actions
Thats when I opened the closet, closet, closet
I fucking hate you Mariners
Oh my God, a rubber.....
I fucking hate you Mariners
by kentroyals5 on Apr 10, 2008 10:08 PM PDT up reply actions
"I pull out my Baretta"
I fucking hate you Mariners
by kentroyals5 on Apr 10, 2008 10:27 PM PDT up reply actions
A long long time ago
Me and the people at work would do Trapped In The Closet freestyles just to kill time. The point being that the lyrics were so tuneless and devoid of art you could just riff on what you were doing at that moment, fade out, and then BAM you had written a hit R Kelly song.
Free Barry Bonds
Thats very true
And its only really the first time you hear that song that you actually laugh..the other times you just think to hard and analyze. Its the "WTF factor" that makes it so great.
I fucking hate you Mariners
by kentroyals5 on Apr 10, 2008 10:59 PM PDT up reply actions
I got descibed by Dave Cameron as 'kind of like a European mgl'?
Words cannot express the pride I feel right now.
by Graham MacAree on Apr 11, 2008 3:44 AM PDT up reply actions
Nitpick...
any chance that you can get your speadsheet to reflect the percentiles as being the more positive of the outcomes?
EX. #1 in K% = 99%
#1 (lowest) in BB% = 99%
Right now Silva is in a very low percential in BB rate, which seems counter intuitive to me.
I'm still thinking about whether I want to do this
I almost prefer having absolutes on there just to be more consistent, but there's an argument to be made for highlighting the 'good' stats over the 'bad'.
by Graham MacAree on Apr 10, 2008 5:46 PM PDT up reply actions
Well....
the way I see it is that when someone looks at Bedard's card they see he's in the 99 %ile for K% and say "Wow. He's good!" Then they look at Silva's BB% and see he's in the 6-7 %ile and think "WTF?"
So would everyone prefer it if I did something like...
K positive
BB negative
HBP negative
LD/BIP ???
GB/BIP ???
FB/BIP ???
IF/FB positive
HR/FB negative
I'm not at all sure what to do with the middle ones though...
by Graham MacAree on Apr 11, 2008 2:19 AM PDT up reply actions
Soooo
Do y'all prefer this version (Sonnanstine)? Is it clear which categories are inverted and which aren't? How's the labelling?
by Graham MacAree on Apr 11, 2008 6:25 AM PDT up reply actions
Oh. And I've flipped line drives now too.
by Graham MacAree on Apr 11, 2008 9:32 AM PDT up reply actions
So at a quick Glance.....
I see that Sonnanstine is a pitcher who:
Get his K's
Doesn't Walk many
A flyball pitcher who's profile suggests that he should give up fewer linedrives than he does and has been extremely fortunate to have given up so few homers.
Does that fit Sonnanstine?
Am confused about the HR thing
He's ~avg for HR/FB
by Graham MacAree on Apr 11, 2008 2:25 PM PDT up reply actions
That's perfect
I like this version. The %/batted ball avoids the weirdness discussed above re: Silva's LD rate. You'd still get a sense that he should allow more total LDs by looking at the K/BB%.
This is awesome.
I like it...
It seems fairly intuitive to me to have the X/BIP stats in that direction. Somehow it was weird to have BB% in ascending order, but it's not weird for LD/FB. I'm not sure what the deal is with that.
It's starting to get a bit busy, but would it be worth it to have a BIP% column in the per batter faced cluster? I know it's implied from the first three rates, but it might be good to have it in there explicitly? I'm not sure, just throwing that out there.
I am on the fence RE: line drive ascending or descending
Should probably give it some more thought at some point, but it's quite easy to switch between the two - the hard part was trying to figure out a way of indicating which measures were ascending and descending without too much clutter.
