The SOG Myth, Or: Why You Shouldn't Use Statistics to Talk About Hockey
WARNING: Consumption of the statistics contained in the FanPost may lead to head asplosion. Read at your own risk!
Welcome back for my second stats-based FanPost -- this time we're looking at the SOG (shots on goal) statistic, and other game-by-game statistics that may shed some light on, essentially, what wins hockey games. After reading gmh's excellent and comprehensive summary of SOG for the regular season, the question came up -- how is it that the Blackhawks lose games in which they outshoot the opponent by 30+ shots?
![]() Damn you, Hiller! |
To answer this question I turned to NHL event summaries like this one, summed the numbers up for each game, and did my own home-baked stats work on them. What follows is pretty heavy, so if you intend to sit through it, please put away all sharp objects immeeeeeeeeediately and pour yourself your beverage of choice.
(I apologize in advance for making this sound like you need a degree in statistics -- ask questions and I'll try to clarify and simplify)
Shots on Goal (SOG)
To figure out how important each shots (no, not that kind) are to winning a game, I compared shot differential (CHI SOG ‒ OPP SOG) against goal differential (CHI goals ‒ OPP goals). This is our yardstick -- the more the 'Hawks outscore their opponent, the better they've done.
To get a relationship between the two, I ran a regression to get an equation (by fitting the red line to the data) and an R-squared value to determine how tight that relationship was:
(For all you young stats geeks out there: Linear regression is good for continuous sets of values. Since you can't win or lose by half a goal, what you get from the equation might not make sense. I won't get into the details here, but the shading you see under the graph tells you the probability getting that goal differential given the corresponding shot differential. If you really want to know how this is done, click here.)
The R-squared value to tells us how well the shot differential explains the goal differential; since it's practically zero, I can say that, for the 'Hawks at least, outshooting the opponent doesn't have much to do with scoring more.
There are some hockey explanations for this. While protecting a lead, a teams may be more focused on protecting the puck than taking shots. Or when behind, they'll be trying to put as many shots on goal as possible (which may not go in). But, this is a stats post. Y'all can discuss in the comments section. Let's do more stats!

What Wins Hockey Games?
Okay, so if running up the shot total isn't the key to winning, what is? Well, this is a question that's been asked before, believe it or not. Our frenemies over at On The Forecheck had did a nice post way back in 2006 about it, and concluded that teams that have a lot of takeaways also win a lot.
Good, because the NHL event summary data includes that, along with the usual stuff like blocked shots, hits, and face-off percentage. It also had interesting stats like shift lengths, which, after reading this article on Behind the Net, got me thinking.
One stat you can use to compare numbers is correlation, like the OtF guy (Dirk) did. So, I just ran all of these stats together to get a correlation matrix:
(I've actually already calculated the correlation between SOG differential and goal differential -- it's R, so it's the square root of R-squared in the graph above.)
To interpret the table:
- Positive correlation describes how well two numbers move together.
- Negative correlation describes how well two numbers move in opposite directions.
- Zero correlation means the two numbers' movements don't affect each other.
- The last row contains correlations between Goal Differential and everything else.
I also used a couple of non-standard stats:
- Shots Directed Towards Net (SDN) Differential is similar to SOG except that it includes blocked and missed shots; it's like a Corsi rating for the whole team.
- On-Net % Differential is the difference between the percentage of shots that are on net for each team.
As we have already seen, SOG differential has little correlation with goal differential. But we can get some interesting observations here:
- As you'd expect, the two types of shot differential are closely correlated.
- Likewise, more shots tend to lead to lower shooting percentages.
- One interesting relationship is that more SDN tends to happen with fewer PIM; but it would make sense you would be able to shoot more if you're taking fewer penalties.
- The negative correlation between SDN differential and goal differential, then, is interesting -- shooting more (not necessarily on net) looks like a bad thing. Perhaps it's a sign of 3rd period desperation when trailing?
