Once more unto the breach, dear friends, once more!
Yup, I've dusted off the Big Honking Database and propose once more to look at One-Run Games in general and the hometown heroes in particular.
This one's for BlueJayWay, obviously.
Before we get to the Blue Jays, we're going to review a few theoretical and data issues. For our purposes here, we're confining ourselves to the years 1900-2015. These are seasons for which I happen to have every team's record in one-run games in handy, easy-to-manipulate form. We're looking at 2414 seasons, which seems like a reasonably large sample. It includes 376,963 games. A lot of baseball. Just how many of those games were decided by a single run? Glad you asked - it's 114,242, which is just over 30 per cent.
The crucial point to understand before looking at one-run games is this: the effect of these games is always, always, always to pull teams towards .500. One run games drag the better teams down towards .500. They lift the bad teams up towards .500. This is the One Run Fundamental. It is a Law of the Game.
Let me break those 2414 seasons into digestible chunks, that you might see this for yourselves.
Since 1900, there have been ten - that's just 10 - teams that have played .700 baseball or better over the course of a season, from the 1902 Pirates to the 2001 Mariners. Those teams played a total of 1530 games, and won 1100 of them. Their overall winning percentage was .719. They played 393 one-run games (just 25.7%), and in those games they went 256-137 - which is a .651 winning percentage. Which is really, really good. But obviously, it's nowhere near .719, and in games that were decided by more than one run, those same ten teams went 844-293. And that's a .742 winning percentage. The overall record was dragged down - and dragged down quite a bit - by their record in close games. They were .091 worse in one-run games than in the rest of their games.
It happens at the top, and it happens at the bottom. There have been twenty teams whose winning percentage couldn't even crack .300, from the 1904 Senators to the 2003 Tigers. Those teams played .276 ball (843-2214) - but they did much better in one run games (331-578, .364) than in the rest of them (512-1636, .238). They were .126 better in one run games. My next group (.300-.349) improved by .095, the next group by .075, and so on and so forth.
And that's the basic pattern. The farther away a team is from .500, the larger the pull effect of one-run games in dragging them back towards .500. Which makes sense on an intuitive level as well. A team as awful as the 2003 Tigers - if by some weird chance they were to win a game, odds are they'd just barely win it. (They actually had a winning record, 19-18, in one-run games. While going a gruesome 24-101 in their other contests.) And similarly, a team as awesome as the 1927 Yankees - if you do manage to beat them, it's probably not going to be by a lot. And Ruth's Yankees went 24-19 in one-run games. They were 86-25 the rest of the time.
Behold! A Data Table!
As you can see, the pattern is pretty dependable. The only group that doesn't fit perfectly includes the 133 teams who played between .600 and .624 ball. Those teams had results in one-run games that were just a little bit worse than all this would lead you to expect. They played 6195 one run games, and I would have expected them to win about 3560 of them (roughly .575 ball) - they actually went 3488-2707, which is just .563 ball- in other words, it's exactly the same as the difference between going 93-69 and going 91-71.
This, by the way, is why all the game's greatest and most successful managers have worse records in one-run games than they do the rest of the time. Having a worse record in one-run games than you do in the rest of your games is actually a characteristic of any group of good teams, and those are the types of team that were managed by McCarthy and McGraw and Weaver.
Anyway, that's the pattern, and let me run off a small tangent for the rest of this paragraph. Here's my question - how many games do we need before the sample size becomes large enough for the One Run Fundamental to show itself. It's true that all of these samples behave roughly as you would expect them to. The smallest sample here consists of 10 seasons, 1530 overall games, 393 one-run games. But I still suspect that even that number of games is just a little on the small size.
I do think we can be pretty damn sure that a single season, and the 30 or 40 one-run games it might include, is nowhere near a large enough sample for the One-Run Fundamental to assert itself - it's about the same as... oh, 30 or 40 at bats over the course of the year. In which anything can happen. It's a little like Josh Donaldson going 5-35 back in May. He's still Josh Donaldson.
So what's the biggest factor in one-run games?