As for the BIP% column... I don't think it's really necessary, mainly because the pie chart gives you a pretty good idea of the rough BIP% anyway. What would the merits of having a an numeric value there? I'm not really seeing it..
by Graham MacAree on Apr 11, 2008 2:31 PM PDT up reply actions
re: BIP% column
I would include it for the same reason you include the FB/BIP column, essentially. The FB/BIP column isn't strictly necessary, but it's nice to know at a glance whether or not a pitcher gives up a lot of fly balls. Similarly, a BIP% column isn't strictly necessary, but it might be nice to know at a glance whether or not a pitcher could be considered a contact pitcher.
At this point, I can see the advantages of not adding anything more to the cards as there is already a lot of information there. (I wouldn't mind seeing the actual and park-adjusted stats dropped entirely in favor of just presenting the regressed statistics...but that probably wouldn't be a popular viewpoint.)
Brandon Webb
Micah Owings
Danny Haren
Chad Qualls
Brandon Lyon
Jose Valverde
Felix Hernandez may be The King, but Justin Upton is a GOD.
I'm mostly interested in the Chad Qualls/Brandon Lyon comparisions
because I've been leading the "Chad Qualls for closer" bandwagon and Brandon Lyon is terrible.
Felix Hernandez may be The King, but Justin Upton is a GOD.
You'll love RJ's card.
Yesterday's Pants
A blog-thingy about the Mariners and stuff.
by BrettJMiller on Apr 10, 2008 9:20 PM PDT up reply actions
Sweet, thanks.
Ah Michah :(
QUALLS FOR CLOSER!
Felix Hernandez may be The King, but Justin Upton is a GOD.
Probably worth pointing out
That this doesn't have an ageing curve built in. Micah Owings will get better.
by Graham MacAree on Apr 11, 2008 5:04 AM PDT up reply actions
Adam Wainwright plz
I can't think of anyone else on the Cardinals even worth looking up.
...and that's even with Player A throwing a full shutout inning last year.
Free Barry Bonds
Anthony Reyes could also be interesting.
Free Barry Bonds
by JI on Apr 10, 2008 8:08 PM PDT up reply actions
I'll play too
Verlander
R. Hill
Billingsley
B. Wilson
Broxton
Neshek
H. Bell
Time to get excited about baseball again!
That looks eeriely like someone's fantasy team ;)
I'll get round to this and any new requests late this afternoon. I need to study bioinformatics :(
by Graham MacAree on Apr 11, 2008 3:31 AM PDT up reply actions
Pat Neshek is the man.
I wonder how long he can stay effective v. LHB...
Free Barry Bonds
by JI on Apr 11, 2008 9:29 AM PDT up reply actions
Looks really nifty.
Ran accross this at Tango's blog. As far as hand-collating the data, assuming I correctly identified what you're using, I went ahead and parsed it out of the 2004-2007 Retrosheet events logs. Hope this helps.
I was literally just trying to post a link to that spreadsheet
nice timing.
Graham, this looks great and should really help you gauge the predictive power of tRA. Should be better than FIP/xFIP, but it'll be cool to know how MUCH better.
he had to long collect it the first time
because he foolishly didn't ask me. I already went through and grabbed the retrosheet data for him and data from MLB for going forward. The hope is to have daily tRA updates housed somewhere relatively soon.
I think you talked about this before
But this is not necessarily meant for projections yeah? Although regression implies projections, you cannot or are currently not using these player cards in order to estimate a tRA for 2008, for example, correct?
...and now I'm here
Well,
RA in year 0 correlates better with ERA in year 1 than ERA in year 0.
Similarly, FIP in year 0 correlates better with ERA in year 1 than RA in year 0.
xFIP in year 0 is a bit better.
tRA should be better still.
If you have a better handle on a pitcher's skills, you should, over time, see that pitcher's results fall in line. In that sense, it's predictive.
Predicting tRA isn't all that interesting; skills are skills. Felix isn't suddenly going to become a flyballer who doesn't strike anyone out. His tRA profile should vary, but not by much.
