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| Baseball Articles | 2000 Post-Season Team Reviews |
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2000 Team-by-Team Performance
Reviews
Last updated: March 19, 2001 From January 10th through mid-March, we'll be posting a series of 30 articles, one for each team, that take a close look at the performances of each team and its key players in 2000. (For the publishing schedule, see below.) Our purpose is to shed light on what happened in 2000 so that we might gain a better understanding of what's likely to happen in the future. If a team was down last year, was it because they suffered more than their share of injuries? If they were up, did they get an unusually large number of career years from their players? If so, is it reasonable to expect this to happen again next year? Did the team add or subtract talent in their personnel moves during the year? Or were they just lucky or unlucky? We believe this type of analysis is most revealing if the actual results are compared to an objective set of pre-season expectations. The key word here is "objective". Different people have different expectations about what will happen in the coming season. So whose expectations should we use as our baseline? Certainly not those of general managers and other club officials, because they're renowned for their springtime optimism. How many times have you heard the GM of a last place club talk about being 2-3 players away from contending next year? The reality is that you could add Koufax, Ruth and Bench to some of these teams and they'd still only finish in the middle of the pack. In fairness, we can't blame the GMs for their optimism. After all, part of their job is to create a positive feeling about the team. But that doesn't mean we have to use their public statements as a fair indication of what was most likely to happen. So, rather than rely on pre-season opinions, we're using the results of the computer simulations that we ran back in March, 2000. Why these? Because: - our projections included expected runs scored and allowed by each team, along with their projected totals win-loss record and place in the standings, giving us more material to work with than if we relied on other published predictions - we projected a full set of statistics for over 1500 players, and many other sources don't include as many players or as many stats - our projection methodology takes a lot of factors into account, and does so quite rigorously. To summarize briefly, we start with three years of data from both the major and minor league level, then adjust the player stats for park effects (including minor league parks), league (DH vs non-DH), competitive level (MLB vs AAA vs AA), age, and expected 1999 role. - our simulations used manager profiles for each team that included starting rotations, relief roles, starting lineups against LHP and RHP, platoons, and utility roles, making sure to limit the playing time for guys who were known to be starting the season on the DL. - defense matters in our simulation software, and because all of our players have ratings for range and error rates (along with ratings for many other skills), clubs that improved their defenses will help their pitchers and won-loss records accordingly - our projections are a matter of public record. We published our projected team standings and win-loss records in an article before the season started, and we published our player projections in the form of a Projection Disk for our Diamond Mind Baseball computer game, so nobody can claim we're engaging in revisionist history. We simply want to be able to say that a certain player did better than expected, about as well as expected, or worse than expected, and have that statement mean something. Without a set of projections that are unbiased and reasonably based in fact, such comparisons would be meaningless. If you're interested in learning more about our projection system, check out the following: Diamond Mind projection system Content of the Team ReviewsOf course, every baseball season produces its share of team and player performances that nobody could anticipate, and 2000 was no different. Some players raised their game to a new level, and time will tell whether this was a fluke or an indication of things to come. Others had their games fall off a cliff, and they may or may not get another chance to prove that they can still play the game. So, whether you're evaluating the predictions of a baseball expert or a computer simulation, it would be grossly unfair to expect anything resembling a perfect match of forecast and actual results. Sometimes the forecast is reasonable but the actual results are an anomaly -- like Brady Anderson's 50 homeruns in 1996 -- that will very likely never be repeated. Sometimes the forecast is wrong because it fails to take into account some vital information that was available at the time -- that Sammy Sosa took up baseball relatively late in his youth and might still be improving at an age when most players are past their peak. In our team reviews, we'll be presenting detailed comparisions of three types. Each will begin with a capsule summary of the team's performance relative to our projections. The second section presents projected versus actual statistics for at least a dozen position players, along with our observations about each of these players. The third section does the same for the most important pitchers on the team. And we'll wrap up with a few thoughts about the team's chances for next year. Capsule Summary Projected Actual Runs for 719 665 Runs allowed 843 812 Run margin -124 -147 Wins 70 65 Pythagorean wins 68 65 Placement 5th 5th In this section, we'll compare our team projections for runs scored, runs allowed, run margin, wins, pythagorean wins, and place in the standings. If the term pythagorean wins is foreign to you, it's a concept developed by Bill James that connects runs to wins using the following formula: Runs^^2
Wins = 162 * -----------------------------
Runs^^2 + (Runs allowed)^^2
The notation ^^ means to the power of, so this formula computes the expected winning percentage by dividing the square of runs scored by the sum of the squares of runs scored and runs allowed, then multiplies that percentage by 162 to get the projected win total. In our capsule summaries, the projected wins figure is the average number of wins in five simulated seasons, while the pythagorean wins number is the expected number of wins given the average runs scored and allowed in those simulated seasons. In most cases, the pythagorean wins is a slightly better indicator of the team's true talent level. Position Player ExampleHere's what the McGwire portion of the Cardinals review looked like a year ago. It starts with the player's name, position, and age (as of July 1) and is followed by a comparison of projected and actual performance: Mark McGwire, 1b, age 35AB H 2B 3B HR R RBI HP W IW K SB CS AVG OBP SPC OPS RC Projection StL 521 145 23 0 63 112 131 7 133 22 155 1 0 .278 .429 .685 1.114 161 Prorated StL 517 144 22 0 62 111 130 6 132 21 154 0 0 .279 .429 .681 1.109 159 Actual StL 521 145 21 1 65 118 147 2 133 21 141 0 0 .278 .424 .697 1.120 160 The top line is the projection we made in the spring. The second line is the projection adjusted to the actual number of plate appearances he had in 1999. The third line shows his 1999 stats. You can compare the first two lines to see how much more or less he played than we anticipated. And you can compare the second and third rows to see how his performance compared with our expectations.
Pitcher ExampleHere's what the Randy Johnson portion of the DiamondBacks review looked like last winter. It starts with the player's name, position, and age (as of July 1, 1999) and is followed by a comparison of projected and actual performance: Randy Johnson, Starter, age 35Tm ERA G GS W L S INN H HR BB K AVG OPS Projection Ari 3.00 32 32 16 10 0 234 190 22 77 312 .222 .636 Prorated Ari 3.00 36 36 18 11 0 263 214 25 87 351 .222 .636 Actual Ari 2.48 35 35 17 9 0 272 207 30 70 364 .208 .601 The playing time adjustment for pitchers is based on batters faced. Some pitchers were projected as relievers but were used as starting pitchers instead. In those cases, their innings went up but their games played went down. In these cases, we simply leave the G and GS entries blank in the Prorated line because it would be meaningless to say that Ron Villone's prorated games played total was 102. It's not unusual for starting pitcher to exceed our projected playing time figures if he stays healthy all year. We've been projecting starters for 32 starts to allow for the injuries and fatigue that affect many of them each year. For that reason, we almost never project anyone to win more than 18 games. If a pitcher stays healthy, pitches well, and gets decent run support from his offense, he'll almost always win more games than we project. OPS is defined in the McGwire example above. Publication ScheduleWe expect to publish three team reviews per week, usually on Monday, Wednesday and Friday, moving through the teams more or less in alphabetical order. As new reviews are posted, we'll activate the links in the following list:
Copyright © 2001. Diamond Mind, Inc. All rights reserved. |
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