|
|
| Baseball Articles | 1998 Post-Season Reviews |
|
1998 Team-by-Team Performance
Reviews
By Tom Tippett and Tom Ruane From November 30 through mid-March, we've posted 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 1998. (To find out when we published the reviews for specific teams, see below.) Our purpose is to shed light on what happened in 1998 so that we might gain a better understanding of what's likely to happen in the future. If a team was down this past 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. It's very easy to forget how things looked just seven months ago, before we knew that Sammy Sosa would hit 66 homers, Randy Johnson would be awful at the start of the year and brilliant after being traded to Houston, the Marlins would unload what little talent they had left, and Orlando Hernandez would go from raft trip survivor to superior starting pitcher in just a few months. Choosing a BaselineBecause our focus is going to be on comparisons between expected and actual results, we must start with a reasonable set of expectations. What's reasonable? Certainly not the public statements 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 so they can sell tickets. So, rather than rely on pre-season opinions, we'll use the results of our March/98 computer simulations as our yardstick. 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 we'd have if we relied on other published predictions - we projected a full set of statistics for over 1100 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 1998 role. - our simulations used profiles for each team that included starting rotations, relief roles, starting lineups against LHP and RHP, platoons, and utility roles for each team, making sure to limit the playing time for guys who were known to be starting the season on the DL. - defense matters in the 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 Diamond Mind Baseball, so nobody can claim we're engaging in revisionist history. - we developed them, so we don't need to ask anyone for permission to use them, and that makes life a lot simpler.
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. Content of the Team ReviewsAlthough we'll be using our own projections as the baseline, our purpose is not self-promotion. A lot of our projections were accurate, but some were not. Where we missed the mark, we'll do two things. First, we'll take another look and see if the projection really was a reasonable one, and we'll come clean if there were factors that should have helped us foresee what actually happened in 1998. Second, we'll see if we can learn something from this example that will help us improve our projection system for next year. Of course, every baseball season produces its share of team and player performances that nobody could anticipate, and 1998 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 a fluke (e.g. 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 (e.g. 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). But it is fair to expect that the projections are relatively close more often than they're way off, so we'll be presenting detailed comparisions of three types, capsule summaries for the teams, projected versus actual hitting for 12-14 key position players per team, and projected vs actual pitching stats for 8-9 key pitchers per team. The next three sections provide an example of each, with an explanation of any terms you might not be familiar with. 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 ExampleJay Buhner, RFAB H 2B 3B HR R RBI HP W IW K SB CS AVG OBP SPC OPS RC Projection SEA 492 120 20 1 36 89 106 5 84 4 142 0 0 .244 .357 .508 .865 90 Prorated SEA 240 59 10 0 18 43 52 2 41 2 69 0 0 .244 .357 .508 .865 44 Actual SEA 244 59 7 1 15 33 45 1 38 0 71 0 0 .242 .344 .463 .807 42 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 1998. The third line shows his 1998 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 ExamplePedro Martinez, SPERA G GS W L S INN H HR BB K AVG Projection BOS 2.80 32 32 17 6 0 238 189 21 73 266 .218 Prorated BOS 2.80 32 32 17 6 0 236 187 21 72 264 .218 Actual BOS 2.89 33 33 19 7 0 234 188 26 67 251 .217 The playing time adjustment for pitchers is based on batters faced. It is, of course, no coincidence that we picked this example. We chose it to illustrate a fundamental principle in our projection system -- that it's possible to make accurate adjustments for league and park effects. In this case, our projection was based on a weighted average of Pedro's Montreal stats from 1995-7, adjusted for the fact that in 1998 he would be (a) facing the DH, (b) pitching half his games in Fenway Park instead of pitcher-friendly Olympic Stadium, and (c) a year older and better. In this case, our league, park and age adjustments yielded a near-perfect forecast. Publication ScheduleWe expect to publish two team reviews per week, one each on Monday and Friday. We'll be alternating between leagues, going more or less in alphabetical order within each league. As new reviews are posted, we'll activate the links in the following list:
|
 |