Marc's got it spot on
And I fully plan on using this to predict RA. Otherwise there wouldn't be any point.
by Graham MacAree on Apr 11, 2008 2:08 PM PDT up reply actions
Predicting tRA
Predicting tRA isn't all that interesting; skills are skills.
What are we left to predict then? If results are the fuction of skills, teammates, opponents, park, and luck in some combination, and we already have a good handle on a player's skills, his teammates' skills, his opponents' skills, and the park factors, then all we have left to predict is luck--and no one is going to be good at that.
I would assert that what we want to do is measure everyone's skills accurately and then figure out for players of a given skill level, what the variance around their expected results is.
(Also, there should be some expected change in skills as players age, so I don't think that forecasting tRA is a completely trivial task. Or at least it remains to be shown that it's a trivial task.)
So the key thing here is that I'm not writing a projection system
So I'm ignoring player development curves, etc, etc, etc. However, one of the goals of the project is to eventually get around to the player skill projections, which is why I've done stuff like include age and handedness, so I can write a PECOTA-style clustering algorithm and do my best to match players (this will be unfeasible for a while - AFAIK we don't have good historic BIP data, which makes matching pitcher types difficult).
tRA, as it stands, is an attempt to evaluate pitcher performance by removing park effects and team defensive performance. It will hopefully (well, I'll use park and defense adjusted tRA*) correlate well with y+1 RA.
I think player projection and a performance/skill indicator are actually very different things, despite the relation.
by Graham MacAree on Apr 11, 2008 2:43 PM PDT up reply actions
I mostly agree
I definitely think that it would be really great to see the lists of comparable pitchers based on the categories that you are tracking.
tRA, as it stands, is an attempt to evaluate pitcher performance by removing park effects and team defensive performance. It will hopefully (well, I'll use park and defense adjusted tRA*) correlate well with y+1 RA.
I guess I don't understand why we shouldn't at least park and defense adjust the y+1 RA. Predicting a pitcher's y+1 park factor and y+1 defense are distinct issues from predicting a pitcher's contribution to winning, and by not park and defense adjusting RA, things seem to get a bit murky.
Part adjusting tRA does the same thing as adjusting RA, but makes it easier on users reading the output
It's essentially just a user-friendliness thing. If people look at a player card and see an xRA of 5.00, I'm not sure I can count on them to take into account park and expected defence. I'd much rather do the processing on the inside so I can deliver better predictions.
by Graham MacAree on Apr 11, 2008 3:02 PM PDT up reply actions
I think I see what you are saying now
Instead of taking a park and defense neutral stat in year y and a park and defense neutral stat in year y+1 and determining the correlation, you take the park and defense neutral stat in year y, then in effect do a park and defense un-adjustment based on your best guess of the year y+1 park and defense factors, and then do the correlation to the y+1 RA.
I kind of don't like that approach because I really like to drive home the point that RA is a measure of team run prevention, not pitcher effectiveness, but I suppose that you need to make a compromise somewhere, and Rome wasn't built in a day, etc., etc.
I'm with you
But I think if you're going to make predictions, you have to have all the information on hand. It's not really anything to worry about, though - I'll still have tRA in its original form when I start predicting stuff with xRA* (or whatever I'll call it), and tRA will still be the focus.
by Graham MacAree on Apr 12, 2008 11:25 AM PDT up reply actions
It might be cool if you threw up cards
in Matthew's series previews he has been doing.
by Edgar for Pres on Apr 11, 2008 8:35 PM PDT reply actions 1 recs
Since I know y'all are big Lenny fans....
Today: 5 innings, 3 K, 0 BB, 12 GO, 0 FO.
The A's colors are green and gold.
hmmm
I read that when you posted it, but I was in a nocompetewithoutHarden mindset (actually I still am), and Lenny was the #7 starter.