Well, obviously the quality of the team is a pretty large factor. The best teams really do have the best records in one-run games.
But the closer a game gets, the greater the chance that Random Circumstance can determine the outcome. And Luck doesn't know anything about quality. Luck is a flip of a coin, and the odds are the same for everyone. Heads or tails, win or lose, it's 50-50.
Let's look at the teams that played .700 ball or better. They played .651 ball in one-run games. In an average season, they'd have played about 42 such games, so it's as if they went 27-15 in those games. But we would have expected them to go 31-11, had they played one-run games the same way they played the rest of them. It's almost as if half the games were decided by the team's quality (their .742 winning percentage) and the other half were decided by a coin flip (which ought to be .500).
Half of the one-run games are effectively decided by a coin flip?
Gulp. Because if you flip that coin 3000 times, you'll surely see heads come up 1500 times. But if you only flip it 30 or 40 times? Weird, weird things can happen.
Which brings us, at last to the Toronto Blue Jays.
From that snowy April day in 1977 through this year's All-Star Break, the Jays have played 6,284 games and they've had a losing record for almost all of that time. (They were briefly above .500 from September 1993 through May 1994, and intemittently after that for the next year. But the franchise has had a losing record every day since May 1995. Not to mention the sixteen years before the second championship.) At this particular moment, they got 3129 wins and 3155 losses, a .498 percentage. We would expect them to have a record in one-run games that's very close to that. Maybe a game or two better.
They don't. They're 874-926 (.486) in one-run games. It's not that big a deal - one more loss, one fewer win every other year or so. Here are the raw numbers:
So what was the most disturbing experience, when did the team lose way more one-run games than you would expect from a team of that general quality? That would be the 2015 team, who played .349 ball (15-28) in one-run games and .655 ball (78-41) the rest of the time. (Using my Coin Flip logic, they went roughly 15-6 on Quality, but the coin came up Tails 20 times in a row when they were calling Heads. Yikes.
The next worse? Meet this year's team, playing .375 ball (9-15) in one-run games, and .627 ball (42-25 the rest of the time.
Next worse? The 2005 squad, who played the one-run games at a .340 clip (16-31), while playing .557 ball.
What do these teams have in common? Well, there's ownership. And batting practice pitcher Jesus Figueroa. And... well, let's look at the managers, shall we?
This requires a bit of digging through the Game Logs, as the Jays made mid-season managerial changes in 1989, 1997, 2002, 2004, and 2008. And while Cito Gaston was the manager of the 1991 team that went 91-71, Gaston went into Mt Sinai Hospital with a herniated disk on August 21 of that year and was away from the ballpark for just over a month. Gene Tenace managed the games in his absence.
This time, instead of running through the data in chronological order, we'll rank the teams by their proficiency in one-run games. And by proficiency I don't mean mere winning percentage - I mean winning percentage in one-run games compared to winning percentage of the other games. Which Toronto team had the most good fortune in the close ones?
And finally, let's just add up the manager's records and see how they've done in one-run games.
In my view, all of these represent Small Samples. A few tidbits, nonetheless...
The terrible teams managed by Hartsfield and Mattick both posted significantly better results in one-run games, exactly as you would expect them to do. Mattick's teams helped themselves a little more than you might expect.
Bobby Cox's excellent teams didn't lose much to the coin flip at all...
Whereas Jimy Williams' teams were pretty bad in close games. His teams were even better than Cox's teams in the other games, but everything went to hell in one-run games.
Gaston's first tour is remarkable - the exact same winning percentage (.518) in all kinds of games..
Jim Fregosi, Tim Johnson, and Buck Martinez all did quite well in one-run games, in their brief times in charge.
But since Martinez was fired, everything has gone to hell. All five managers (counting Gibbons twice) have seen significantly worse results in one-run games than you would expect. Tosca, Gibbons Mark I, and Farrell were all disappointing. Gaston Mark II was awful, twice as bad as that Group of Three. And Gibbons Mark II - great gosh almighty, he's been twice as bad as that, some twenty-seven shades of godawful.
