I apologize for taking so long in re-presenting (no, not representing) this to all of you. I’ve actually been done for about a week now, but honestly, I was dreading the fact of writing a rather long post just to explain everything. That’s actually a bit ridiculous to admit, considering how exciting I’ve found this whole thing to be.

In case you forgot or didn’t know, using data from the 2009 season, I looked at all Minnesota Twins players and their success rate of driving in runners in scoring position, success rate of driving in all runners, success rate of advancing runners at least one base, and the average number of bases these runners were advanced by the hitters. I originally included both situations where the batter advanced or scored a runner without making an out, which was quickly constructively criticized by my friend Steven. After presenting all of my findings, I went back and looked through the entire season a second time, but this time eliminating all instances of when a hitter made an out, even if he advanced or scored a baserunner (I’ll explain more in a bit). If you want to review what I previously posted, here they are for you:

1. Send ‘Em Home, Part 1: An introduction to my research, with an explanation of assumptions that I made.
2. Send ‘Em Home, Part 2: The results for Twins hitters and their success rates of driving in runners in scoring position and all runners.
3. Moving Them Over: The results for Twins hitters and their success rates of moving runners up at least one base.
4. Moving Them Around: The results for Twins hitters and the average number of bases they advanced a runner.
Clearly, the main difference between what I’m going to show you now and what I had in #2 above is that I no longer credited hitters for when they made an out. Yes, even if that meant a sacrifice fly or an RBI groundout. I’m sure you’re curious as to why I omitted those when the batter still managed to get a run in, and there’s one simple explanation. If I didn’t remove them from my data, the data from the first time and now wouldn’t have changed at all. It’s not very exciting to see “new” data presented, only to find out that it’s exactly what you’ve seen before, so, for the sake of being uniform, I excluded all instances of outs being recorded.

Second, I apologize, but I made a few mistakes in counting the number of baserunners for most of the hitters. Usually, I was only off by 1 or 2 baserunners in a certain category, so to adjust for the errors, I just replaced my count from going through the season the second time to what I originally had the first time. I know that this is wrong and again, I apologize, but if I was honestly concerned about it, I wouldn’t be posting this on a blog that prides itself for its satirical articles and song parodies.

Overall, there wasn’t much of a shift for a player’s rankings by removing outs from the equation. In the chart below, the light gray cells are for the players’ ranking on the 2009 Twins in success rate of driving in runners in scoring position (SPS, for “scoring position scored”) when outs were both included and excluded. The blue cells are for the rankings of success rate for all runners on base (TRS, or “total runners scored”),* again both for when outs were included and excluded. The last two columns are the difference in ranking for SPS and TRS for the Twins hitters.

** Maybe I’ll stick to calling these two things SPS % and TRS %. SPS % isn’t as much of a mouthful as % RS w/ RISP (percentage of runners scored with runners in scoring position) or whatever I had the first time. *

As you can see, there’s not a lot of shifting here. With the numbers that you’ll see below in a second, I ran correlation tests between the numbers I had before and what I have now, and found that the *r*-value (correlation coefficient) for each was .95 and .98, respectively, meaning that there was a very strong positive correlation for both statistics. Of course, this is only true for Twins hitters in 2009, there’s no reason to believe that this will be true for all players. Now onto the data!

I apologize that the format for this chart is slightly different than the one above. Here, the overall SPS and TRS are presented in the first two columns. The next two (the gold columns) are the SPS and TRS without outs, and the last two (blue) are the difference between the two. You can also read the last two columns as being the percentage of runners that scored when the hitter made an out.

I included the team average at the bottom as well. Therefore, at least in relation to the rest of the team, we can determine who was above or below average in 2009. Some oddities (certainly not all of them, but just a few that I will point out to you):

1. Carlos Gomez was one of the team’s best hitters in avoiding outs while driving in runners. Roughly a quarter of all runners that were on base in scoring position were driven in by him.

2. Justin Morneau was one of the worst in terms of driving in runners while making an out. The same is true for Delmon Young.

3. Jason Kubel was the best in driving in RISP without making an out. Mike Redmond was by far the worst. The same was true for TRS % without making an out.

4. Michael Cuddyer was almost perfectly average in both statistics in relation to the entire team. (.222 SPS % vs. .221 team SPS % and .123 TRS % vs. .122 team TRS % when not making an out).