- Longer shift lengths don't lead to more goals -- but, as BTN pointed out, they do lead to more (but less accurate) shots. Our players aren't immune to getting tired.
- Stats highly correlated with goal differential are indicators of success, so we ought to spend our time looking at those.
To get a clearer picture, I re-ran my regressions on two of the stats most correlated with goal differential: Takeaways ‒ Giveaways and On-Net % Differential. I excluded shooting percentage because 1) it's pretty obvious and 2) it's calculated using goals scored, which means that in stats geek world at least, it's cheating.

Takeaways and Giveaways (TK & GV)
It's not the best relationship, but for every extra takeaway over the number of giveaways, the 'Hawks tend to score 0.143 more goals than their opponent:
It might be more informative to compare against this stat for other teams in the league, but it does demonstrate the importance of puck possession. And I agree with Dirk's conclusion (on OtF) that these are important stats. So, hanging onto the puck is better than shooting haphazardly... which brings us to our next stat.

On-Net Percentage (On-Net%)
One criticism of the 'Hawks in the games where they've out-shot the opponent but lost, has been that they were making low quality shots. If you think of blocked and missed shots as an indication of how badly they're shooting, this stat makes sense -- and at 40% correlation, it seems to be one of the best indicators of success:
If you remember the SDN (shots directed toward net) discussion above, high SDN differential tends to result when a team is pressing while behind -- ending up with high quantity but low quality chances. In such situations it will have a low On-Net% differential, which, is not good.

Conclusions
A quick note before I finish this drivel with a mindless laundry list -- even if you didn't read the "for experts geeks" italicized text, you might've noticed that the shaded strip along the +3 goal differential is darker than the stuff around it.
This is because, for no reason whatsoever, the 'Hawks have won an abnormally large number of games by 3 goals:
This is probably just a fluke, but maybe somebody has an idea how this could've happened. But anyway, to end the misery (look at Toews!) you must be going through by reading this (do you really have nothing better to do with your life?), here are some overall observations:
- Protecting the puck and shooting the puck accurately are keys to success.
- Running up SOG isn't.
- Shorter shift lengths help in these areas, but not really overall.
- These numbers all compare the 'Hawks against their opponents; it would be interesting to see these for other teams (and also way too much work).
- Also way too much work, but a legitimate discussion point is how these numbers would break down if we split them (home/away, Huet/Niemi, East/West, etc.).
- None of the statistical relationships are all that strong (don't get me wrong, 40% is a pretty strong correlation for something like this, but it still only explains 16% of what's going on). There are a lot of intangibles that go into how a game will turn out.
- In the end, I spent way too much time doing this, only to come up with some vague conclusions about what works. Clearly, while they can be descriptive, statistics are a waste of time for talking hockey. But I'm going to keep doing it anyway.
Thanks for reading. Since I'm all out of cookies, and since you were such a trouper for making it through all this, have a puck instead:
(courtesy of Luscious Layers Bakery... ooooh, I want one too!)
Feel free to ask lots of questions (so I can edit this and make it clearer/simpler) or talk about this stuff. There's a lot I didn't cover or described poorly, and somebody with more hockey IQ can probably add a lot more insight.
(I was hoping to finish this before the playoffs started, or at least on an off-day, but hope you enjoyed this as a welcome distraction from whatever... or as a form of self-torture. Oh, and apologies to gmh for blowing off the whole collaboration idea on this one... we'll do one next time!)
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Wow!
I really appreciate this! Beautiful graphs and chart. Very disappointing that there’s not really statistical relevance, though. This is the first thing I’ve read yet today, so I may have to check back later after more coffee.
If I read this right, the worse the Hawks do, the more statistically relevant it is? Or am I just misreading the correlations? But anyway, although it would be a lot of work and at this point perhaps not even worth doing as we’re not seeing anything of value, do you think it’s going to show more statistical relevance if split out by opposing team?
BTW, I’ll be out of town tomorrow through Monday with hopefully no internet access, and have a shitload of things to take care of today to get ready because I procrastinated.