Something is clearly wrong with the coins around here. These last ten years or so have been weird. Really, really weird.
Anyway - BlueJayWay.... we feel your pain.
Yup, I've dusted off the Big Honking Database and propose once more to look at One-Run Games in general and the hometown heroes in particular.
This one's for BlueJayWay, obviously.
Before we get to the Blue Jays, we're going to review a few theoretical and data issues. For our purposes here, we're confining ourselves to the years 1900-2015. These are seasons for which I happen to have every team's record in one-run games in handy, easy-to-manipulate form. We're looking at 2414 seasons, which seems like a reasonably large sample. It includes 376,963 games. A lot of baseball. Just how many of those games were decided by a single run? Glad you asked - it's 114,242, which is just over 30 per cent.
The crucial point to understand before looking at one-run games is this: the effect of these games is always, always, always to pull teams towards .500. One run games drag the better teams down towards .500. They lift the bad teams up towards .500. This is the One Run Fundamental. It is a Law of the Game.
Let me break those 2414 seasons into digestible chunks, that you might see this for yourselves.
Since 1900, there have been ten - that's just 10 - teams that have played .700 baseball or better over the course of a season, from the 1902 Pirates to the 2001 Mariners. Those teams played a total of 1530 games, and won 1100 of them. Their overall winning percentage was .719. They played 393 one-run games (just 25.7%), and in those games they went 256-137 - which is a .651 winning percentage. Which is really, really good. But obviously, it's nowhere near .719, and in games that were decided by more than one run, those same ten teams went 844-293. And that's a .742 winning percentage. The overall record was dragged down - and dragged down quite a bit - by their record in close games. They were .091 worse in one-run games than in the rest of their games.
It happens at the top, and it happens at the bottom. There have been twenty teams whose winning percentage couldn't even crack .300, from the 1904 Senators to the 2003 Tigers. Those teams played .276 ball (843-2214) - but they did much better in one run games (331-578, .364) than in the rest of them (512-1636, .238). They were .126 better in one run games. My next group (.300-.349) improved by .095, the next group by .075, and so on and so forth.
And that's the basic pattern. The farther away a team is from .500, the larger the pull effect of one-run games in dragging them back towards .500. Which makes sense on an intuitive level as well. A team as awful as the 2003 Tigers - if by some weird chance they were to win a game, odds are they'd just barely win it. (They actually had a winning record, 19-18, in one-run games. While going a gruesome 24-101 in their other contests.) And similarly, a team as awesome as the 1927 Yankees - if you do manage to beat them, it's probably not going to be by a lot. And Ruth's Yankees went 24-19 in one-run games. They were 86-25 the rest of the time.
Behold! A Data Table!
OVERALL ONE-RUN GAMES OTHER GAMES
Record No. of Teams GPL W L PCT GPL W L PCT GPL W L PCT
.700 plus 10 1,530 1,100 430 .719 393 256 137 .651 1,137 844 293 .742
.650-.699 43 6,556 4,394 2,162 .670 1,931 1,158 773 .600 4,760 3,236 1,389 .700
.625-.649 68 10,576 6,723 3,853 .636 3,106 1,837 1,269 .591 7,470 4,886 2,584 .654
.600-.624 133 20,686 12,651 8,035 .612 6,195 3,488 2,707 .563 14,491 9,163 5,328 .632
.575-.599 199 30,987 18,235 12,752 .588 9,305 5,230 4,075 .562 21,682 13,005 8,677 .600
.550-.574 233 36,253 20,401 15,852 .563 10,983 5,898 5,085 .537 25,270 14,503 10,767 .574
.525-.549 325 51,352 27,572 23,780 .537 15,589 8,103 7,486 .520 35,763 19,469 16,294 .544
.500-.524 258 40,532 20,677 19,855 .510 12,445 6,252 6,193 .502 28,085 14,425 13,662 .514
.475-.499 238 37,403 18,166 19,237 .486 11,472 5,655 5,817 .493 25,931 12,511 13,420 .482
.450-.474 256 39,927 18,439 21,488 .462 12,149 5,792 6,357 .477 27,778 12,647 15,131 .455
