Who is really the best baseball team in the majors? I honestly don't know but I try to figure that out by using basic and advanced statistics. I live for talking about baseball, it's my biggest drive in my life and I will jump on the opportunity to talk baseball with anyone, even with people who I don't really like. For me, Baseball is a piece of art that sits in my mind all day, ready to be painted on at any point of the day.

Sunday, February 20, 2011

A Brief History on Sabermetrics Part V (Miscellanuous)


Josh Hamilton was the league leader in WAR last year with 8.0


By Simon Stracher

This is my last post on Sabermetrics (most likely) and I hope you all enjoyed my other four and this one too.
Also, don't forget to read my new 30 Teams post which will be coming out in a couple of days.


WAR (Wins Above Replacement)- WAR is a statistic that attempts to measure a player’s total contributions to their team in one statistic. It is an extremely handy statistic and is widely used by in baseball circles today. WAR basically looks at a player and asks the question, If this player got injured, how many wins would we lose if we replaced him with a player on our bench?” This value is expressed in a wins format, so we could say that Player A is worth 6.3 wins to their team while Player B is only worth 3.5 wins.

The way to calculate WAR is actually fairly easy. You use wRAA (I talk about wRAA in this post), and 10 runs of wRAA equals one "win". You do the same with UZR (I talk about UZR in this post). Add in a positional adjustment, since some positions are tougher to play than others, and then convert the numbers so that they’re not based on league average (both of these are explained here and here), but on replacement level, which is the value of a fringe player or waiver wire pickup.

If you want to understand WAR, just remember that a team full of replacement players would win about 48 games a year, and that 10 wRAA and 10 UZR both equal one win. Its a great statistic and I highly recommend it.

Context (from www.fangraphs.com):

Starting Pitchers

Relief Pitchers



Hitters

Best: Josh Hamilton 8.0

Worst: Melky Cabrera -1.2

WE (Win Expectancy)- David Appelman (the creator of FanGraphs) summed up Win Expectancy perfectly when he said Win Expectancy is, “the percent chance a particular team will win based on the score, inning, outs, runners on base, and the run environment.”
These percentages are based on decades of historical data, so this means if your team has a 72% chance of winning, than 72% of teams in this situation have the won the game.

Context (from www.fangraphs.com):

20100428_Phillies_Giants_0.png


Notice how as the game goes on, the green line moves closer and closer to the Giants’ side of the chart, indicating that the Giants are becoming more and more likely to win, but then the Phillies dramatically come back and win the game. Also notice that certain key events change the win expectancy more than others. If you want to read more about Win Expectancy click here.

As I stated earlier, this is most likely my last post on Sabermetric terms. I might have one more post talking about Sabermetric terms and such, but don't count on it. Be sure to read my next 30 Teams post and enjoy February Break!

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