2009 SCH Post Whore
2010 Troll Collector
SCH's Resident Mom
The sun never sets on a badass
Ha, I know all about procrastination
But to answer your question, I took these correlations over the whole regular season, and the highlighted ones are all against goal differential — so it’s a measure of how relevant it is to how the Hawks do. When they don’t do well they end up in the left-hand sides of the graphs, but they contribute just as much statistically as when they do well.
I considered doing a team split (like for the Preds), but I think the sample size gets so small at that point that you probably wouldn’t be able to draw any conclusions, other than comparing to the overall stats.
I like stats too
I appreciate the hard work.
I get the feeling that this is how Q makes his lines, only he uses things like “when I wore this pair of socks Eager and Kops scored……..”
In my world, as small as it is, I like to watch hockey games. While I’m watching the game, I try to figure out what the other team is doing and what the Hawks need to do to beat what the other team is doing. Statistics like this might help, but I don’t see how. Shoot less score more? Shoot more score less? Less penalties equals more goals? Shorter shifts equal less penalties? Take it easy, I’m not stating that is what your numbers imply.
The players have to do what the system they are playing requires. If the other team doesn’t let them do that, then the stats will be off. For example, run this same exercise as above adjusted for when a team is trailing with 10 minutes to go in the game. The other teams will be playing a different style and the numbers will be quite different, I would think.
I’m going to keep looking at this off and on during the day to see what else my obviously atrophied brain can think of
Tonight will be a fun game to watch, eh?
Chewing gum?
I think I misunderstood what you were trying to say.
But now that I have read it again, and again, I see that my comment above really is unnecessary, as most of mine seem to be lately.
Chewing gum?
http://www.instantsfun.es/sadtuba
Picture bloodbaths and elevator shafts
Like these murderous rhymes tight from genuine craft
Rec'd and nice job
You hinted to it a fair amount in your post, but I think the one stat that would show a fairly strong correlation to wins are even strength shots on goal while the game is tied. This stat may not work for the Hawks bc they are rarely outshot, but league wide I betcha there’s a strong correlation. Teams play a different style when they are up or down. Im going to guess that the Hawks lost the games when they heavily outshot the other teams (30+ diff.) because they fell behind by a couple goals early and they started to press while their opponents were content to protect their lead while allowing shots fired from low percentages. Of course, I am way too lazy to do the research for this, so I’m just going to assume I’m right until I’m told otherwise.
this is why I love Behind the Net
They covered that for CORSI percentages and then they followed it up with one by period too. And then they did something with Fenwick numbers that are sort of similar.
But when it was suggested to him that Toews v. Kane seems likely to become a sidebar to every future international hockey tournament, he smiled and said: "I'd like us to win something together, too."
(Tweets @ChiBlackhawks and blogs at Blackhawks Down Low.)
by chiblackhawks on Apr 20, 2010 10:46 AM CDT up reply actions 1 recs
That stuff is fantastic
I think there’s more revealing information in just the “chi” rows of those tables than I got out of this whole FanPost. Seems like the “3rd period letdown” that we’ve noticed from our boys does actually happen.
I wonder where BTN gets their numbers, because I can only break stuff down by game (until I delve into the play-by-play data, ugh). I’ll probably never have the experience or depth of data that they have, but thanks for bringing it up — not only is it relevant, but I’ve been struggling to figure out how to actually use the stats I have for anything useful.
With more discussion (and your help) maybe I can change that “shouldn’t” to a “should” and come up with something more meaningful.
I wish I knew as well
but I think they go into play by play data. It’s awesome stuff, either way, but definitely a lot of work to try and do manually. SIGH.
PS. I rec’d your post even though you don’t think it amounted to as much info as BtN’s—there’s so many numbers to just play with that sometimes just disproving a common belief helps a lot, even if it just tells us we’re moving in maybe not the right direction. The data for takeaways is pretty interesting as well, as it seems to be a stat often overlooked in favor of others.
