Its getting to be that time of year again when Twins fans start to talk about the draft. This year the Twins will have only one first round choice and no supplemental choices since they didn't lose any ranked free agents. Unlike basketball and football, the baseball draft is much more a numbers game, with even top picks sometimes failing. And it often takes 5-10 years before you know a draft was a success, especially for teams that draft a lot of high school players.
So as we look at the last draft of the decade, lets look at its earlier drafts.
In 2001, the Twins made Joe Mauer their first draft pick of this millennium. At the time there was a lot of talk about two more advanced players, Mark Prior and Mark Teixera, and some people criticized the Mauer choice as a budget move. If it was, it was a good move as Mauer may turn out to be one of the greatest players ever to play the game.
In 2002, The Twin took Denard Span. He didn't move as fast as Mauer and a lot of people gave up on him. But he has come into his own. He's not Torii Hunter, but he is a good major league center fielder and will likely remain the Twins leadoff hitter for a long time to come.
In 2003, the Twins took Matt Moses. His bat was supposed to carry him, but it didn't carry him very far. He never really got beyond AA.
In 2004, the Twins had two extra first round choices, the picks were Trevor Plouffe, Glen Perkins and Steve Waldrop. This draft demonstrates the patience required to really know how a draft came out.
Plouffe just had his first brief stint in the majors and impressed the coaching staff. It looks like he is ready, but is blocked by last year's deal for JJ Hardy. It looks a bit like a repeat of the experience Span had when the Twins brought in Carlos Gomez.
Last season, Perkins looked like he was going to be a regular in the rotation, or at least a stalwart of the bullpen. Right now he back at AAA struggling to put things together after ending last season early with an injury. He seems to have burned some bridges with the club's management. But he is probably not going anywhere until he shows he is ready to pitch again in the major leagues.
Waldrop suffered an arm injury and is just now playing his first year at AAA, working out of the bullpen. He looks like he may be ready if there is an opening. But he is not on the major league roster.
In 2005, the Twins took Matt Garza who turned out to be extremely talented and also extremely hard for Ron Gardenhire to deal with. He got dealt to Tampa for Delmon Young.
In 2006, the Twins took Chris Parmelee. Parmelee was considered a slugger and he still is. Unfortunately he makes contact so rarely his opportunities to show off that power are limited. He was just demoted from AA back to A ball after struggling in his first year at New Britain. He isn't finished, but he is not on a fast track of any kind. At best he looks like an all or nothing guy that bats low in the order.
In 2007, the Twins took Ben Revere. Like the choice of Mauer, this was criticized as a financial move. Unlike Mauer, Revere is unlikely to be a hall-of-famer. But he has shown that the Twins knew what they were doing. He is the organizations fastest player and top base stealer. He has hit over .300 at every stop. He was criticized as a slap hitter when drafted and he has yet to show any real power. But it is likely, like Span, his power numbers will improve as he gets more mature. He is never going to be a big home run threat, but a guy who hits balls into the gap and can run like the wind is likely going to be a productive major league player. The other knock on Revere is his defense, He isn't a polished defender yet and his arm is never going to be a plus.
In 2008, the Twins had two choices. Aaron Hicks and Carlos Guttierez.
Hicks has everyone excited as a guy who has both speed and power. But he is very raw and is not on a fast track. He started the year at Beloit with a very cold bat. He then got very hot for a while raising his barring average in to the .300's. That hot streak ended and his hitting has fallen back to the mid-.200's. He may get a promotion in June, but its possible the Twins will let him play out the year in low A ball.
Guttierez was coming off arm surgery when drafted. Because of the surgery he had been used as a closer his last year in college. The Twins, however, drafted him as a starter. He has a great sinker, but needed to work on auxiliarly pitches as a starter. He has been used carefully as they try to build his stamina. Last year they moved him to the bullpen to finish the year in order to avoid over-working him. He is back at New Britain this year and doing well. Given the Twins depth in pitching, its possible they will give up on the idea of him starting. But he has the potential to be a number one or two starter if he can develop pitches to go with his sinker.
In 2009, the Twins took Kyle Gibson. Gibson didn't pitch last summer and is already at AA this year where he now seems to be thriving.
In general, recent drafts will seem better than earlier drafts. This is because guys like Gibson are all about projection and tools. Whereas players who have been around a couple years have usually started to show a few warts. But its important to remember Joe Mauer, the first pick of this decade, is just reaching his prime. Drafts in baseball require a lot of patience.
