The Unwritten Book is Finally Written!
An in-depth analysis of: The sacrifice bunt, batter/pitcher matchups, the intentional base on balls, optimizing a batting lineup, hot and cold streaks, clutch performance, platooning strategies, and much more. Read Excerpts & Customer Reviews
Just went to Vegas and looked at some of the odds. Mariners were 100 to 1 odds to win the World Series at the end of last offseason. Now they are 25 to 1 to win the WS. At 100 to 1 in a weak AL West that would have looked like a great bet to me.
Which pitchers help them most by working the count in their favor? I suggest using the WE by count (from http://baseball.bornbybits.com/statistics/WPA.html). How much do some pitchers rely on getting hitters to good counts? I think there might be some interesting stuff here and the great thing about using WE would be that it works in leverage/context into the pitcher's performance.
I'm not trying to say that looking at variance is the best way to look at the steroids problem. Just an interesting coincidence when I was looking at variance.
There is so much Pitch f/x to examine too. A lot of the interesting things is examining the game in detail and what goes on in the head of pitchers and hitters. Is it better to go outside after a pitch inside? Many of these articles might not be heavy hitting but are very interesting and actually probably impact how I view the game much more than some of the number heavy research out there.
Brian I already posted what I did on lookoutlanding. I'm not sure I can post a link in here but I'll try anyway. I'm not sure its steroids but it seems very convenient.
http://www.lookoutlanding.com/2008/1/11/25150/9196
I want to see all the swinging strike percentages, called strike %, etc used to create a predictive metric. These numbers should be able to be used in a way to eliminate even more luck than a metric like xFIP does. It would be interesting to examine.
It would be interesting to look at how the player talent distribution has changed over the years. Can we extract things and say that offensive shortstops are a higher team priority (at the cost of defense) or is it just that we have more natural talent at the shortstop position now. Where are the best players playing these days? Which positions over the years have seen talent gluts or scarcities?
I tried to do the following idea originally a little while back and just didn't have much luck. OPS+ normalizes a player's OPS for that year's average OPS. Comparing two different players in two different decades and trying to extract which player was better using OPS+ is not as trivial as comparing their OPS+ if the standard deviation of OPS in the league has changed. As baseball has become more competitive over time, the standard deviation of the league should decrease since all players are elite and less filler exists. It might be better then to normalize OPS+ by the variance of a particular year to turn OPS+ into a quartile based metric and still keep the "park" adjustment. 99% would mean that the player (in that park) was better than 99% of players in the league. I tried to look at this before and just did not see a big enough variation in standard deviation to drastically impact the stats. The steroid era also had some interesting results if I remember correctly.
#6. Yeah I guess I suggested that because I thought it'd be easier to do and would maybe shed a little light on the actual outcomes of IBB. WE and RE are great and extremely useful but I think they might hide a little of the info that would be interesting. WE convolutes the sucess/failure of an IBB with LI which makes it useful for identifying when IBB are useful but does not tell us how runs score or with what distribution. RE reduces the number down to an average value. This hides the information about the distribution of runs scored. If 50% of the time no runs score and 50% of the time 4 runs score this might be an acceptable risk in a close game. If 100% of the time 2 runs score then the IBB is always a bad decision in a close game.
The route you took with RE is actually more useful than you give it credit. It is very difficult to take into account platoon splits and player quality with most techniques. I think it was a good effort but is such a complicated problem that no easy solution is apparent.
Another idea would be to look at each instance of an IBB and try to judge the validity of it using your RE/wOBA methods using actual player information. Then we might see some instances where it makes sense to have an IBB.
One thing that might be good to look at the distribution of runs allowed that inning after an IBB occurs vs when an IBB does not occur. If you are in a tied game in late innings it probably doesn't matter if you allow 1 run, 2 runs, or 10 runs. The outcome is very bad. I'd guess that the IBB would increase the times you got out of the inning without giving up a run. This in effect "keeps you in the game".
I agree, it would be very useful to have a WE that easily took into account all variables including team construction, splits, etc. but that is probably way too hard.
I really like that this is being discussed because I think it has a lot of potential. I like using Fangraphs live WPA charts when watching games sometimes but when I've got #7-9 hitters coming up in the 9th and we're down one run I'm pretty sure we are going to lose. I can't really help on implementation but the simpler it was the better (even at the cost of some accuracy I think).
Another M's fan. I'll grant you that Betancourt won't be a legit SS gold glove until he can stop sailing throws. I am very surprised to see Beltre at zero runs. In my mind he might be the best defensive 3B (probably some bias) but he's got to be at least quite a bit above average.