Lastly, I present to you the correlations with 17 various offensive statistics to see what best correlated with SPS % and TRS %. The best correlation is in blue, and other noteworthy correlations are in gold.

When avoiding outs, a hitter’s slugging percentage with RISP was the best correlation with SPS %. In terms of analysis, I feel that this is very understandable. It’s one of the explanations as to why Ryan Howard has such high RBI totals at the end of every season despite only hitting around .250.* This definitely makes sense, a hitter that gets plenty of extra base hits will drive in a higher percentage of runners than a hitter that only hits singles. I do find it interesting though that RBI and TRS % have a fairly strong correlation. Once again, though, I think this is fairly easy to understand. A hitter that drives in a high percentage of runners will receive (or already have) plenty of playing time, allowing for more opportunities and higher RBI totals. Looking at the chart of players above, the players with the highest TRS % are all guys that we would expect to hit in the middle of the lineup. The top 4 guys were Jason Kubel, Joe Mauer, Delmon Young,** and Justin Morneau, and the three lefties led the team in RBI last year, which we noticed that it correlated pretty well with TRS % in the table above.

* *The values around .4-.5 for all three types of batting average, compared to the .69-.83 for slugging percentage confirm this explanation. *

*** I mentioned before that Young was a crazy hitter in 2009. Good in high leverage situations, but bad in late game situations. Good with runners in scoring position, but bad when runners were on base. I’m sure we can complain about small sample sizes here, but these two relationships (especially the second one) almost seem like paradoxes. *

I’ve already mentioned this several times, but I’m hoping to keep track of these stats for all 30 teams in 2010. By doing this, I’ll be able to have a larger sample size, rate teams during the season, find the major league average for these stats and rate individual players against the MLB average, and look at how other players perform throughout the season that aren’t with the Minnesota Twins. I do expect it to be time consuming, but I feel that it’s possible.

Sometime in the next few days, I’ll put up the post for the success rates of advancing baserunners without making an out. Also look for my post on my tour of Target Field sometime on Friday.

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## Research Revisions, Pt. 1

I apologize for taking so long in re-presenting (no, not representing) this to all of you. I’ve actually been done for about a week now, but honestly, I was dreading the fact of writing a rather long post just to explain everything. That’s actually a bit ridiculous to admit, considering how exciting I’ve found this whole thing to be.

In case you forgot or didn’t know, using data from the 2009 season, I looked at all Minnesota Twins players and their success rate of driving in runners in scoring position, success rate of driving in all runners, success rate of advancing runners at least one base, and the average number of bases these runners were advanced by the hitters. I originally included both situations where the batter advanced or scored a runner without making an out, which was quickly constructively criticized by my friend Steven. After presenting all of my findings, I went back and looked through the entire season a second time, but this time eliminating all instances of when a hitter made an out, even if he advanced or scored a baserunner (I’ll explain more in a bit). If you want to review what I previously posted, here they are for you:

1. Send ‘Em Home, Part 1: An introduction to my research, with an explanation of assumptions that I made. 2. Send ‘Em Home, Part 2: The results for Twins hitters and their success rates of driving in runners in scoring position and all runners. 3. Moving Them Over: The results for Twins hitters and their success rates of moving runners up at least one base. 4. Moving Them Around: The results for Twins hitters and the average number of bases they advanced a runner.Clearly, the main difference between what I’m going to show you now and what I had in #2 above is that I no longer credited hitters for when they made an out. Yes, even if that meant a sacrifice fly or an RBI groundout. I’m sure you’re curious as to why I omitted those when the batter still managed to get a run in, and there’s one simple explanation. If I didn’t remove them from my data, the data from the first time and now wouldn’t have changed at all. It’s not very exciting to see “new” data presented, only to find out that it’s exactly what you’ve seen before, so, for the sake of being uniform, I excluded all instances of outs being recorded.

Second, I apologize, but I made a few mistakes in counting the number of baserunners for most of the hitters. Usually, I was only off by 1 or 2 baserunners in a certain category, so to adjust for the errors, I just replaced my count from going through the season the second time to what I originally had the first time. I know that this is wrong and again, I apologize, but if I was honestly concerned about it, I wouldn’t be posting this on a blog that prides itself for its satirical articles and song parodies.

