Lucky Teams
At the break and with the official news finally coming in that Manny Acta has been let go in Washington, I decided to take a look at which at which teams have been lucky or unlucky the most so far this season. Of course, the definition of lucky is going to be pretty subjective to people. Here is how I have defined it, and have defined it in the past as well lest there be any concerns that I gerrymandered my criteria.
I use BaseRuns, which is my favorite team-wide metric for determining expected runs allowed and scored, to come up with an expected won-loss record based on the pythagorean method (with a variable exponent based on the runs per game, namely the David Smyth/Patriot model of pythag).
That expected winning percentage is then added to the team’s strength of schedule and then 0.5 is subtracted away to get a scheduled-neutralized expected winning percentage. Multiplying that by 162 yields a BaseRuns, schedule-neutral estimate for how many games the team should win over a season if it played at its season-to-date level.
I then subtract that from the team’s actual winning percentage scaled out to 162 games to arrive a plus or minus win figure of how lucky the team has been per 162 games.
For the more math inclined,
And the rankings, from most lucky, to most unlucky:
Astros 11
Giants 10
Phillies 10
Tigers 9
Reds 9
Angels 6
Brewers 6
Red Sox 6
Marlins 6
Rangers 3
Orioles 3
Cardinals 3
White Sox 2
Cubs 1
Mets 1
Dodgers 0
Mariners 0
Yankees -1
Padres -1
Rockies -2
Braves -3
Pirates -3
Twins -5
Athletics -5
Royals -5
Blue Jays -8
Diamondbacks -8
Rays -9
Indians -11
Nationals -19
Matthew Carruth is a software engineer who has been fascinated with baseball statistics since age five. When not dissecting baseball, he is watching hockey or playing soccer.
the nationals are good!!! i knew it
Im not suprised to see the rays at the bottom of that list. I really expect them to catch some more breaks in the second half and win the Wild Card
if the rays make it to the playoffs, one of boston and new york wouldnt make it. I really think the odd team out would be boston. Yankees just have too good a team
Dream on
How do you determine the strength of a team’s schedule?
I believe he explained it in a Lookout Landing post. Give me a minute here….
I think it might be in here somewhere:
http://www.lookoutlanding.com/2009/7/13/948108/mariners-have-not-been-lucky
It is not that big of a deal, but you can’t or at least shouldn’t use opponents’ actual winning percentage to figure a team’s strength of schedule adjustment.
A few unusual examples will suffice to explain why:
Say we are at the beginning of the season, and I have played 10 games. All 10 of those games have been against team A. Team A has played 100 games. Their record is 95 and 5. My record is 5-5. Do I want to adjust that 5-5 record for the fact that I played a .950 team in those 10 games? I think not.
Say you are doing what matthew is doing here and he comes up with the fact that the Astros are the luckiest team in baseball. The have played 100 games. They are .600 (60/40) but they should be a .400 team. I have played all 10 of my games against them. Do we want to adjust my strength of schedule by .600 or by .400? Certainly not by .600. I likely played a bad team that just has gotten lucky in those 100 games, most of which were not played against me. Why would I want to adjust my record to reflect the fact that I played an excellent team (.600) when in fact I likely played a crummy (.400) team? I wouldn’t and shouldn’t.
The correct way to do a strength of schedule adjustment is to use something else other than w/l record for each teams’ opponents, if you have that info. Something that more reflects their true strength. If you don’t have that info (and even if you do), you want to use a regressed wp for those opponents (if you are using some more granular data, you still want to regress that data).
Yes. If I had more time, I would have worked out a more robust SoS calculation. I figured the standard RPI measurement would do well enough for a proxy since I had that freely available to me.
What do you think of doing something like using the pW1 from above, regressed 50%, as the “something else” to do a SoS?
Strength of schedule completely depends on the players that the opponent is fielding. Say you face Kansas City, and for a 3 game series, and the first 2 games they start Zack Grienke and Gil Meche. Grienke is averaging 7 innings a game with a 1.97 FIP, and Meche a little less than 6 with a 4.20 FIP. That series is going to be a lot harder than a series vs. KC with Luke Hochevar and Brian Bannister, and Bruce Chen starting the 3 games. See my point? There are too many variables to go by anything to do with winning %….it is too general and reminds me of the LD +120 BABIP formula….over-simplified and inaccurate. It would be better to eliminate strength of schedule from the formula than to include it and have it be completely inaccurate.
BTW, if you do the correct strength of schedule adjustments for teams at the end of a season, you will find that it doesn’t make that much difference. The teams with the toughest or easiest schedules will gain or lose 1-2 wins at the most, if I remember correctly, and I think that 2 is a rarity.
Yep. The only team that moved more than one game in the won/loss column thanks to this SoS adjustment was the Angels, at +2 and 12 teams didn’t move at all, and that’s with a stronger SoS then I probably should have used.
“Indians -11”
Of course.
