Yup, it’s been fun indeed.

I understand where you are coming from as far as contract negotiations are concerned but I don’t personally think either party is going to use miniscule details like WAR, BABIP, etc. that are more appropriate for fantasy league than business negotiations.

As mentioned before, professionals fully understand how talented the player is already. Each party tries to figure out what the other would either offer or accept based on market value that has as much to do with raising the ante to outbid other teams competing for the same player and the money the team can make by that signing. WAR doesn’t account for the amount of money a team can make by selling a superstar’s player jersey and the more season tickets his signing can generate or what the player can make by other outside revenue opportunities.

Ciao

Look at Angel Paegan BABIP between the respective years of 2011 and 2012. A picture of this graph in the link tells the story of his 2012 success and why the Giants did not tender him an offer.

http://www.fangraphs.com/graphs.aspx?playerid=2918&position=OF&page=7&type=full

I enjoy dialogue anfd thanks for participating with me..

BABIP has little or no relevancy for a mangerial decision in a game. But it has what I condider a ton of relevancy in evaluating a player to acquire him, give him a big contact be it pitcher or hitter. As an example Andress Torres had a plus 6 WAR in 2010 he had a BA of .270 and a BABIP of .333. We presume he was somewhat lucky that year. If we factor to the norm he should have batted maybe .255. A beter example is Capt. Kirk in May. He was batting .290 with a BABIP of over .400. Those numbers tell you Capt. Kirk “K’s” alot which we saw but forgave with his .290 B.A. Look what happened thereafter. DW in May with a .370 B.A. and about a .430 BABIP which certainly he could not sustain.

But it’s because the BABIP doesn’t include strikeouts and with it missing that important factor it really doesn’t paint a picture of the batter or pitcher overall or help the manager with strategical decisions.

From a statistical point of view, the bottom line is that a .320 hitter is a .320 hitter, A 210 hitter against lefties is a .210 hitter against lefties. A .275 hitter against righties is a .275 hitter against righties. A pitcher who has a batter’s number has a batter’s number. A pitcher who can throw the ball the way he wants to can get batters to hit the ball to his fielders based on their positioning – which is determined by how the pitcher throws, knowing the the batter’s tendency and the geometric result of both these factors when the ball meets the bat. The better pitchers get this done more often and therefore are tougher to hit. In turn, the better batters due to their mechanics and pure talent are less predictable with their tendency and thus are able to do what Wee Willie Keeler knew well over a century ago – “hit ‘em where they ain’t”.

We all know faster players will get more of their share of legged out hits than a slower one. We also know a left handed hitter has the advantage of less feet having to run to first which gives him the advantage of legging out a grounder hit to the left side as opposed to a right handed hitter. BABIP isn’t really needed to understand that.

As far as individual game situations, one also has to consider the thickness of the grass, the way the wind blows, the humidity in the air, the smaller ballpark grouping fielders closer together, etc. into what happens after a batter makes contact. A blooper toward left is bound to be caught in Fenway Park because the left fielder does not need to play that far back due to the green monster being so close while the same can’t be said at Citi Field with it’s deeper dimensions. Poor fielding teams help opposing batters while great fielding teams help those on the mound for them. Every hitter gets his share of lucky hits when not making good contact and every pitcher gets his share of lucky outs due to an outstanding play on a bad pitch.

That’s why I feel BABIP is an interesting tidbit for those who enjoy breaking down statistics to the infinite detail but is not important for the player or astute fan of the game to know due to all the examples I’ve cited above. It’s perfect for those who love calculus as much as they do baseball but I’ll use your example of the .290 hitter maybe really being a .275 hitter to explain what I perceive as it’s irrelevancy. Over the course of the season with 500 at bats, that difference in batting average results in 7.5 less hits for the year – perhaps one less hit every twenty games. Doesn’t seem like much, does it?

Good conversation, enjoyed it.

Batting Average Balls In Play BABIP (excludes strikeouts)

It evens the playing field both for the hitters stats and pitching stats based on line drives caugh or seing eye dogs getting through the whole. These too examples have a reverse relationship of luck or bad luck when used as a pitching stat or hitting stat : That is “other things being equal or disregarding stikeouts.

In the prior link as of May 19, 2012 both DW and Capt. Kirk had extradonarily high BABIP, all their contact made were away from fielders. They hit them where they ain’t. The good luck caught up with them.