Overall, there wasn’t much of a shift for a player’s rankings by removing outs from the equation. In the chart below, the light gray cells are for the players’ ranking on the 2009 Twins in success rate of driving in runners in scoring position (SPS, for “scoring position scored”) when outs were both included and excluded. The blue cells are for the rankings of success rate for all runners on base (TRS, or “total runners scored”),* again both for when outs were included and excluded. The last two columns are the difference in ranking for SPS and TRS for the Twins hitters.

* Maybe I’ll stick to calling these two things SPS % and TRS %. SPS % isn’t as much of a mouthful as % RS w/ RISP (percentage of runners scored with runners in scoring position) or whatever I had the first time.As you can see, there’s not a lot of shifting here. With the numbers that you’ll see below in a second, I ran correlation tests between the numbers I had before and what I have now, and found that the

r-value (correlation coefficient) for each was .95 and .98, respectively, meaning that there was a very strong positive correlation for both statistics. Of course, this is only true for Twins hitters in 2009, there’s no reason to believe that this will be true for all players. Now onto the data!I apologize that the format for this chart is slightly different than the one above. Here, the overall SPS and TRS are presented in the first two columns. The next two (the gold columns) are the SPS and TRS without outs, and the last two (blue) are the difference between the two. You can also read the last two columns as being the percentage of runners that scored when the hitter made an out.

I included the team average at the bottom as well. Therefore, at least in relation to the rest of the team, we can determine who was above or below average in 2009. Some oddities (certainly not all of them, but just a few that I will point out to you):

1. Carlos Gomez was one of the team’s best hitters in avoiding outs while driving in runners. Roughly a quarter of all runners that were on base in scoring position were driven in by him.

2. Justin Morneau was one of the worst in terms of driving in runners while making an out. The same is true for Delmon Young.

3. Jason Kubel was the best in driving in RISP without making an out. Mike Redmond was by far the worst. The same was true for TRS % without making an out.

4. Michael Cuddyer was almost perfectly average in both statistics in relation to the entire team. (.222 SPS % vs. .221 team SPS % and .123 TRS % vs. .122 team TRS % when not making an out).

Lastly, I present to you the correlations with 17 various offensive statistics to see what best correlated with SPS % and TRS %. The best correlation is in blue, and other noteworthy correlations are in gold.

When avoiding outs, a hitter’s slugging percentage with RISP was the best correlation with SPS %. In terms of analysis, I feel that this is very understandable. It’s one of the explanations as to why Ryan Howard has such high RBI totals at the end of every season despite only hitting around .250.* This definitely makes sense, a hitter that gets plenty of extra base hits will drive in a higher percentage of runners than a hitter that only hits singles. I do find it interesting though that RBI and TRS % have a fairly strong correlation. Once again, though, I think this is fairly easy to understand. A hitter that drives in a high percentage of runners will receive (or already have) plenty of playing time, allowing for more opportunities and higher RBI totals. Looking at the chart of players above, the players with the highest TRS % are all guys that we would expect to hit in the middle of the lineup. The top 4 guys were Jason Kubel, Joe Mauer, Delmon Young,** and Justin Morneau, and the three lefties led the team in RBI last year, which we noticed that it correlated pretty well with TRS % in the table above.

*

The values around .4-.5 for all three types of batting average, compared to the .69-.83 for slugging percentage confirm this explanation.** I mentioned before that Young was a crazy hitter in 2009. Good in high leverage situations, but bad in late game situations. Good with runners in scoring position, but bad when runners were on base. I’m sure we can complain about small sample sizes here, but these two relationships (especially the second one) almost seem like paradoxes.I’ve already mentioned this several times, but I’m hoping to keep track of these stats for all 30 teams in 2010. By doing this, I’ll be able to have a larger sample size, rate teams during the season, find the major league average for these stats and rate individual players against the MLB average, and look at how other players perform throughout the season that aren’t with the Minnesota Twins. I do expect it to be time consuming, but I feel that it’s possible.

Sometime in the next few days, I’ll put up the post for the success rates of advancing baserunners without making an out. Also look for my post on my tour of Target Field sometime on Friday.

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RelatedThis entry was posted on March 3, 2010 at 7:18 pm and is filed under Andrew Posts, Commentary & Analysis. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.