Wednesday, May 26, 2010
Tuesday, May 25, 2010
Run Probabilities versus Win Expectancies
Over at Twinsgeek there is an interesting set of data that is provided to discuss late game decisions:
"historically what percentage of games were won by the home team carrying various leads or deficits into the top of the ninth.
Leading by 5 - win 99.7% of the time
Leading by 4 - win 98.8% of the time
Leading by 3 - win 98.0% of the time
Leading by 2 - win 94.5% of the time
Leading by 1 - win 86.6% of the time
Tied - win 52.2% of the time
Losing by 1 - win 15.2% of the time
Losing by 2 - win 6.3% of the time
Losing by 3 - win 2.9% of the time
Losing by 4 - win 1.3% of the time
Losing by 5 - win 0.6% of the time"
I think the really interesting part of this data is that it clearly shows that not all runs are created equally. While the data here is only for one particular situation, I think the pattern is likely to apply regardless of the inning.
In a tie game, the first run that scores in the bottom of the 8th raises a team's chances of winning by 66%,more than all the additional runs combined. The second run raises the team's chances by 10% and the third run raises the team's chances by 4%. If the home team starts the bottom of the 8th down by a run, the first run it scores raises its chances of winning by 243%.
On the other hand, when down by two runs, scoring the first run only increases the chances of winning by 141% and when down by 2 runs only 117%.
What this demonstrates, of no surprise to traditionalists, is that in a close game, playing for one run is by far and away the better strategy than playing for a big inning. If you are down by more than a run, then playing for the big inning makes more sense.
One other note. I calculated the increases based on the formula (chances after run scores- chances before run scores)/(chances before run scores). That is to say, the change in the probability a team will win. You an argue whether the percentage increase is more appropriate than just the straight number of additional games a team would win. But the pattern is the same either way. And, of course, these are averages. It may well be that in close games where both teams are scoring runs in bunches, the extra runs become more important. Or that a single run is more important in a pitchers duel. In fact, both of those are likely true. Those are the limits of all "probabilities" in baseball. There are so many variables that every situation is different and the average has only limited value for a specific decision or player.
"historically what percentage of games were won by the home team carrying various leads or deficits into the top of the ninth.
Leading by 5 - win 99.7% of the time
Leading by 4 - win 98.8% of the time
Leading by 3 - win 98.0% of the time
Leading by 2 - win 94.5% of the time
Leading by 1 - win 86.6% of the time
Tied - win 52.2% of the time
Losing by 1 - win 15.2% of the time
Losing by 2 - win 6.3% of the time
Losing by 3 - win 2.9% of the time
Losing by 4 - win 1.3% of the time
Losing by 5 - win 0.6% of the time"
I think the really interesting part of this data is that it clearly shows that not all runs are created equally. While the data here is only for one particular situation, I think the pattern is likely to apply regardless of the inning.
In a tie game, the first run that scores in the bottom of the 8th raises a team's chances of winning by 66%,more than all the additional runs combined. The second run raises the team's chances by 10% and the third run raises the team's chances by 4%. If the home team starts the bottom of the 8th down by a run, the first run it scores raises its chances of winning by 243%.
On the other hand, when down by two runs, scoring the first run only increases the chances of winning by 141% and when down by 2 runs only 117%.
What this demonstrates, of no surprise to traditionalists, is that in a close game, playing for one run is by far and away the better strategy than playing for a big inning. If you are down by more than a run, then playing for the big inning makes more sense.
One other note. I calculated the increases based on the formula (chances after run scores- chances before run scores)/(chances before run scores). That is to say, the change in the probability a team will win. You an argue whether the percentage increase is more appropriate than just the straight number of additional games a team would win. But the pattern is the same either way. And, of course, these are averages. It may well be that in close games where both teams are scoring runs in bunches, the extra runs become more important. Or that a single run is more important in a pitchers duel. In fact, both of those are likely true. Those are the limits of all "probabilities" in baseball. There are so many variables that every situation is different and the average has only limited value for a specific decision or player.
Sunday, May 23, 2010
Understanding the Psychology of Crackpot Stats
To understand how mob psychology can make common wisdom of complete nonsense consider these claims by Voros McCracken in 2001:
"There is little if any difference among major-league pitchers in their ability to prevent hits on balls hit in the field of play."
"The critical thing to understand is that major-league pitchers don't appear to have the ability to prevent hits on balls in play."
In support of that claim, McCracken goes on to site the following about pitchers' Batting Average on Balls In Play ( (H-HR)/(BFP-HR-BB-SO-HB) ):
"The vast majority of pitchers who have pitched significant innings have career rates between .280 and .290."