.425-.449 202 31,600 13,823 17,777 .437 9,746 4,529 5,217 .465 21,854 9,294 12,560 .425
.400-.424 173 27,129 11,166 15,963 .412 8,157 3,687 4,470 .452 18,972 7,479 11,493 .394
.375-.399 113 17,554 6,800 10,754 .387 5,320 2,253 3,067 .423 12,234 4,547 7,687 .372
.350-.374 62 9,520 3,446 6,074 .362 2,828 1,172 1,656 .414 6,692 2,274 4,418 .340
.300-.349 81 12,500 4,145 8,355 .332 3,712 1,479 2,233 .398 8,788 2,666 6,122 .303
.000-.299 20 3,057 843 2,214 .276 909 331 578 .364 2,148 512 1,636 .238
2414 377,162 188,581 188,581 .500 114,240 57,120 57,120 .500 263,055 131,461 131,461 0.500
As you can see, the pattern is pretty dependable. The only group that doesn't fit perfectly includes the 133 teams who played between .600 and .624 ball. Those teams had results in one-run games that were just a little bit worse than all this would lead you to expect. They played 6195 one run games, and I would have expected them to win about 3560 of them (roughly .575 ball) - they actually went 3488-2707, which is just .563 ball- in other words, it's exactly the same as the difference between going 93-69 and going 91-71.
This, by the way, is why all the game's greatest and most successful managers have worse records in one-run games than they do the rest of the time. Having a worse record in one-run games than you do in the rest of your games is actually a characteristic of any group of good teams, and those are the types of team that were managed by McCarthy and McGraw and Weaver.
Anyway, that's the pattern, and let me run off a small tangent for the rest of this paragraph. Here's my question - how many games do we need before the sample size becomes large enough for the One Run Fundamental to show itself. It's true that all of these samples behave roughly as you would expect them to. The smallest sample here consists of 10 seasons, 1530 overall games, 393 one-run games. But I still suspect that even that number of games is just a little on the small size.
I do think we can be pretty damn sure that a single season, and the 30 or 40 one-run games it might include, is nowhere near a large enough sample for the One-Run Fundamental to assert itself - it's about the same as... oh, 30 or 40 at bats over the course of the year. In which anything can happen. It's a little like Josh Donaldson going 5-35 back in May. He's still Josh Donaldson.
So what's the biggest factor in one-run games?
Well, obviously the quality of the team is a pretty large factor. The best teams really do have the best records in one-run games.
But the closer a game gets, the greater the chance that Random Circumstance can determine the outcome. And Luck doesn't know anything about quality. Luck is a flip of a coin, and the odds are the same for everyone. Heads or tails, win or lose, it's 50-50.
Let's look at the teams that played .700 ball or better. They played .651 ball in one-run games. In an average season, they'd have played about 42 such games, so it's as if they went 27-15 in those games. But we would have expected them to go 31-11, had they played one-run games the same way they played the rest of them. It's almost as if half the games were decided by the team's quality (their .742 winning percentage) and the other half were decided by a coin flip (which ought to be .500).
Half of the one-run games are effectively decided by a coin flip?
Gulp. Because if you flip that coin 3000 times, you'll surely see heads come up 1500 times. But if you only flip it 30 or 40 times? Weird, weird things can happen.
Which brings us, at last to the Toronto Blue Jays.
From that snowy April day in 1977 through this year's All-Star Break, the Jays have played 6,284 games and they've had a losing record for almost all of that time. (They were briefly above .500 from September 1993 through May 1994, and intemittently after that for the next year. But the franchise has had a losing record every day since May 1995. Not to mention the sixteen years before the second championship.) At this particular moment, they got 3129 wins and 3155 losses, a .498 percentage. We would expect them to have a record in one-run games that's very close to that. Maybe a game or two better.