The fact that the Nats were so “unlucky” pretty much disproves this system. Watch them play, they are embarrassing bad. The pitching is among the worst I’ve ever seen, and their defense is even worse than that!!!
Sometimes the stats lie to you, the Nats aren’t unlucky they are just that damn bad.
The Padres have about the same run differential and are 16 games below .500 instead of 35. The Nationals are still horrible, but they shouldn’t be on pace to lose 110+. It’s sort of misleading that these numbers are for the whole season rather than the half a season that they’ve played.
They played a 4 game set with Philly where they scored 22 runs and got *swept*. What are the odds?
The fact that Derek Jeter is ranked as a “bad fielder” pretty much disproves fielding stat systems. His range is among the best I’ve ever seen, and did you see that one play that he dove in the stands?!!!
Sometimes the stats lie to you, Jeter isn’t bad, he’s amazing.
Are bad and unlucky mutually exclusive?
You have a “schedule-neutral estimate ” for the rest of the season, but you use this figure to compare to-date win/loss record and count that as luck. Indeed, you need the non-neutral estimate if you are going to compare to actual games played.
If I understand you correctly, you are saying that it is safe to assume a .500 schedule for the rest of the season, but the actual schedule matters in comparing to actual games played so far as far as determining “luck” ?
If so, I get that, but I felt like treating the strength of schedule to date as luck as well. I wanted an estimate of wins had each team played a neutral schedule to date.
B-
They’re unlucky and bad. When you have such a big outlier, it’s usually both.
Acta will be the next Terry Francona.
Give him a real roster from a GM that understands that pitching matters and that LF =/= CF, and he’d do well. Love how smart baseball guys like Acta get canned, and Dusty Baker still gets to manage a roster.
The Nats on Sunday TWICE loaded the bases with one out and failed to score. They stuck 14 runners on base and none of them scored.
http://deacondrake.blogspot.com/2009/07/nationals-baseball-again.html
They have found amazing new ways to snatch defeat from the jaws of victory. They are the masters of losing two games 6-8, then salvaging the sweep with a 7-1 win.
Baffling team.
The Angels pop up as “lucky” every year in every permutation of this sort of study. Perhaps just actually going out and doing things to win the game in front of them actually works?
When somebody finds a way to quantify why that happens, then I will acknowledge this sort of opinion. Until then, I am going to treat it like any other fair coin landing heads seven out of ten times. (The Angels do not pop up as lucky every single year. Just a majority of the past ten or so)
One area where I feel that any pythag system fails is that they consider all runs scored/allowed the same; however we know that runs in high leverage situations are more important. While leverage tends to average out one situation where it does not is with relievers. A good place to start would be to count high leverage reliever’s tRA more than low leverage reliever’s tRA. Do we really care when scrub relievers give up four runs in a blowout and should those runs count against their runs allowed?
I would think baserunning and bullpen are the most likely culprits. These are areas the Angels are almost always strong in and harder to judge with basic metrics. Also while “small ball” gets a bad name, looking at things like advancing runners from 2nd to 3rd with no outs etc you generally see the teams who excel at this score more runs than their stats suggest (I’m looking at you Twins). Kind of hard to know if this is repeatable or just luck for any given team though.
Why is it that seemingly every year since they went to the W.S. the Astros put together a really shabby team and they still manage to win respectable numbers of games? I’m really not surprised that they can be interpreted as a lucky team…they’re horribly run and have a roster of poor pitchers and bad contracts and yet manage to be not-horrible.
On a related note, I find it humorous that nearly every season announcers take it as just a self-evident truth that the Astros will play well in the 2nd half, like it’s some kind of innate skill of theirs. Um, it’s not a team playing over its head ever?
Eh. The Astros have enough talent on their team to be successful. True, Drayton McLane is paying a lot of money for a .500 team, but at things could be worse. I guess they have a roster of “poor pitchers”. Go look at their pitchers in terms of RAR, and they’re an average NL club. Chris Sampson is best relief pitcher in the NL Central, in terms of RAR. Oswalt and Rodriguez at the top of the rotation aren’t too shabby…Hampton has been a cost efficient one year rental.
True, their pythag record is poor, but they have a number of blowout, outlier type games that make them “luckier” than they should be. Throw out those outliers, and they’re just right on pace.
It’s also tough to deny the Astros are a strong second half team. Maybe they’ll be terrible in the second half this season, but I doubt it.
hilarious. fagnraphs never ceases to amaze me.
How do you equate intangibles such as losing 4 pitchng starters to the dl, the back end of the bullpen also being in the dl, key hitters missing a lot of time from the batting lineup, and the death of a player? I guess that makes you the 6th luckiest team.
If the luck drops off for the Angels and the Rangers it could be a real tight three-way race in the West (assuming these stats are accurate).
(Go M’s!).
All I can say is you’re full of crap. This whole site is a joke.
At what point is the pythagorean W/L system completely reevaluated? The Angels seem to be perennially “lucky”, yet haven’t dropped out of contention in years.