A slugging scion or an injury-prone first baseman on the wrong side of 30? Marc investigates.
Derrek Leon Lee, the nephew of former major leaguer Leron Lee, was drafted fourteenth overall by the San Diego Padres all the way back in 1993 at the age of 17. (On the random side of things, Derrek's father is Leon Lee, the scout who actually discovered Hee-Seop Choi. Choi and Lee were traded for each other prior to the 2004 season.) Lee had received a full scholarship to the University of North Carolina to play basketball, but instead chose to head straight to the minor leagues and try his luck at baseball, signing with the Padres and heading to the Arizona Padres for his professional debut:
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Even Alexis Gomez came from somewhere (Kansas City). Kevin tells us how the Tigers and A's acquired the rest of their postseason difference-makers.
\nMathematically, leverage is based on the win expectancy work done by Keith Woolner in BP 2005, and is defined as the change in the probability of winning the game from scoring (or allowing) one additional run in the current game situation divided by the change in probability from scoring\n(or allowing) one run at the start of the game.';
xxxpxxxxx1160846402_18 = 'Adjusted Pitcher Wins. Thorn and Palmers method for calculating a starters value in wins. Included for comparison with SNVA. APW values here calculated using runs instead of earned runs.';
xxxpxxxxx1160846402_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.';
xxxpxxxxx1160846402_20 = 'The number of double play opportunities (defined as less than two outs with runner(s) on first, first and second, or first second and third).';
xxxpxxxxx1160846402_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.';
xxxpxxxxx1160846402_22 = 'Winning percentage. For teams, Win% is determined by dividing wins by games played. For pitchers, Win% is determined by dividing wins by total decisions. ';
xxxpxxxxx1160846402_23 = 'Expected winning percentage for the pitcher, based on how often\na pitcher with the same innings pitched and runs allowed in each individual\ngame earned a win or loss historically in the modern era (1972-present).';
xxxpxxxxx1160846402_24 = 'Attrition Rate is the percent chance that a hitters plate appearances or a pitchers opposing batters faced will decrease by at least 50% relative to his Baseline playing time forecast. Although it is generally a good indicator of the risk of injury, Attrition Rate will also capture seasons in which his playing time decreases due to poor performance or managerial decisions. ';
xxxpxxxxx1160846402_25 = 'Batting average (hitters) or batting average allowed (pitchers).';
xxxpxxxxx1160846402_26 = 'Average number of pitches per start.';
xxxpxxxxx1160846402_27 = 'Average Pitcher Abuse Points per game started.';
xxxpxxxxx1160846402_28 = 'Singles or singles allowed.';
xxxpxxxxx1160846402_29 = 'Batting average; hits divided by at-bats.';
xxxpxxxxx1160846402_30 = 'Percentage of pitches thrown for balls.';
xxxpxxxxx1160846402_31 = 'The Baseline forecast, although it does not appear here, is a crucial intermediate step in creating a players forecast. The Baseline developed based on the players previous three seasons of performance. Both major league and (translated) minor league performances are considered.
Dan backs up and provides an overview on what this summer's findings tell us about team-level baserunning, and what we can learn about baserunning in general.
When last we were together, we added up the various baserunning metrics we've been formulating all summer to come up with a total number of theoretical runs contributed on the bases for individual players. This included runs from advancing on ground and air outs, advancing on hits, and runs contributed from stolen base attempts (and pickoffs).
Jason Giambi and Ken Griffey Jr. won the Comeback Player of the Year Award in their leagues as voted by the fans. Is there a more objective way of handing out the award?
This bounceback comes in three steps: the first peak, the valley and the second peak. In order for a player to qualify for our 2005 Objective Rebound Award (or ORA, because we love acronyms and we're hoping that the winner has that special something about him), the second peak should come in 2005. For the initial run, we're only going to consider players whose first peak came in 2003 and valley came in 2004. Later, we'll open it up to look at larger windows, up to five years from peak to peak. Although the subjective Comeback Awards are given out by league, we'll make no such distinction here, to avoid having to split playing time across leagues.
Overall, the level of the rebound is measured by the distance dropped plus the distance gained back, or (Peak 1 VORP - Valley VORP) + (Peak 2 VORP - Valley VORP). Although this method would leave us open to having some rebounds that appeared large because of one large peak on either end, there are so many seasons in question that the highest rebounds end up having large peaks on each end. Once we start to limit the sample sizes down to three consecutive years ending in 2005, you get some interesting "rebounds." Although we could place limits on these, it would take arbitrary cut-offs, and since it's an inexact science and simply a toy at this point, we can eliminate these by sight as they come up.
Will Carroll and Mike Carminati wonder if swinging and missing is that big of a deal, and their findings may surprise you.
Just as an out-of-the-blue bolt of plate discipline presaged Sosa's assent, his decline might have been predicted by his tendency to swing and miss that haunted him even in his stellar 1999 season. Sosa swung at and missed 475 pitches in his record-setting 1999 campaign. This is the highest total for any major-league batter over the last five seasons and isn't the "swing and a miss!" call of the announcer the cruelest fate in baseball? But what does it mean in the greater scheme?
Does having a tendency to swing and miss more than most impair a batter's productivity as we have been told since Little League? Do batters with better batting eyes tend to be more productive than the average batter? Is it better to be patient at the plate or go for the first pitch you can hit? Does this data tell us anything new and could that be used to help build a better team or find successful players?
Should you panic if your stud players have suffered through a terrible April? Erik Siegrist has the answer.
Is it true though? Is a slow start really just a statistical blip which will sort itself out over the next five months? It's never a bad idea to challenge conventional wisdom, and every self-respecting Baseball Prospectus writer needs only the feeblest of excuses to start playing around with numbers. So let's test the hypothesis that production comes in fits and spurts, not steadily over the course of the season, and see if there's anything that can be learned in the process.
Productive outs are a small part of offense that, at the extremes, can be worth a win a season. Making them, however, does not appear to be a repeatable skill for players.
This past April, ESPN.com's Buster Olney introduced a new statistic, Productive Out Percentage, to the baseball public. Working with the Elias Sports Bureau, Olney attempted to create a metric that would support the idea that productive outs were a key element in winning baseball. While the sabermetric community swiftly debunked Olney's creation as flawed--there's no relationship between the quality of a team's offense and its tendency to make productive outs--one question remained unanswered: how valuable are productive outs relative to other offensive events?
Productive outs, such as ground balls that advance runners, have a small benefit relative to outs that do not, such as strikeouts and pop-ups. Certainly, moving a runner over is preferable to not doing so, and over the course of 162 games, occasional bases gained can add up. What they add up to has never been quantified, but thanks to the new widespread availability of play-by-play data, however, we now have the opportunity to do so.
Are the Angels the favorites in the AL West, according to PECOTA? How hard did Dusty work Cub starters in '03? And do the Tigers have a better option than playing Alex Sanchez every day? All this and much more news from Anaheim, Chicago, and Detroit in your Thursday edition of Prospectus Triple Play.
If we could only get that "Ready to Rumble" guy to read this...: Without further ado, it is our great pleasure to introduce the spawn of big, bad projection system PECOTA and the brand new BP depth charts: THE PROJECTED AL WEST STANDINGS!