Of course McCracken's claim caused a sensation in the statistical community. It greatly simplified the troublesome need to consider team defense when evaluating pitching (FIPS anyone?) It all but eliminated the need to consider pitching when evaluating fielding. As a result, the statistical community developed all sorts of new statistics working from his premise and it has been extended to hitters.
Now you would expect some healthy skepticism of that claim. The obvious question is what was the league BABIP in 2000 when McCracken did his "study?" If the vast majority of successful pitchers, those that got a significant number of outs, are all above average in getting hitters out on balls in play you would probably conclude it is unlikely they have no control over it. But the league BABIP was and is around.300. That is 10-20 points higher than the figure sited for the "vast majority" of successful starting pitchers as identified by McCracken.
Now you might think this was overlooked all these years. It wasn't. That .300 average is sited on the Baseball Prospectus site as the "typical" BABIP for pitchers. In fact, that claim is itself inaccurate. The average (mean) for all pitchers is .300, but the typical (median) pitcher's BABIP is actually considerably higher since the best pitchers face more batters than those with higher BABIP. But either way, the best pitchers have the best BABIP, well above an average pitcher.
As others looked at the numbers and raised troublesome question about McCracken's basic premise finding numerous examples that contradicted it, they were explained as "outliers", ground ball pitchers, etc..Many pitchers had career BABIP far lower than the .280 McCracken claimed and the range of career. BABIP for pitchers goes from as low as .250 up to .350. Very similar to the range in hitter's batting averages. Combined with McCracken's own data showing the vast majority of successful starting pitchers have above average BABIP, you would think pitchers influence over whether a ball goes for a hit had been proven. Successful pitchers are successful, in part, because they get hitters to put the ball in play in ways that make it easy for their fielders to turn them into outs. That certainly is traditional baseball wisdom. And the actual numbers support it.
Nonetheless, McCracken's basic conclusion has become an urban legend. Like any urban legend, once believed, no amount of facts will cause people to abandon their belief in it. None of us like to admit we were enthusiastically wrong.
"There is little if any difference among major-league pitchers in their ability to prevent hits on balls hit in the field of play."
"The critical thing to understand is that major-league pitchers don't appear to have the ability to prevent hits on balls in play."
In support of that claim, McCracken goes on to site the following about pitchers' Batting Average on Balls In Play ( (H-HR)/(BFP-HR-BB-SO-HB) ):
"The vast majority of pitchers who have pitched significant innings have career rates between .280 and .290."
Of course McCracken's claim caused a sensation in the statistical community. It greatly simplified the troublesome need to consider team defense when evaluating pitching (FIPS anyone?) It all but eliminated the need to consider pitching when evaluating fielding. As a result, the statistical community developed all sorts of new statistics working from his premise and it has been extended to hitters.
Now you would expect some healthy skepticism of that claim. The obvious question is what was the league BABIP in 2000 when McCracken did his "study?" If the vast majority of successful pitchers, those that got a significant number of outs, are all above average in getting hitters out on balls in play you would probably conclude it is unlikely they have no control over it. But the league BABIP was and is around.300. That is 10-20 points higher than the figure sited for the "vast majority" of successful starting pitchers as identified by McCracken.
Now you might think this was overlooked all these years. It wasn't. That .300 average is sited on the Baseball Prospectus site as the "typical" BABIP for pitchers. In fact, that claim is itself inaccurate. The average (mean) for all pitchers is .300, but the typical (median) pitcher's BABIP is actually considerably higher since the best pitchers face more batters than those with higher BABIP. But either way, the best pitchers have the best BABIP, well above an average pitcher.
As others looked at the numbers and raised troublesome question about McCracken's basic premise finding numerous examples that contradicted it, they were explained as "outliers", ground ball pitchers, etc..Many pitchers had career BABIP far lower than the .280 McCracken claimed and the range of career. BABIP for pitchers goes from as low as .250 up to .350. Very similar to the range in hitter's batting averages. Combined with McCracken's own data showing the vast majority of successful starting pitchers have above average BABIP, you would think pitchers influence over whether a ball goes for a hit had been proven. Successful pitchers are successful, in part, because they get hitters to put the ball in play in ways that make it easy for their fielders to turn them into outs. That certainly is traditional baseball wisdom. And the actual numbers support it.
Nonetheless, McCracken's basic conclusion has become an urban legend. Like any urban legend, once believed, no amount of facts will cause people to abandon their belief in it. None of us like to admit we were enthusiastically wrong.
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