One Evil Empire was dispatched by another on Tuesday night, as Boston dismissed the Yankees in a somewhat ho-hum game. And last night the Dodgers got by the Cardinals in a tense, gripping affair that was only decided on the game's final pitch. Which took place four hours and fifteen minutes after the first pitch. It was wonderful, dramatic entertainment if you had the endurance required to stick with it to the end. But now we have an Elite Eight.
The ALDS kicks off this afternoon with the White Sox in Houston, two teams managed by guys even older than me. Cool. The Red Sox and Rays get underway in Tampa Bay later tonight. The Other League gets started on Friday.
So why don't I make a fool of myself and venture some predictions?
Boston-Tampa Bay
The Red Sox are irritating, streaky, and unpredictable. But the Rays are easily the best team in the league, and by a considerable margin. Rays in four
Chicago-Houston
Two ancient managers (who apparently don't like each other too much) will get a lot of the attention. But the real story is the classic clash between an irresistible force (the Houston offense, best in the league) and an immovable object (the White Sox pitching, also best in the league.) It's always interesting when that happens. Astros in five
Atlanta-Milwaukee
The Braves have a solid team but the main reason they're in this thing is because they're the only good team in their weak-ass division. They'll be in tough against what might be the most frightening pitching rotation in the post-season. It's one thing to win the NL East without your best player. This will be harder. Brewers in three
Dodgers-Giants
These teams have never met in actual post-season play, but they do have a history. Oh, they have a history. One than spans an entire continent and more than a century of baseball. And some of the most memorable parts of that history have indeed come after what supposed to be the last day of the regular season. There was a rather playoff famous series to settle a tie between these teams at the end of the 1951 season. There was another at the end of the 1962 season. The Giants were the winners on both occasions, and got to go to the World Series and get beat by the Yankees. I think the Dodgers are the better team and they were unlucky to finish second. But the Giants are really good as well and the Dodgers are pretty banged up. Giants in five
Matchups!
Thursday
Chicago (Lynn 11-6, 2.69) at Houston (McCullers 13-5, 3.16)
Boston (Rodriguez 13-8, 4.74) at Tampa Bay (McClanahan 10-6, 3.43)
Friday
Chicago (Giolito 11-9, 3.53) at Houston (Valdez 11-6, 3.14)
Atlanta (Morton 14-6, 3.34) at Milwaukee (Burnes 11-5, 2.43)
Boston (Some Guy ?=?, ?.??) at Tampa Bay (Baz 2-0, 2.03)
Los Angeles (Buehler 16-4, 2.47) at San Francisco (Webb 11-3, 3.03)
And there will be more...
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I mentioned the other day that I had moved beyond Pythagoras when it came to evaluating a team's season, because I am so very, very progressive. So let me explain myself! (He never does anything else, they wearily murmur.)
We are more or less agreed that sometimes a team's W-L record doesn't tell their story clear and true. And when it doesn't, we know why. It's because the team's record in either one-run games or blowouts (or both) varies somehow from their performance the rest of the time.
These days even ESPN's home page includes Runs Scored and Allowed and Run Differential. As if that told the story (after all, a run differential of 100 runs in Dodger Stadium is very, very different from the same thing in Coors Field.)
From a team's Runs Scored and Allowed we extrapolate we have come to call a team's Pythagorean W-L record. This is based entirely - entirely - on the relationship between totals Runs Scored and Allowed. As I suppose is generally known, there are two fairly common methods of making that calculation: one involves squaring the numbers involved, while the other uses a component, often 1.83, instead. Whichever you use is entirely up to you. Let me hear no talk of accuracy. Please. Whichever formula you choose generates a fiction, an imaginary W-L record. One fantasy is not more accurate than another. It's all a matter of which one you like best, or which one suits your needs. (As I was generally trying to identify real seasons that didn't tally closely with the actual results, I very much preferred the traditional formula that squared the numbers. If you're looking for seasons that deviate from one's reasonable expectations you don't want to use a method that generates those deviant seasons willy-nilly. Which is what using the component will do.)
Now there are two problems with using one of the Pythagorean formulae to generate a W-L record, as imaginary as it may be.