Don’t worry, Stig; we’ll think of something. ;)
But when it was suggested to him that Toews v. Kane seems likely to become a sidebar to every future international hockey tournament, he smiled and said: "I'd like us to win something together, too."
(Tweets @ChiBlackhawks and blogs at Blackhawks Down Low.)
by chiblackhawks on Apr 20, 2010 11:52 AM CDT up reply actions
Disproving a common belief
Yeah, I guess now I just get annoyed when people talk about “outshooting” an opponent, when we all know it’s “outchancing” them that counts. Or at least, we do now.
"hey, how about a little something, you know, for the effort, you know."
hey – this is nice work. Especially the sweet charts!
Some thoughts:
- You’ve delved into one of the great unanswered questions in hockey – what micro-events lead to wins at the single-game level?
- We know what repeatable talent leads to wins at the team-season level – shot differential
- We know that legitimately good goaltending does the same
- To a lesser extent, faceoffs (talent) and turnovers (sort of) lead to wins
- However, a high shooting percentage, which is not repeatable, also leads to wins
And that’s the biggest problem – at the game-level, “making your shots” is the single-biggest driver of whether you’ll win the game. So essentially you need to get lucky over a small number of trials to win any given game. Over the course of the season, things tend to even out.
We need to know a hell of a lot more about what’s going on during the game to figure out what drives winning at the micro level. For now, I think the focus should be on generating as many shots as possible and preventing them at the other end. Do that, and more often than not, you’ll win, even if the Sharks just provided a counter-example on Sunday.
Hey, thanks for noticing!
I must admit I don’t read your blog enough — I only became a hockey fan a little over a year ago, and haven’t gotten so into it, stats-wise, until now.
I guess what kind of interests me in terms of trying to boil stuff out over a whole season, is not just the trends, but also what exceptions to those trends mean. Like, if the Sharks outshoot the Avs by 30+ shots, what else is coming into play to cause them to lose? (Okay, Boyle, but he’s not the reason they couldn’t end it in regulation) Maybe it’s Anderson standing on his head, but there are other factors too that you might be able to glean from the numbers.
Maybe as a microcosm of these “great unanswered questions in hockey” I’m looking for reasons why the ‘Hawks talent, specifically works or doesn’t. Hopefully there’s more to come, as time allows.
Usually the exceptions are all unsustainably high (or low) shooting percentages.
One method I really like for looking at these things is to correlate performance in even and odd games. If something is a true talent, then it should exist in roughly similar quantities in games 1, 3, 5…81 as it does in games 2,4,6…82. You’ll find that shot volume is quite consistent in those two groups. Shooting percentage is not. PP% is not. PK% is not. But wins are driven by high shooting , high PP and high PK%. So in one game, you’re trying to capture ephemeral performances. If you find that something’s important, but it’s not a persistent talent, then it doesn’t do much good going forward.
Now if we had RFID tags on the puck and every player, maybe we could make some progress.
That's a really interesting technique
I didn’t major in statistics but it’s a large part of my day job… and I’ve never heard of doing something like that to determine whether a trend/distribution is reliable. But I can see how it would be a much more intuitive technique than, say, looking at a histogram or running a formal test.
I just re-read your first comment, and it was actually really helpful to frame I was doing with the whole “single game vs season trend” distinction. Like I’ve mentioned I don’t really know what I’m doing but I think it’s helpful in terms of looking for ways to get any further (short of RFID tags! haha).
It seems like everything does go back to scoring chances though (which makes sense). If you think about it, being on the PP is just a way to get more shots at the expense of the other team’s chances, and really, so are things like puck possession, face-off wins, etc. So maybe the objective should be finding the next level — what it is that generates scoring chances, rather than goals. At least that way you can get some sense of useful statistics that you can actually connect with something players can act on.
