Far too busy reading Lost forums (and doing work) at work this morning. I'll post something later. Unless I'm dead, or have some other malady.

Update: Eating or walking at lunch is for losers.

Back to the old category wins (by popular request according to the survey).
So here's the skinny, I calculated the number of weeks out of 7 a team won (or tied) a category. I then calculated the winning percentage for that category, using the same method as ESPN for our standings (Ties count as half a win and half a loss). Then, I figured out which categories you've locked down for Wins (60% or over), which you stumble through for Losses (40% or less), with the middle counting for tossups. Those numbers proved rather arbitrary, but if you said a team had to have 6 or 7 out of 7 (or lost the same), this analysis doesn't do all that much. Anyway, I took the number you bomb and the number you nail and calculated a win percentage, which doesn't mean much since there are a lot of tossups. The actual number of expected W or L is more indicative of success (as seen by Jon's 6 expected wins every week and his brother's 1).



I assume you can figure out which team is which (it made it a lot easier to calculate using Excel, so you're stuck with it).

For full results on each team/category see below.


I'll probably go through these in more detail in a video recap (assuming it happens this week). Of note, the only sure thing (100% or 0%) on the hitting side thus far is the Dunbars winning SB. I'm a little sad that the schedule thus far has already taken out any potential 100% v 100% matchups. Also, since thus far 3-5 people are using the same pitching strategy, Bobby doesn't have 100% in 3 categories thus far this year. Thus far.

Update: This is a video that you can watch with your eyes.

Rotating League Name week 6 recap

Chapter 6: In which I crap my pants

Whenever I listen to audio books, I always want the old Brit speaking to say that title. Anyway, here's stuff you might care about.

Decided to see how well overall performance can predict weekly performance in a given matchup, so here's a picture of what I found:




The numbers shown for each week 6 matchup shows how many categories were won by the team with the better overall numbers through week 5. That is, if team A had more RBI year-to-date than team B, and team A beat team B in RBI, that got scored a 1 or W for prediction. If either the YTD or matchup ended in a tie, it was scored a .5 (used the same rules as our standings as ties counting half a win and half a loss).

Of note is the Kid-Pawn matchup where every single hitting category went against the past performance (4-2 Bartha, instead of 2-4). At the same time, every pitching category in that matchup went exactly according to the past (though Bartha almost blew it trying to chase Saves history - which incidentally was the only best/worst change from last week, so I'm not bothering to update it this week).

At the bottom of the picture are measures of how well YTD predicted this week's outcome. I actually ran the figures using the current data (through week 6) first because: 1) I thought it would be easier and 2) I forgot that I had the cumulative stats through week 5 handy in the same spreadsheet.

In general, the predictive power based on this one small subset was somewhat better than just flat out guessing (.500). As you might expect (or maybe not, who am I to know what you expect?), adding this week's cumulative stats produces better overall guess, but not that much better than before. The pitching categories seem to follow form a little closer, and so are more predictive (the hitting categories were dead even). I believe this is partly because the league is set up with extreme hitting strategies (this year at least) and because the presence of several rate-based categories means that one good or bad week is more mitigated than in the counting stats. Indeed, when I separated out the rate categories, they were correct 2/3 of the time, versus around 52% each for the positive and negative (and net) counters.

So, after showing that the predictive power is potentially a problem (I mean limited, but I was on a roll), I decided the best way to use this information would be to make predictions for the next week. Here that is:


Yes, I'm going out on a limb and saying that these scores will be closer to correct overall than just picking 6-6-0 for each matchup. Depending on whether this is true, there may or may not be an update on this next week.

My bold predictions (or those of this system I'm using if they are far off) include 4 out of 6 matchups ending 5-7. Shown in gray, there's only one predicted upset (Rod Beck's Counting). If nothing else, this little exercise allows me time to sit around thinking of (good?) ways to combine team names.

brew plop week 6

Dog Days of May:

I'm not going to actually reference the title, as it really only serves as a way of showing that I changed this weeks post.

Bringing back the weekly wins stat. If you don't remember, a weekly win is what would happen if each week was winner take all, so a score of 1-0-0 instead of some numbers that add up to 12.