They don't. They're 874-926 (.486) in one-run games. It's not that big a deal - one more loss, one fewer win every other year or so. Here are the raw numbers:
ONE-RUN OVERALL OTHER GAMES
Year W L PCT W L PCT W L PCT Manager(s)
1977 17 27 .386 54 107 .335 37 80 .316 Hartsfield
1978 23 30 .434 59 102 .366 36 72 .333 Hartsfield
1979 19 28 .404 53 109 .327 34 81 .296 Hartsfield
1980 23 21 .523 67 95 .414 44 74 .373 Mattick
1981 10 17 .370 37 69 .349 27 52 .342 Mattick
1982 28 30 .483 78 84 .481 50 54 .481 Cox
1983 25 20 .556 89 73 .549 64 53 .547 Cox
1984 34 25 .576 89 73 .549 55 48 .534 Cox
1985 26 21 .553 99 62 .615 73 41 .640 Cox
1986 22 25 .468 86 76 .531 64 51 .557 Williams
1987 27 24 .529 96 66 .593 69 42 .622 Williams
1988 21 17 .553 87 75 .537 66 58 .532 Williams
1989 25 22 .532 89 73 .549 64 51 .557 Williams-Gaston
1990 24 27 .471 86 76 .531 62 49 .559 Gaston
1991 28 20 .583 91 71 .562 63 51 .553 Gaston-Tenace-Gaston
1992 28 20 .583 96 66 .593 68 46 .596 Gaston
1993 23 22 .511 95 67 .586 72 45 .615 Gaston
1994 13 15 .464 55 60 .478 42 45 .483 Gaston
1995 16 23 .410 56 88 .389 40 65 .381 Gaston
1996 19 22 .463 74 88 .457 55 66 .455 Gaston
1997 29 30 .492 76 86 .469 47 56 .456 Gaston-Queen
1998 28 17 .622 88 74 .543 60 57 .513 Johnson
1999 26 18 .591 84 78 .519 58 60 .492 Fregosi
2000 21 19 .525 83 79 .512 62 60 .508 Fregosi
2001 28 21 .571 80 82 .494 52 61 .460 Martinez
2002 23 21 .523 78 84 .481 55 63 .466 Martinez-Tosca
2003 14 23 .378 86 76 .531 72 53 .576 Tosca
2004 17 22 .436 67 94 .416 50 72 .410 Tosca-Gibbons
2005 16 31 .340 80 82 .494 64 51 .557 Gibbons
2006 20 10 .667 87 75 .537 67 65 .508 Gibbons
2007 29 25 .537 83 79 .512 54 54 .500 Gibbons
2008 24 32 .429 86 76 .531 62 44 .585 Gibbons-Gaston
2009 21 28 .429 75 87 .463 54 59 .478 Gaston
2010 24 28 .462 85 77 .525 61 49 .555 Gaston
2011 29 28 .509 81 81 .500 52 53 .495 Farrell
2012 15 25 .375 73 89 .451 58 64 .475 Farrell
2013 20 29 .408 74 88 .457 54 59 .478 Gibbons
2014 15 20 .429 83 79 .512 68 59 .535 Gibbons
2015 15 28 .349 93 69 .574 78 41 .655 Gibbons
2016 9 15 .375 51 40 .560 42 25 .627 Gibbons
874 926 .486 3129 3155 .498 2255 2229 .503
So what was the most disturbing experience, when did the team lose way more one-run games than you would expect from a team of that general quality? That would be the 2015 team, who played .349 ball (15-28) in one-run games and .655 ball (78-41) the rest of the time. (Using my Coin Flip logic, they went roughly 15-6 on Quality, but the coin came up Tails 20 times in a row when they were calling Heads. Yikes.
The next worse? Meet this year's team, playing .375 ball (9-15) in one-run games, and .627 ball (42-25 the rest of the time.
Next worse? The 2005 squad, who played the one-run games at a .340 clip (16-31), while playing .557 ball.
What do these teams have in common? Well, there's ownership. And batting practice pitcher Jesus Figueroa. And... well, let's look at the managers, shall we?
