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Sabermetrics
#1
Posted 25 September 2012  03:52 PM
BA  does not tell the whole story because a hit depends on luck and the placement of the 9 players in the field (which makes me even happier about Dale defensive shifts). Which is why small sample sizes are not useful. Over the course of a season luck tends to average out and people with better contact skills tend to have higher averages.
OBP is better because it speaks more of players overall ability to get on base which is one part of run scoring.
SLG Talks about the ability to move players who are currently on base over (which is the second part of scoring runs). The basic thought is the more bases the batter advances the more bases current runners on base advance, and the greater the likely hood they will score. So a double is better than a single and a triple is better than a double.
I looked up how often a player scores from 2nd base on a single and I found 58% of the time he will score (not sure about that number the site I found didn't strike me as a primary source). It is safe to assume a runner will score from second 100% of the time on a double or better. So if I look at ability of 3 different hypothetical players to score a player from second base.
Player A, a 0.300 hitter who only hits singles In a 100 at bats he will have 30 singles drive in player from second (0.3 x 0.58) 17.4 % of the time.
Player B, a person batting 0.250 and slugging 0.350 and his numbers are 19 singles, 4 doubles, and 2 home runs in 100 at bats. He scores the player from second (0.19 x 0.58 + 0.04 + 0.02) 17.0% of the time. He knocks in the runner a lower percentage of the time but he also scores himself 2% of the time so he ends up with more RBI's. (plus he has the potential to knocks in anyone on 1st base)
Player C, a person batting 0.250 and slugging 0.490 and his numbers are 14 singles, 4 double, 1 triple, and 6 home runs in 100 at bats. He scores the player from second (0.14 x 0.58 + .04+.01+.06) 19.1% of the time and also scores himself 6% of time so he also has more RBI's.
(needed the math for myself)
So slugging makes up for the difference in average because extra base hits have a high chance of scoring the a run even if they occur less often. So do I have this correct?
#3
Posted 26 September 2012  04:48 AM
Throw sabermetrics out the window, man. Grace had an outstanding batter's eye, rarely struck out and was one of the best contact hitter's the Cubs have ever had. There are plenty of people (experts included) that would agree with your assessment.
#4
Posted 26 September 2012  06:47 AM
I went on ahead plugged the numbers for Sosa an Grace over their careers into the situation I used above (I know its not perfect but the general idea is 9th inning runner on 2nd) by taking the number of each type of hit and dividing by by total number of PA.
Grace  singled 21.3%, doubled 6.3%, tripled 0.5% and home runs 2.1% of his at bats (career BA 0.303, SLG 0.442)
Sosa  singled 15.6%, doubled 4.3%, tripled, 0.5% and home runs 6.9% of his at bats (career BA 0.273, SLG 0.468)
Grace scores the guy from second 21.3% of the time and Sosa 20.7% of the time, but Sosa ends up with more RBI because he scored himself 6.9% of the time vs Grace 2.1%. If it is the 9th inning and the game is tied Grace wins it more often, if the cubs are down by 1 Sosa wins it more often while Grace forces extra innings. As was mentioned before the difference doesn't end up being that large when you take their full career into account.
#6
Posted 26 September 2012  08:37 AM
Just wait till you learn about OPS+ or even better wRC+
I'll put those two on the list for the next two things I learn. One thing I should of mentioned before is the winning situation I proposed only works in 1 run games and Ideally your going to avoid those by scoring more runs earlier.
#7
Posted 26 September 2012  10:03 AM
wOBA essentially takes the numbers that you did (how often a player scores from second on a 1B, 2B, 3B, HR) and applies it to every situation (nobody on, bases loaded, etc.) and looks at the probability that each one of those plays results in a run (or rather how many runs each is expected to result in based on their probabilities). That way you can weight each hit according to its run value, and they also incorporate the runvalue of walks. Using the weighted value of each hit and walk, you can calculate a weighted On Base Average (combination of OBP, BA, and SLG, but better!).
#8
Posted 26 September 2012  12:13 PM
What I'm picking up is sabermetric stats make an attempt to generalize a hitter over the course of a year by eliminate any the fluctuation in the position of runners when they come up to bat. Since different situation occurs somewhat randomly during a game (e.g. runner on second, bases load, or bases empty (I'm guessing coming up with the bases empty is the most common situation)) the idea is just to find the hitters that are most likely to generate RBI given all possibilities.
#9
Posted 26 September 2012  12:20 PM
#10
Posted 26 September 2012  01:54 PM
#12
Posted 27 September 2012  05:02 PM
#13
Posted 28 September 2012  08:44 AM
here's some more advanced metrics: http://www.platoonad...sonvoting.html
Favorite part about that was seeing Darwin Barney as a likely MVP candidate using Archaic statistics.
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