An even half of the league has 3 wins out of 6 possible to date. It seems like there are quite a few more ties this year than in years past, perhaps because of the scoring changes. I imagine that if you included relatively close scores (i.e., 6-5-1), the number of ties would go even further up. In fact, the number of almost ties (two losses at 5-6-1-) helps explain the oddity that the Shiners are 4th overall in the standings, but have more weekly losses than wins.

But here's yet more evidence that the league is rather competitive top to bottom (excepting maybe the Lefties, who look about as bad as most lefty-lefty match-ups).

And because you asked for it (after I told you to want it), here is the updated weekly bests and worsts:


I'll point that out the best and worst HR weeks were actually in the same match-up (though the Hoopster matched the worst in week 6).

For the bad Wins and Saves, there are so many 0 occurrences I didn't bother to list the weeks, but instead listed the culprits and how many times they "achieved" the feat.

Video to come later.

rotating league name week 5 recap

Far too involved league analysis:

Couldn't decide what I wanted to do for this week's update, so I just did way too much for way too little.

The table below shows expected win values next to actual win totals and the difference between the two.

Here's how we got there. I found the average values and standard deviations for each category. I then classified each weekly category result and assigned that result a point value (high outlier +2, above average +1, below average 0, low outlier -2). I figured you had a reasonable expectation to win a category by being above average in it, with bonuses/punishment for extreme showings. I'm pretty sure I treated negative categories correctly. If you're at all interested, I used 1.75sd for the outlier break, because there were very few above the standard 1.96. I then added up all those categories and weeks and got an expected points total (451), which I then scaled to the number of possible wins (360 to this point). The actual total of wins is lower than 360 due to ties.


Anyway, here's the result:


A negative difference means based on your teams performance, your team would have fared better against an average team than against the teams it actually faced. The biggest caveats are that this is actually less precise than the other way I did expected wins, as this assumes an on/off for winning or not, while the other rates your chance to win a category given others' performance. (old way explained here). This way was slightly easier to look at the season as a whole though, instead of just one week. It also helps show how much luck and opponent can affect the standings.

And since Shane is still kicking names and taking ass, here's the ongoing best (with a new best and worst from week 5):

Brew Plop Week 5

Griping it up:

Because I lost epically to my fantasy nemesis (that's right, it's gotten that bad after this loss and last years final), I had time to stew and think of several ways to make myself feel better.

First up, a new thing I hadn't though much of until this weekend:


Through week 5 in our league, there have been 1561 runs scored and 1436 RBI compared to 2060 hitter's strikeouts (only 1710 pitching K's thanks to the minimalist style of several). Since there have been more -K than either R or RBI, it would seem that a "good week" would be one where you had more R or RBI than -K. Likewise, since there are more R and RBI combined than K (by a lot), a "bad week" would be one where your hitter's strike out more than those two stats combined.

The above table shows the number of weeks a team had more R or RBI than -K. It also shows a negative count of how many times a team had less combined RBI and R than -K. At the bottom of the table, you see the average, min and max number of wins had when having a "good week" or a "bad week", as narrowly defined for this post.

There are nine instances of good R week. In six of those instances, the team managed 7 or more wins (win totals of 6,5, and 3-my terrible week 5- were the others). There are also nine instances of good RBI week. In five of those, the team won 8 or more, but the remaining four were just okay (6,5,5,3-see above).

There are 13 total "good weeks", meaning that there were 5 weeks where a team was good in both R and RBI. Those five weeks resulted in win totals of 10 (dalek), 8 (edit), 8 (unicorn elbow), 8 (hops), and 3 (who do you think). In general, if you have a double good week, you win the week. It also appears that R is a better indicator than RBI for how well your team might do.

On the flip side are "bad weeks", which seem to be more straight forward. If you have a "bad week", your team will most likely win only 4 games.

Because Jon asked for it (and I'm still feeling sorry for myself), here are week 5's expected wins compared to actual.


Of note, I also tried incorporating in ties this time (by counting each tie as half a win), but it didn't change the overall picture by much.

Not a lot to comment on that doesn't make me feel angry and bitter. Interesting though to see when the match-up projects less than 12 wins, who picks up the extras (Dunbars and Reynolds this week).

Lastly, here's a longer term view of the expected wins.


Lots of fluctuations here that you can sort through for yourself. All the same caveats apply to this as to regular roto rankings (i.e., doesn't adjust for extreme weeks, no account for punting a category).

Video updated: My glasses were falling down and I look kinda wonky. I'll try to get someone better to do it next time.