This requires a bit of digging through the Game Logs, as the Jays made mid-season managerial changes in 1989, 1997, 2002, 2004, and 2008. And while Cito Gaston was the manager of the 1991 team that went 91-71, Gaston went into Mt Sinai Hospital with a herniated disk on August 21 of that year and was away from the ballpark for just over a month. Gene Tenace managed the games in his absence.
This time, instead of running through the data in chronological order, we'll rank the teams by their proficiency in one-run games. And by proficiency I don't mean mere winning percentage - I mean winning percentage in one-run games compared to winning percentage of the other games. Which Toronto team had the most good fortune in the close ones?
We're going to pass over Mel Queen's five game stint at the end of 1997, and try to remember the good fortune enjoyed by John Gibbons's 2006 team. They played .667 ball (20-10) in the one-run games, while being little more than a .500 team (67-65, .508) the rest of the time? Go figure. Cito Gaston's 1989 team was even better in the one-run games (23-10, .697) but that team was quite a bit better than the 2006 squad - they played .581 ball (54-39) for Gaston the rest of the time. And the most unfortunate manager of all was not Gibbons, although heaven knows his name does show up often enough as the bottom of this table. It was Jimy Williams in early 1989. The 12-24 start that cost him his job was built on a horrific 2-12 mark in the one-run games. Something I hadn't known!
ONE-RUN OVERALL OTHER GAMES
Year W L PCT W L PCT W L PCT DIFF Manager(s) 1997 2 0 1.000 4 1 .800 2 1 .667 .333 Queen 2006 20 10 .667 87 75 .537 67 65 .508 .159 Gibbons 1980 23 21 .523 67 95 .414 44 74 .373 .150 Mattick 1989 23 10 .697 77 49 .611 54 39 .581 .116 Gaston 2001 28 21 .571 80 82 .494 52 61 .460 .111 Martinez 1998 28 17 .622 88 74 .543 60 57 .513 .109 Johnson 1979 19 28 .404 53 109 .327 34 81 .296 .109 Hartsfield 1991 24 14 .632 72 57 .558 48 43 .527 .104 Gaston 1978 23 30 .434 59 102 .366 36 72 .333 .101 Hartsfield 1999 26 18 .591 84 78 .519 58 60 .492 .099 Fregosi 2002 5 6 .455 20 33 .377 15 27 .357 .097 Martinez 2004 13 14 .481 47 64 .423 34 50 .405 .077 Tosca 1977 17 27 .386 54 107 .335 37 80 .316 .070 Hartsfield 1984 34 25 .576 89 73 .549 55 48 .534 .042 Cox 2007 29 25 .537 83 79 .512 54 54 .500 .037 Gibbons 1995 16 23 .410 56 88 .389 40 65 .381 .029 Gaston 1981 10 17 .370 37 69 .349 27 52 .342 .029 Mattick 1997 27 30 .474 72 85 .459 45 55 .450 .024 Gaston 1988 21 17 .553 87 75 .537 66 58 .532 .020 Williams 2002 18 15 .545 58 51 .532 40 36 .526 .019 Tosca 2000 21 19 .525 83 79 .512 62 60 .508 .017 Fregosi 2011 29 28 .509 81 81 .500 52 53 .495 .014 Farrell 1996 19 22 .463 74 88 .457 55 66 .455 .009 Gaston 1983 25 20 .556 89 73 .549 64 53 .547 .009 Cox 1982 28 30 .483 78 84 .481 50 54 .481 .002 Cox 1992 28 20 .583 96 66 .593 68 46 .596 -.013 Gaston 1994 13 15 .464 55 60 .478 42 45 .483 -.018 Gaston 2009 21 28 .429 75 87 .463 54 59 .478 -.049 Gaston 2013 20 29 .408 74 88 .457 54 59 .478 -.070 Gibbons 1985 26 21 .553 99 62 .615 73 41 .640 -.087 Cox 2004 4 8 .333 20 30 .400 16 22 .421 -.088 Gibbons 1990 24 27 .471 86 76 .531 62 49 .559 -.088 Gaston 1986 22 25 .468 86 76 .531 64 51 .557 -.088 Williams 1987 27 24 .529 96 66 .593 69 42 .622 -.092 Williams 2010 24 28 .462 85 77 .525 61 49 .555 -.093 Gaston 2012 15 25 .375 73 89 .451 58 64 .475 -.100 Farrell 1993 23 22 .511 95 67 .586 72 45 .615 -.104 Gaston 2014 15 20 .429 83 79 .512 68 59 .535 -.107 Gibbons 2008 11 17 .393 35 39 .473 24 22 .522 -.129 Gibbons 2008 13 15 .464 51 37 .580 38 22 .633 -.169 Gaston 2003 14 23 .378 86 76 .531 72 53 .576 -.198 Tosca 2005 16 31 .340 80 82 .494 64 51 .557 -.216 Gibbons 2016 9 15 .375 51 40 .560 42 25 .627 -.252 Gibbons 1991 4 6 .400 19 14 .576 15 8 .652 -.252 Tenace 2015 15 28 .349 93 69 .574 78 41 .655 -.307 Gibbons 1989 2 12 .143 12 24 .333 10 12 .455 -.312 Williams
And finally, let's just add up the manager's records and see how they've done in one-run games.
ONE RUN GAMES OTHER GAMES OVERALL Manager W L PCT W L PCT W L PCT DIFF Hartsfield 59 85 .410 107 233 .315 166 318 .343 .095 Mattick 33 38 .465 71 126 .360 104 164 .388 .104 Cox 113 96 .541 242 196 .553 355 292 .549 -.012 Williams 72 78 .480 209 163 .562 281 241 .538 -.082 Gaston I (1989-2007) 197 183 .518 486 453 .518 683 636 .518 .001 Tenace 4 6 .400 15 8 .652 19 14 .576 -.252 Queen 2 0 1.000 2 1 .667 4 1 .800 .333 Johnson 28 17 .622 60 57 .513 88 74 .543 .109 Fregosi 47 37 .560 120 120 .500 167 157 .515 .060 Martinez 33 27 .550 67 88 .432 100 115 .465 .118 Tosca 45 52 .464 146 139 .512 191 191 .500 -.048 Gibbons I (2004-2008) 80 91 .468 225 214 .513 305 305 .500 -.045 Gaston II (2008-2010) 58 71 .450 153 130 .541 211 201 .512 -.091 Farrell 44 53 .454 110 117 .485 154 170 .475 -.031 Gibbons II (2013-2016) 59 92 .391 242 184 .568 301 276 .522 -.177 Gaston TOTAL 255 254 .501 639 583 .523 894 837 .516 -.022 Gibbons TOTAL 139 183 .432 467 398 .540 606 581 .511 -.108That final column just compares the manager's winning percentage in one-run games to his percentage in the other games.
In my view, all of these represent Small Samples. A few tidbits, nonetheless...
The terrible teams managed by Hartsfield and Mattick both posted significantly better results in one-run games, exactly as you would expect them to do. Mattick's teams helped themselves a little more than you might expect.
Bobby Cox's excellent teams didn't lose much to the coin flip at all...
Whereas Jimy Williams' teams were pretty bad in close games. His teams were even better than Cox's teams in the other games, but everything went to hell in one-run games.
Gaston's first tour is remarkable - the exact same winning percentage (.518) in all kinds of games..
Jim Fregosi, Tim Johnson, and Buck Martinez all did quite well in one-run games, in their brief times in charge.
But since Martinez was fired, everything has gone to hell. All five managers (counting Gibbons twice) have seen significantly worse results in one-run games than you would expect. Tosca, Gibbons Mark I, and Farrell were all disappointing. Gaston Mark II was awful, twice as bad as that Group of Three. And Gibbons Mark II - great gosh almighty, he's been twice as bad as that, some twenty-seven shades of godawful.
Something is clearly wrong with the coins around here. These last ten years or so have been weird. Really, really weird.
Anyway - BlueJayWay.... we feel your pain.
