WAR on the Move: Gaining and Losing Via Trade
Please see a note on methodology and opportunities for improvement after the jump. - ed.
For some reason, I decided to spend the last 10 days digging through MORE trade data. I think it's some sick, self-destructive disorder I have, because it was in no way fun. But, what I ended up with is a comprehensive spreadsheet of every trade in the past five seasons, and the WAR each team lost and gained with those trades. (Despite the tedious and mind-numbing task it was to put it together, it's kind of awesome, so I'm making it available for your viewing pleasure / future use as a multi-tabbed , year-by-year Google spreadsheet.) Then I had to find out how to turn it into something pretty to look at. It's not nearly as complex as my first tangled web of a graphic, but it's interesting nonetheless. I'll let you all play around with it (it's interactive again) and draw your own conclusions, and I'll save my thoughts for after the jump. Enjoy!
(Again, due to size constraints, I've posted a bigger version over on my own site.)
- Texas has lost a potential 60.8 WAR in the past five years. I think this could be indicative of a few things, (some related to the reliability of WAR and some purely related to the Rangers' front office management) but I'll leave let you all ponder/argue about them in the comments instead of addressing them here.
- Despite the fact that the Padres sit atop the graph, the recent dealing of Adrian Gonzalez means that probably won't last long.
- A few teams at the top (Tigers, Nationals, Orioles, Blue Jays) have been pretty bad in the past few years, but these numbers make me wonder if the next few seasons could potentially be bright for them.
I've gotten a lot of questions (in the comments and via e-mail) about my methodology for this project. I'll admit that I stupidly forgot to include a note about it in the original post, so I'll attempt to explain it here. Before I jump into anything, however, I want to let everyone know that I'm not 100% certain that my method was the best one, or that it was even correct. Your (kindly-worded) comments and corrections are welcome and encouraged.
To calculate WAR Received, I used a similar method. I included all WAR accumulated by a player during his time spent with the receiving team. Again, I'll go to the Teixeira example. As I mentioned before, Teixeira was sent to the Braves in 2007. During his time with the Braves, he accumulated 6.3 WAR. That value is what I placed in the WAR Received column, because it is what Teixeira contributed to Atlanta.
This method, as I mentioned before, isn't flawless. Had Teixeira stayed in Texas, it is possible that he might not have contributed 19.7 WAR. He may have over- or under-performed that value based on many factors. But this method is what I considered to be the simplest and most effective. Some have mentioned that I should instead focus on a different metric, one that could potentially be labeled Dollars Per WAR. This would put a value on the money each team spent per WAR. It's an interesting concept, and one I might examine soon. Thanks so much for your thoughts thus far. You're helping a young saberist learn and grow.
30 comments
|
5 recs |
Do you like this story?
Comments
Excellent work
Not only is it pretty, but informative—two goals for any visualization.
My initial thought about something like this is that teams with positive WAR should be playoff teams that typically trade for stars to make a push for a championship. Teams trading away stars get prospects/younger players in return, so the short term WAR net is negative for them. However, no pattern jumps out at me at first glance.
How did you compile WAR? Did you take all WAR from 2006 up to 2010 for each player? Did you average it? Was it just for the year they were traded?
A question
Shouldn’t the total net “WAR received” be equal to the total net “WAR sent”? That is, shouldn’t the net amount of WAR sent by a team be equal to the amount of WAR received by its trading partner? Your chart shows quite a bit more WAR sent than WAR received.
A note on methodology:
What I looked at was potential WAR lost by being traded. If Team X had kept Player Y, what WAR would they have received via that player’s performance? So the “WAR sent” ended up being the total WAR a particular player achieved after he left the trading team. For example, Mark Teixeira has accrued 19.7 WAR since leaving Texas, so I assigned 19.7 WAR sent to Texas as a result of that trade, because they lost out on those stats as a result of losing Teixeira. The “WAR received” category, on the other hand, is strictly the WAR that player put up while with the receiving team. So, because Teixeira totaled 6.3 WAR while with Atlanta, that’s the value the Braves get in WAR received. So it makes sense then that WAR sent would be much higher.
by Chris Spurlock on Dec 31, 2010 12:19 PM EST up reply actions
Makes sense
but I still wonder how you dealt with in-season trades. Did you figure out partial WAR at the time a player was traded and then subtract the first half of their season from the total sent by their original team?
I also wonder whether this visual should be produced yearly, rather than for a group of years. Reason being, teams that may have traded away studs in 2009 sent WAR as someone whose stud left in 2006 and has had 4 seasons to accumulate their stats. Just a thought.
Baseball-Reference is a godsend
They keep WAR stats for partial seasons. They list Teixeira as having 2.7 WAR for Texas for the first half of ’07, and then 2.3 WAR for Atlanta in the second half of ’07. So when Texas traded him away, they lost the 2.3 for the Atlanta ’07 season, as well as all WAR Teixeira accumulated after that trade.
by Chris Spurlock on Dec 31, 2010 2:23 PM EST up reply actions
Ahhhhhh
yup, totally forgot about their in-season splits (which is amazing, since I’ve been living there the last few days getting data for my post next week).