The first problem, which I regard as as less important but still an issue, is with the blowout games that constitute a significant part of any team's season. It's not that it makes no difference at all whether you win by 6 runs or 12 - but I do suspect that this mostly tells you something about choices made by the losing team when a game gets out of hand rather than anything about the quality of either team. So I think that while a team's record in blowout games is very significant, I don't think a team's Runs Scored and Allowed in those games is nearly as important.
And what this means is that the raw data - the Runs Scored and Allowed - that is being fed into the Pythagorean formula of your choice creates its own distortions right from the jump.
But I think that's a fairly minor matter. The other issue I think is much more important. And it's pretty obvious. And of course it involves my own Great White Whale. But nevertheless, here we go! Because baseball teams play lots of games that are decided by a single run. And even if you do believe that Run Differential and the Pythagorean formula will give you an accurate idea of a team's quality, you still can't apply it to one-run games. You simply can't do that.
Because that's not how one-run games work.
It just isn't. You can't apply a Pythagorean formula to those games. Because in one-run games, the impact of random chance is sufficient to overcome the impact of team quality. You may not be able to win a game by ten runs thanks to a lucky bounce. But you can definitely win by one-run.
This is why the effect of one-run games is to drag every team to the centre. It drags everyone towards .500 - it lifts the bad teams and it lowers the good teams. That's what it does. This is a Law.
This doesn't quite mean that we should set a .500 record in one-run games as a team's expected outcome. The better teams actually do play better in one-run games than the bad teams. It's just that any single season is much, much too short a sample for that result to manifest itself. It would be exactly like assessing a hitter's season on 30 random plate appearances. We need the whole season, we need the 700 plate appearances to have a decent idea. As it happens, that's about how many one-run games it takes for a team's quality to begin to consistently affect that team's record in one-run games.
And even when we have that many games (in truth, the number needed might be closer to 1,000 games) - a team's record in one-run games still isn't going to match whatever Pythagorean projection we had come up with. Because one-run games are still going to drag teams towards .500, however good or bad they may be. That's what they do. It's just that if you play enough of those games, the effect won't be as pronounced. Given enough games, an equilibrium between these two forces is reached, between the the relentless pull towards .500 and the actual quality of the teams. The effect is always present, and it's generally reliable: to state it crudely, the .600 teams will play something like .550 ball in one run games, the .550 teams will play something like .530 ball in one-run game, the .450 teams will play something .480 ball in one-run games. And so on.
And so I developed a very, very simple formula to generate a team's projected record in one-run games. It's as consistent as I could hope for once the sample gets large enough. Once the sample gets large enough, the formula actually works (I can hardly believe it myself!) I don't need to worry about the blowouts. I don't even have to worry about total Runs Scored and Allowed. Simply adjusting the outcomes of one-run games turns out to be enough to make the actual results match up with the expected results.
Tampa Bay went 20-25 in their one-run games. They played .684 ball (80-37) the rest of the time. So:
1) Multiply their 45 one-run games by their .684 winning percentage in their Other Games. You get 30 (because I'm using the INTEGER function, I don't want to mess around with 30.7 - hey, you either win or you don't!)
2) Multiply those same 45 games by .500 - after all, dragging every team towards .500 is precisely what one-run games do. It's what they're for. This time we get 22 (the INTEGER function strikes again, lowering 22.5 to 22).
3) Add the two figures - 30 and 22 - and divide them by 2. Easy enough, it's 26.
Voila! Tampa Bay's expected W-L record in one-run games is 26-19 instead of the 20-25 inflicted on them by Cold Reality. We are free, if we like, to regard this as more reflective of that team's quality than What Actually Happened.
Repeat 29 times. Or do what I did, Copy and Paste the formula. (I had a blank cell waiting for this calculation in 2,789 other seasons. That would have been a lot of data entry.)
And these would be your modified standings. (The two Times columns near the end give the results of the two calculations carried out on the team's one-run games; the final pair gives their new fantasy record in those games.)
FANTASY REALITY ONE RUN GAMES OTHER GAMES (OG) Times Times FANTASY ONE-RUNThis past season, eight of the 30 teams would see a change of more than five games in their W-L record. As you can see, the AL East, the Al West, and the NL West all end up with a slightly different pecking order. Boston, New York, and San Francisco all did better in the one-run games played in the Real World, while the A's and Dodgers did worse. This was enough to vault the Giants past the Dodgers, the Red Sox and Yankees past the Blue Jays. Because in baseball, the real world is stranger than fantasy. Otherwise, the Giants would have faced off with the Cardinals last night. Boston, New York, and Oakland would have had to fight among themselves to see who played Toronto in the AL Wild Card.
