Introduction

I should probably introduce this blog, which will more than likely go forgotten after a few posts here.  It happens, I've written on at least one in the past and other things come up.  Honestly, at this point, the blog is a function of my sports fandom, my love of numbers, and quite frankly, boredom.

I will mention that there are really three teams I follow more than anybody else.  There's the Milwaukee Brewers, the Green Bay Packers, and the Milwaukee Panthers men's basketball team.  You probably won't see much written up about the Milwaukee Bucks, the Wisconsin Badgers, or the Marquette Gold in this blog since I don't follow them (and if you can't tell, I don't particularly care for Marquette, although they are playing very well right now).

I do follow my teams very closely.  I have been to all 10 Panther home games this season (as painful as that is), all 17 Panther home games last season (slightly less painful), and 40 Brewers games last season.  Save for the first two Panther home games last year, I have a scorecard for each of the games.  I don't know if it's because I love numbers or that I always need to do more than one thing at a time, but I always enjoy keeping them.


To give you an idea on the kind of information I look into when I look into sports stats, here is what I found from my Brewers stats last year:

• Martin Maldonado was exceptional in Brewers games I attended last year. His line (BA/OBP/Slug) was .389/.450/.648 in those games and he hit 3 home runs.
• He put up those stats in the span of 60 plate appearances, which admittedly is a small sample size.  By my calculation, in those 60 plate appearances, he contributed about 14.68 runs to the team.
• Starting catcher, Jonathan Lucroy, on the other hand, had 90 plate appearances and contributed about 12.90 runs to the team.  
• Nyjer Morgan had 99 plate appearances and contributed 12.64 runs to the team.  And it just so happened that I was there in person to see all 3 of his home runs last year.  So I saw him in the games he provided a little more value than average for the team (line of .282/.313/.474), and still contributed 2 fewer runs than the backup catcher did in about 40 fewer plate appearances.
• The Brewers had 4 players with at least 150 plate appearances in games I attended last year.  Ryan Braun and Rickie Weeks each had 164, Aramis Ramirez had 157, and Norichika Aoki had 151.  Even though he had fewer at bats, Ramirez contributed the most runs to the team (31.49), followed by Ryan Braun (28.93), and Rickie Weeks (26.20).  Norichika Aoki came in sixth at 14.83.
• I must have seen Maldonado at his best and Aoki at his worst.  As stated above, Aoki contributed 14.83 runs in the games I attended and Maldonado contributed 14.68.  They essentially contributed the same number of runs, but it took Aoki 91 more plate appearances to do it.  However, I think most of this is attributed to luck (Aoki's line of .242/.344/.305 is far from his actual .288/.355/.433 line).  
• To put this another way, based on these statistics, a team of 9 Martin Maldonados would have defeated a team of 9 Norichika Aokis by the average score of 9.44 - 3.79, based on their offensive stats in games I attended.
• Want to take a guess who led the team in triples in games I attended last year?  Was it Carlos Gomez?  No, he had 0.  Rickie Weeks?  He had 2.  Ryan Braun?  He had 1 triple.  Nyjer Morgan?  He had 2.  The correct answer is ARAMIS RAMIREZ, with 3.

What do these stats mean?  Very little, since for the most part, these sample sizes are small.  Still, there may be some things to take from it.  For example, the fact that Aramis Ramirez hit 3 triples in 157 plate appearances while Rickie Weeks hit 2 triples in 164 plate appearances and Carlos Gomez hit 0 in 104 plate appearances shows that speed may not be all that large of an indicator in who gets triples.  Aramis Ramirez is a good power hitter who can hit the ball the opposite way; there is no way a ball hit to the wall in left field turns into a triple.  Maybe he can beat the shift.  I tend to think that the cause of this is that he is a strong hitter and that the sample size is small enough that there is a chance at a significant error.

I used the sample of plate appearances in games I attended since I had those stats handy, but this is just an example of the kinds of things I look at.  If I keep this blog going, I will go over how I calculated runs contributed (for future references, I'll call it Equivalent Runs, or Eq. Runs).  It will change slightly going into next season, but the basics of the formula will remain the same.

As you may be able to tell from what is written above, I really prefer baseball statistics to any other statistics.  I may write some about college basketball and football, but most of these posts will be based on baseball.