Just went to Vegas and looked at some of the odds. Mariners were 100 to 1 odds to win the World Series at the end of last offseason. Now they are 25 to 1 to win the WS. At 100 to 1 in a weak AL West that would have looked like a great bet to me.
What should I research? (Edgar for Pres) —
Which pitchers help them most by working the count in their favor? I suggest using the WE by count (from http://baseball.bornbybits.com/statistics/WPA.html). How much do some pitchers rely on getting hitters to good counts? I think there might be some interesting stuff here and the great thing about using WE would be that it works in leverage/context into the pitcher's performance.
What should I research? (Edgar for Pres) —
I'm not trying to say that looking at variance is the best way to look at the steroids problem. Just an interesting coincidence when I was looking at variance. There is so much Pitch f/x to examine too. A lot of the interesting things is examining the game in detail and what goes on in the head of pitchers and hitters. Is it better to go outside after a pitch inside? Many of these articles might not be heavy hitting but are very interesting and actually probably impact how I view the game much more than some of the number heavy research out there.
What should I research? (Edgar for Pres) —
Brian I already posted what I did on lookoutlanding. I'm not sure I can post a link in here but I'll try anyway. I'm not sure its steroids but it seems very convenient. http://www.lookoutlanding.com/2008/1/11/25150/9196
What should I research? (Edgar for Pres) —
I want to see all the swinging strike percentages, called strike %, etc used to create a predictive metric. These numbers should be able to be used in a way to eliminate even more luck than a metric like xFIP does. It would be interesting to examine. It would be interesting to look at how the player talent distribution has changed over the years. Can we extract things and say that offensive shortstops are a higher team priority (at the cost of defense) or is it just that we have more natural talent at the shortstop position now. Where are the best players playing these days? Which positions over the years have seen talent gluts or scarcities? I tried to do the following idea originally a little while back and just didn't have much luck. OPS+ normalizes a player's OPS for that year's average OPS. Comparing two different players in two different decades and trying to extract which player was better using OPS+ is not as trivial as comparing their OPS+ if the standard deviation of OPS in the league has changed. As baseball has become more competitive over time, the standard deviation of the league should decrease since all players are elite and less filler exists. It might be better then to normalize OPS+ by the variance of a particular year to turn OPS+ into a quartile based metric and still keep the "park" adjustment. 99% would mean that the player (in that park) was better than 99% of players in the league. I tried to look at this before and just did not see a big enough variation in standard deviation to drastically impact the stats. The steroid era also had some interesting results if I remember correctly.
When to walk 'em... (Edgar for Pres) —
#6. Yeah I guess I suggested that because I thought it'd be easier to do and would maybe shed a little light on the actual outcomes of IBB. WE and RE are great and extremely useful but I think they might hide a little of the info that would be interesting. WE convolutes the sucess/failure of an IBB with LI which makes it useful for identifying when IBB are useful but does not tell us how runs score or with what distribution. RE reduces the number down to an average value. This hides the information about the distribution of runs scored. If 50% of the time no runs score and 50% of the time 4 runs score this might be an acceptable risk in a close game. If 100% of the time 2 runs score then the IBB is always a bad decision in a close game. The route you took with RE is actually more useful than you give it credit. It is very difficult to take into account platoon splits and player quality with most techniques. I think it was a good effort but is such a complicated problem that no easy solution is apparent. Another idea would be to look at each instance of an IBB and try to judge the validity of it using your RE/wOBA methods using actual player information. Then we might see some instances where it makes sense to have an IBB.
When to walk 'em... (Edgar for Pres) —
One thing that might be good to look at the distribution of runs allowed that inning after an IBB occurs vs when an IBB does not occur. If you are in a tied game in late innings it probably doesn't matter if you allow 1 run, 2 runs, or 10 runs. The outcome is very bad. I'd guess that the IBB would increase the times you got out of the inning without giving up a run. This in effect "keeps you in the game". I agree, it would be very useful to have a WE that easily took into account all variables including team construction, splits, etc. but that is probably way too hard.
Win Probability: Preallocation of wins (Edgar for Pres) —
I really like that this is being discussed because I think it has a lot of potential. I like using Fangraphs live WPA charts when watching games sometimes but when I've got #7-9 hitters coming up in the 9th and we're down one run I'm pretty sure we are going to lose. I can't really help on implementation but the simpler it was the better (even at the cost of some accuracy I think).
UZR, 2007, complete list (Edgar for Pres) —
Another M's fan. I'll grant you that Betancourt won't be a legit SS gold glove until he can stop sailing throws. I am very surprised to see Beltre at zero runs. In my mind he might be the best defensive 3B (probably some bias) but he's got to be at least quite a bit above average.