W L PCT GBL W L PCT W L PCT W L PCT OG % 0.5 W L
Tampa Bay 106 56 .654 - 100 62 .617 20 25 .444 80 37 .684 30 22 26 19
Toronto 92 70 .568 14 91 71 .562 15 15 .500 76 56 .576 17 15 16 14
Boston 89 73 .549 17 92 70 .568 26 18 .591 66 52 .559 24 22 23 21
NY Yankees 89 73 .549 17 92 70 .568 28 20 .583 64 50 .561 26 24 25 23
Baltimore 54 108 .333 52 52 110 .321 13 24 .351 39 86 .312 11 18 14 23
Chicago 98 64 .605 - 93 69 .574 18 24 .429 75 45 .625 26 21 23 19
Cleveland 82 80 .506 16 80 82 .494 17 22 .436 63 60 .512 19 19 19 20
Detroit 76 86 .469 22 77 85 .475 23 23 .500 54 62 .466 21 23 22 24
Kansas City 71 91 .438 27 74 88 .457 21 19 .525 53 69 .434 17 20 18 22
Minnesota 67 95 .414 31 73 89 .451 25 19 .568 48 70 .407 17 22 19 25
Houston 96 66 .593 - 95 67 .586 21 19 .525 74 48 .607 24 20 22 18
Oakland 89 73 .549 7 86 76 .531 23 27 .460 63 49 .563 28 25 26 24
Seattle 83 79 .512 13 90 72 .556 33 19 .635 57 53 .518 26 26 26 26
LA Angels 69 93 .426 27 77 85 .475 25 14 .641 52 71 .423 16 19 17 22
Texas 58 104 .358 38 60 102 .370 18 21 .462 42 81 .341 13 19 16 23
Atlanta 93 68 .578 - 88 73 .547 26 31 .456 62 42 .596 33 28 30 27
Philadelphia 79 83 .488 14.5 82 80 .506 30 25 .545 52 55 .486 26 27 26 29
NY Mets 78 84 .481 15.5 77 85 .475 31 35 .470 46 50 .479 31 33 32 34
Miami 68 94 .420 25.5 67 95 .414 21 29 .420 46 66 .411 20 25 22 28
Washington 64 98 .395 29.5 65 97 .401 22 26 .458 43 71 .377 18 24 21 27
Milwaukee 93 69 .574 - 95 67 .586 21 15 .583 74 52 .587 21 18 19 17
St.Louis 87 75 .537 6 90 72 .556 26 19 .578 64 53 .547 24 22 23 22
Cincinnati 81 81 .500 12 83 79 .512 24 20 .545 59 59 .500 22 22 22 22
Chicago Cubs 70 92 .432 23 71 91 .438 24 27 .471 47 64 .423 21 25 23 28
Pittsburgh 58 104 .358 35 61 101 .377 20 22 .476 41 79 .342 14 21 17 25
LA Dodgers 111 51 .685 - 106 56 .654 24 24 .500 82 32 .719 34 24 29 19
San Francisco 104 58 .642 7 107 55 .660 31 17 .646 76 38 .667 32 24 28 20
San Diego 81 81 .500 30 79 83 .488 21 26 .447 58 57 .504 23 23 23 24
Colorado 73 88 .453 37.5 74 87 .460 24 25 .490 50 62 .446 21 24 22 27
Arizona 59 103 .364 52 52 110 .321 10 31 .244 42 79 .347 14 20 17 24
And Seattle finishes a respectable enough 83-79, slipping one spot to third place. The Mariners were in fact the team that really set me off on this adventure, this mad pursuit of an untamed fowl. Seattle's raw Runs Scored and Allowed aren't remotely impressive. If you just apply one of the Pythagorean formulae to it, the team ends up with a losing record. The one-run games were very good to them indeed - they played lots of them and they won 14 more of them than they lost. That was largely good luck, pure and simple. But the Mariners also won more games than they lost the rest of the time as well (57-53.) Which may be why I have some trouble thinking of the 2021 Mariners as losers. They may not be a 90 win quality team. But losers? I think not.