Thanks again for bringing your experience here… I think I’m going to have to start reading around, at BtN and elsewhere, so I can get a little better sense of what I’m doing!
gross shot totals ignore quality of the shot chances (and the shots themselves)
generating lots of shots is not overly hard, and can lead to thos ‘out shoot them by 30+ and lose’ games – like the Hawks periodically had this year.
Confusion will be my epitaph.
take a read around the internet. “Shot quality” is not as big a deal as you think it is. Anyways, the Hawks also dominated the league in scoring chances. They were far and away #1. So whatever metric you want to use: close shots, scoring chances, Corsi – the Hawks dominated them all, and they all converged to the same result.
Makes sense
It evens out in the end. The only reliable measure of “quality” I would imagine is whether a goal was scored. But, that’s not very useful for drawing conclusions…
no, quality shots are those from reasonably close and from good angles
particularly those from odd man breaks
Now, whether there is a database from which to mine those and distinguish them from very long, non-screened and/or bad angle shots?
Confusion will be my epitaph.
Actually
The play-by-play data does include some notes on shots — what kind of shot/miss and the distance. It doesn’t say anything about the angle (I don’t think there’s much I can infer the actual shot angle from) or whether it was screened, and it annoyingly leaves this out when it’s blocked, but it’s definitely something I’m hoping to mine as soon as I get the time.
There’s no substitute for video and actually watching each shot, but then you could take it one step further and talk about how a play develops. In a lot of ways the further you take it, analysis becomes as much an art as it is a science.
I think Hawerchuk’s point, though, was that this so-called “quality” of shot doesn’t statistically give you more information than the number of shots (directed) in general. But, given what we’ve seen from the ‘Hawks this year, I’m inclined to look at this anyway… can’t guarantee it’ll be my next FanPost but I’ll give it a shot sometime.
it does affect your (or anyone's) ability to deal with data
if there really isn’t any data
You aren’t a Global Warming scientist who gets to just make shit up
Confusion will be my epitaph.
or attorney
Well, folks, I want to thank you for being here for the recording of my live comedy album. Funny material and laughter will be dubbed in later.
by ChicagoNativeSon on Apr 25, 2010 8:22 PM CDT up reply actions
You may already be familiar with...
…this site, but a buddy of mine from grade school is one of the contributors here.
One thing he tries to take account of is rebounds. Intuitively, it seems to me that shooting % is higher on such shots, and not just because they’re closer in.
When I try to think hard aout this, I have to stop before my head asplodes, and I’m content with the conclusion in the title of this post.
But something tells me you’re not gonna just throw up your hands here.
Gentlemen! I have invented...this thing!
A rebound occurs
after a goalie has already committed to a position given where the puck was a few moments earlier. Since a rebound can theoretically end up pretty much anywhere in about 150 degree spread, there’s a good chance that the goalie will be very much out of position. At least that’s how it’s seemed to me.
(170 g) * (3x10^8 m/s)^2 = 1.5x10^16 J
Thanks
Wow, that’s really impressive. Though my comment above was pretty accurate, I most likely read the posts you linked and forgot, thus convincing myself that I came to my own conclusion. Thanks for the links.
by EamusCatuli23 on Apr 20, 2010 11:22 AM CDT up reply actions
I love nerds
Only half way through the post, but I have to say the graphics look spectacular.
Time for some thrillin' heroics!
by shinkicker on Apr 20, 2010 10:56 AM CDT via mobile reply actions
PIM is positively correlated with goals!
Haha! If we’re getting off fewer shots per game, but there’s still a positive correlation, our PK really is dangerous!
One interesting thing is that face-off win percentage is negatively correlated. It’s only -4%, but I’d still expect a positive correlation of some sort.
(170 g) * (3x10^8 m/s)^2 = 1.5x10^16 J
I'm glad you did the warning at the beginning
My head did asplode. Nice job on this one.
I went to a fight the other night and a hockey game broke out.
- Rodney Dangerfield
This is great
I think I’m going to have to read this through a couple more times to really get it. It’s pretty interesting that the TA-GA has zero correlation with the SDN yet some positive correlation with goals. I’m trying to figure out if there’s an obvious explanation for this that I’m missing or if it’s a statistical anomaly.