If a GM conversely sees a hitter batted .290 overall and had a .330 BABIP perhaps he should view him as a .275 hitter since the norm BABIP is around.300. That means if the mean BA in say NL is .270 and .BABIP is .300 because it excludes strikeouts. What I found out in my BABIP link is the aveage NL 3rd basemen have a BABIP of .308 but the average catcher it is only .292. That is because the average catcher is slow and does not get infield hits and probably fouls out or hit pop ups to an infielder where there is less a chance of the ball falling in for a hit after contact made. The 3B will hit more line drives which could be bonefide hits when contact is made.

My comment about Niese was he was the poster boy previously for bad luck as when he did not strike out a batter on contact the balls got thru for hits. Again the norm BABIP is .300. His stats always were near .330. Many stat guys predicted he would eventually have an oustanding year when he only gave up the norm. Well in 2012 his BABIP was abnormally low. When contact was made it must have been weak ground balls that did not go thru or his line drives given up were right at a fielder.

In a one run game in the late innings with a runner on third, one out and an open base at first and the next two hitters being mostly equal except for BABIP, my guess is the manager would prefer facing one with a higher BABIP than hitter with a lower one since the one with the high BABIP has that tendency to swing and miss and not put the ball in play which could cause that runner to score.

Just knowing who the better contact hitter is sufficient enough information for in-game strategy. For the professionals, it is as useless piece of information as Mr. Baseball leading his team in ninth inning doubles for the month of August. It is of interest only for the statistical buff.

http://www.fangraphs.com/leaders.aspx?pos=all&stats=bat&lg=nl&qual=0&type=8&season=2012&month=0&season1=2012&ind=0&team=0,ss&rost=0&age=0&filter=&players=0

However you can not average two years. Because this stat shows element of luck or bad luck which inflates or deflates other stats. This is the only stat I find useful.
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That saber stat is iron clad in it’s formula and thus claims that Baltimore should have only been in the neighborhood of 82-80, not 93-69. Yet anyone who saw the Orioles this past season knew they were playing better than a .500 ball club and worthy of their 93 win season.

The analysis was updated daily based on the latest statistical information. It was not meant as projection but representation of the team’s true make-up, eliminating the factor of luck. Therefore, the question is would we want a general manager who relies on such information for his decision making?

I recall in July this Pythagorean stat had Baltimore being slightly below .500. Using Bill James advanced calculations as his guide would Sandy, as the Baltimore GM, have thus concluded his team was playing over it’s head and was still more reflective of the team that he took over the prior season, one that struggled to even win 70 games year after year after year?

What would he do still believing the team needed to be rebuilt and not having faith in the ones currently in the clubhouse? Would he hang onto the players who were producing now but be on the decline by the time his rebuilding plans reached fruition on the outside chance they could continue with their success the rest of the way? Or would he go by what his statistical analysis was telling him about the current roster and dismantle it for the sake of building a bonifide franchise for the future? There were players on his club other teams would want which he could find top prospects for.

And how about the money factor on contracts he inherited? Would Baltimore be better off committed to and therefore risking the possibility of being burned as Adam Jones (approximately $84 million at the time) or Nick Markakis (who was till owed $35 million on his) started slowing down?

The scenario is not as wild as it sounds. If Sandy didn’t have faith in the Mets the past two seasons, despite their play up a bit past the all-star break, would he have felt any differently with Baltimore? Again, this was a team that was way off than the Mets were when he took them over.

Most would see the Pythagorean calculation as useless but could the same be said for one who inherited an annual cellar dweller that up to 2012 needed a fresh infusion of young talent? Would one who relies on interpreting statistics instead of what he sees on the field conclude his team was only an abnormality and take the unpopular stance to break up that team since a one year fluke was not worth sacrificing the rebuilding he thought necessary for the long term health of the franchise?

That’s something to think about.

http://www.fangraphs.com/statss.aspx?playerid=4424&position=P

http://www.fangraphs.com/fantasy/index.php/hitter-babip-leaders/

But you go right on believing OBP correlates better cause you have 30 years of Research that doesn’t exist and has never been produced because it’s about as real as Santa Claus and the Easter Bunny!

So if you have three metrics, one works 50% of the time, one works 75% and one 90%, which do you use?

Says the guy who swears RBI projects runs scored.

And if it isn’t 100% accurate that is a sign that something else is in play that you failed to take into account.

There is no such thing as a FLUKE in mathematics or statistical proofs…

If it isn’t 100% true in all cases there is a problem with the math that needs correcting which is why ALL metrics invented thus far are never 100%

They only tell a part of the story and any insistence it is more important than another is just wishfull thinking.