So if I understand correctly, what you're saying there re: Lenny is:
1) He should have a better than average LOB% due to all the GBs, whereas it was somewhat below average last year; and
2) His swinging strike % and ball % were significantly out of line with his K and BB %s? That is pretty difficult to check on any of the stat sites... Your and Graham's work over here mostly just makes me frustrated with bref and even tht, since baselining everything on PAs makes a million times more sense than baselining it on IP. Would it kill them to have K% and BB%?
Answers/thoughts much appreciated as I'm considering a "Lenny doesn't suck, he's kinda decentish" fAnPoSt in the southerly blogosphere.
The A's colors are green and gold.
Close, but not quite
Based on his 2007 pitch results, I expected DiNardo's:
-K rate to go up
-BB rate to go down
-LOB% to go up (not above average)
-HR/FB rate to go down
Granted, that's if his skill level doesn't change and given his limited sample size, it could but he's certainly decent-ish.
Yep
Would AN like to take a look at this stuff, by the way?
by Graham MacAree on Apr 12, 2008 11:35 PM PDT up reply actions
Thanks
Yeah, some of us would, but we're not a real analytically-inclined community on the whole. This is great stuff though (along with all the preceding diaries), and I think even the most analytically-inclined among us don't much know what to make of pitching. Sal Baxamusa of THT (and of course AN) has a stat primer every few weeks on the front page, and we could certainly use one dealing with pitching. I'll email him, and if and when he does a post on this sort of stuff, if you posted/reposted a diary I think it would be well received, but I think as things stand now it would be mostly ignored, as no one knows who you are.
But anyway, this is great stuff, and it's sort of shocking that it is so hard to find reliable pitching metrics (I don't know how much I trust your tRA, but I trust it more than the other crap out there...)
The A's colors are green and gold.
In terms of trust
Without inputs for total runs scored or total innings pitched, tRA is within 7 runs and 3 IP for the entire season, for all of MLB. I'm inclined to trust tRA, tRA+, tROA, but less so for the regression (tRA*), since I'm still trying to find the best thresholds and exponents.
And the people not knowing who I am thing is strange. I've gotten used to it here, and I find the anonymity at AN a little intimidating.
by Graham MacAree on Apr 13, 2008 1:42 AM PDT up reply actions
It's also apparently a lot more accurate than my brain
I meant 5IP, not 3.
by Graham MacAree on Apr 15, 2008 2:48 AM PDT up reply actions
That's a bigger error! It's like 0.1% rather than 0.06%!
(Yeah I’m pretty pleased with that :D)
by Graham MacAree on Apr 15, 2008 9:06 AM PDT up reply actions
I was hoping that tRA would look more favourably on Glavine than current stats.
by Graham MacAree on Apr 14, 2008 9:56 AM PDT up reply actions
As long as you've got most of the Angel staff anyway
How ‘bout Lackey and Escobar?
~Till the Halo burns out...
As long as you've got the other Angel Starters
How about Lackey and Escobar, just so we know what we’re missing if nothing else.
~Till the Halo burns out...
Got a few.
Scott Kazmir
James Shields
Zack Grienke
Joakim Soria
Randy Johnson
Yovani Gallardo
Cole Hamels
Yesterday's Pants
A blog-thingy about the Mariners and stuff.
Is there data to do this for earlier years
Like Pedro, Randy, Clemens, Maddux around their prime? Especially Pedro.
Since this seems to have slowede down a bit
One more I was interested in: Ervin Santana
If possible though, I’d like two versions- one normal one, and one that only uses home games (if that makes the sample size too small, throw in the 2006 numbers as well). I just want to see how much difference there is between the two sets of number, if any.
~Till the Halo burns out...
Washburn & Baek?
I’ve been wondering about their comparative value.
Formerly Alaskan, until Alaska showed up at the SB Nation switch. Thanks for nothing, Alaska!
by The Alaskan on Apr 21, 2008 12:36 PM PDT reply actions
I'm currently quite ill, and in the middle of finals
I will get to these new ones when I have time, but it’s not looking great right now. Sorry.
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