It would be interesting to see how it broke down for different lines, but a) that would involve a whole lot of mining of play-by-play data, and b) they change so much the sample size would probably be too small.
by WhatWouldBurishDo on Apr 20, 2010 1:29 PM CDT reply actions
It could mean
that TA-GA has a very high conversion rate for shots generated, but it isn’t very common. In that case, a turnover would only result in a small increase in SDN, but a large increase in GF. Even still, R < 0.06 for TA-GA
(170 g) * (3x10^8 m/s)^2 = 1.5x10^16 J
Makes sense
I can follow the maths ok, but the interpretation is not my forte
by WhatWouldBurishDo on Apr 20, 2010 2:08 PM CDT reply actions
wow
And I thought Americans doing the accent was bad in person. Who knew it was even worse typed out?
by WhatWouldBurishDo on Apr 20, 2010 4:32 PM CDT up reply actions 1 recs
Here's a stat for you
this post is awesome 99% of the time.
Good job
no, it's my fault
I should have let you know about my internet situation, but I’m glad you went ahead without me, because it would have taken me a couple of days just to fully understand all of the statistical aspects anyway. I think you did a great job explaining to ’tards like me exactly what everything describes.
I’m leaning toward becoming a stat nihilist, myself, when it comes to hockey, I think primarily because sometimes the numbers on paper don’t quite accurately reflect what happens on the ice. (Unlike basketball, which is fully describable through a breakdown of game stats.) I find the narrative within each game to be intriguingly unique in that so many factors go into, say, the scoring of a goal. Play by play sort of breaks it down where you can trace a sequence of events, but predicting success based on one or two elements seems a bit inadequate. I think you did a good job of illustrating that here.
It would be interesting to see what the correlation is between goals scored and goal differential, actually, since a 5-2 game might play out differently than a 3-0 game. Or time-of-goal-scored and goal differential, i.e. when the Hawks score first kind of thing. Argh, see what I mean? There are too many angles of approach, it drives me nuts sometimes.
that's one of the reasons that even numbers geeks can just sit back, watch & enjoy
some of it is just too ‘chaos theory’ to reduce to formulae
Confusion will be my epitaph.
stats
The attitude I’ve developed with statistics is that you should never assume there’s any use for them beyond being partially descriptive — as in they tell you exactly what they mean, and nothing else. Any interpretation is pretty subjective, and as a stats teacher/professional would always tell you, “correlation doesn’t mean causation.”
I think you have a pretty good point about hockey stats being tough to draw a bead from, partially because it’s such a continuous game with few stoppages in play (there’s a reason why baseball can be so overly analyzed by stats), and partially because so many important things that happen don’t make the score sheet.
The eye test often works better because our brains are capable of processing so much information, plus we learn what kinds of things tend to lead to other things (like goals). So what “looks right” is often more useful than a set of stats. But it’s hard to describe what your eye sees, so stats can lead to some clarity there.
I think what I’m going to look at next is to not be lazy and actually figure something out from the play by play, but rather than looking at correlations and general trends, try to come up with more of a narrative. I think that’s what those sports simulations sites do (I think one of them predicted the Caps would win the cup), but short of looking at video it might be one of the more interesting things to do.
Might be better waiting for the offseason though. For now maybe I just want to figure out why the Preds beat us, but I don’t have to look at stats to figure that part out.
As Old Man Daley used to say...
…when asked why his candidate lost:
“He didn’t get enough votes.”
Gentlemen! I have invented...this thing!
Daley's guy lost one?
where were the legions of the dead that day?
It’s not like they have anything else to do in Chicago
Confusion will be my epitaph.
Stigger, you put entirely too much into that.
Well freaking done.
by Ghost Soldier on Apr 20, 2010 7:27 PM CDT reply actions
I have always thought...
…shots on goal was a very overated stat.
There are far too many games were a teams get outshot (by a lot) and they end up winning.
Hockey is about generating quality opportunties and limiting your opponents quality opportunities. If you do that enough, you will win your share of games.
"I don't like them fellas that drive in two runs but let in three" Casey Stengel
overrated maybe
but slightly indicative to regress SOG Against
http://www.puckprospectus.com/article.php?articleid=369
http://www.puckprospectus.com/article.php?articleid=375
Pearson Correlation Coefficient between shots on goal and points in the standings was 0.48 Using the Pearson Correlation Coefficient, the correlation between shots against and total points in the standings was -0.53. Remember that fewer shots on goal is obviously the objective, so the -0.53 is actually very close to the 0.48 correlation demonstrated last week. In fact, shots against may be slightly more indicative of team success in the standings than shots on goal.
tremendously tremendous
Not overrated
Actually, Hawerchuk was basically making this point — shots are a good indication of a team’s success on the season level. That is, a team that outshoots their opponents (or keeps their shot totals down, whatever) is more likely to be a good team, and thus will gain more points over the course of a season.
Contrast that (which basically makes the ’Hawks season just one data point) with what I did, which was look at shots on goal on a game-by-game basis and see if more shots leads to more goals.
It doesn’t so that would suggest it’s more a general indication of (repeatable) team skill than an ability to win an individual game (which may come from unrepeatable abilities/events).
I’m talking about overrated in that neither SA or SOG are a correlation to a team’s success in actual wins/total points. Again .5 +/- point either way in the standings.
tremendously tremendous
by Crease Monkey on Apr 22, 2010 3:03 PM CDT up reply actions
Unless I'm reading it wrong
It looks pretty similar? According to what you have in italics
Corr(SOG, Pts) = 0.48 = 48%
Corr(SOG against, Pts) = -0.53 = -53%
Since the latter is an inverse relationship it’s obviously negative… but quality-wise they’re essentially just as useful statistically (explains about 25% of the variance in points).
My Brain just Asploded
And I deal with numbers and math at work like no ones buissness
Get off my Land!
ART.I§8-11; AM I-XXVII
James Madison is my Hero!
by Toews-makes-funny-faces on Apr 25, 2010 8:39 PM CDT reply actions
I like you added warning!
Get off my Land!
ART.I§8-11; AM I-XXVII
James Madison is my Hero!
by Toews-makes-funny-faces on Apr 30, 2010 6:03 PM CDT up reply actions
They say 85% of everything you learn in college
is just a bunch of bullshit you’ll never need. 65% of everything you got you bought just to satisfy your greed. Because 90% of the world’s population links your possessions to success, even though 80% of the wealthiest 1% drink to an alarming excess. More money, more stress.
You're the captain, huh? Here... smell my Buff(et)!
You
listen to Bob and Tom.
Correct?
/Note unceasing sarcastic laughter in background.
by burpchelischili on Apr 29, 2010 9:47 PM CDT up reply actions
Is "not listening to Bob and Tom"
really an option in any life worth living??
Well, folks, I want to thank you for being here for the recording of my live comedy album. Funny material and laughter will be dubbed in later.
by ChicagoNativeSon on Apr 29, 2010 10:55 PM CDT up reply actions
No,
but I had to read that 6-7 times to figure out what the correct answer was.
/Note unceasing sarcastic laughter in background.
by burpchelischili on Apr 30, 2010 7:56 PM CDT up reply actions
My bad, let me rephase it for clarity then ...
Is “not listening to Bob and Tom”
really not an option in any life not worth living??
Well, folks, I want to thank you for being here for the recording of my live comedy album. Funny material and laughter will be dubbed in later.
by ChicagoNativeSon on Apr 30, 2010 11:24 PM CDT up reply actions
Do you work for Congress or the White House?
Get off my Land!
ART.I§8-11; AM I-XXVII
James Madison is my Hero!
by Toews-makes-funny-faces on Apr 30, 2010 6:02 PM CDT up reply actions

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