That makes sense.
Think about the Indians trading away Cliff Lee and CC Sabathia. The WAR sent doesn’t come close to the WAR received. In deals for prospects, in a lot of cases, those players never materialize or haven’t made the majors yet, so the WAR sent will be higher than the WAR received.
Chicago White Sox Examiner — Big hat, no cattle
by UribeAuction on Dec 31, 2010 1:27 PM EST up reply actions
Sorry, meant to say the chart makes sense.
Chicago White Sox Examiner — Big hat, no cattle
by UribeAuction on Dec 31, 2010 1:27 PM EST up reply actions
Very nice
By chance…what is the impact of the Brewers two recent trades involving Shaun Marcum and Zack Greinke? Or is that something you cant determine until after the season?
We don't know for sure...
A few sabermetricians make predictions about player WAR for future seasons, so you can go off of those numbers, but Baseball Reference doesn’t have all of those numbers available. Fan Graphs has more, but only for more prominent players. WAR is less of a predictive tool and more of a tool for evaluating past performance anyway.
by Chris Spurlock on Dec 31, 2010 12:21 PM EST up reply actions
*love this*
See Data Differently: Beyond the Box Score | @justinbopp
Create. Coach. Conquer! Two Out Rally, Baseball MMORPG | Facebook
Fantastic.
Essentially the TIgers entire net gain is from Miguel Cabrera beasting for Motown and Andrew Miller sucking while Cam Maybin still develops (who I still have never liked as a prospect – ground ball heavy hitter which means not likely to develop the power everyone predicted.)
My Michigan State (and Big Ten) Baseball Blog.
Like music? See what I'm listening to at my Last.fm account.
The numbers seem to be off or incomplete, at least for the Rockies.
You have them receiving 1.3 WAR from Jason Marquis, for instance, while Baseball Reference has him providing 3 WAR with . You also don’t have Carlos Gonzalez listed at all as part of the Holliday trade, which kind of is going to skew that one to the A’s favor. The Dec 2006 Jason Jennings/Miguel Ascencio for Willy Taveras/Jason Hirsh and Taylor Buchholz trade isn’t included either.
It was inevitable that I missed something...
I was working with ESPN’s transactions data which isn’t perfect (I discovered a few mistakes myself). I was also inputting all WAR data by hand for hours on end, so I no doubt made a few human errors. Thanks for the heads up!
by Chris Spurlock on Dec 31, 2010 5:15 PM EST up reply actions
no problem, it's an awesome spreadsheet and visual.
I don’t want to seem an ingrate, because I could tell a ton of work went into this. I’m guessing Marquis was probably just a transcription error, reversing 3.1 to 1.3, so maybe if fans of other teams could help proofread their teams’ transactions it could make the editing job easier.
This is awesome, but you might not want to use the ESPN transactions data.
I could tell you did a ton of work with this, but there’s some key trades missing. Just looking at the Mariners it doesn’t look like you’ve included the three-way trade with the Mets and Indians involving JJ Putz and Franklin Gutierrez. You’ve left out both Cliff Lee trades as well. Are you filtering the data to remove these trades for some reason?
Additional Mariners trades:
Milton Bradley for Carlos Silva
Ryan Langerhans for Mike Morse
I suggest using the baseball-reference transactions screen if ESPN didn’t pick these up.
Link
M's fan in PA, soon to be LA
This is really neat looking.
And I really appreciate the thought, but a few questions about methodology here:
Are we just taking all the players involved in a trade and writing down all the WAR they contributed in the future for their teams?
Because, woah Nellie! Many players who are traded for are immediately signed to long term extensions by the destination team. Those wins are paid for at market rate, and what is traded for when that player is traded for is primarily the surplus value still on their current contract.
I suppose I feel like the implication here is that the teams that’ve traded away lots of WAR are somehow doing it wrong. If I understand the methodology (which, no offense, doesn’t seem to be explained above), then I don’t think it communicates that information.
Can you please share a bit more specifically what the methodology is?
Love the Simple Design
Your presentation is awesome — little chart junk, lots of data in a very easily understandable way.
However, your methodology is a bit lacking I think.
For instance, Teixeira was traded to Atlanta in July 2007. His contract ended in 2007. Atlanta traded for 3 months of Teixeira, and paid 4.5 million (give or take) for those remaining 2.3 WAR. The 2008 contract was totally independent from the trade, and I think punishing Teixeira for that (let alone his time for the Yankees!) is a bit off.
Ideally, we’d turn this all into a discussion of dollars. How many dollars did each team trade away, and how many did they receive? To get the dollars that each team traded/received you have to convert their WAR into dollars, and subtract their salary. That way, we can also take the prospects that each team received, and use Victor Wang’s values on prospects to estimate their impact (even though they haven’t had an impact on the MLB team yet):
http://www.hardballtimes.com/main/article/the-bright-side-of-losing-santana/
I think that though it’s a lot more work, it would get much better results. Are you willing to share your data? I would love to take a crack at it if you have.
My Work: Henkakyuu
Use the data, please!
All of my data is located here: https://spreadsheets.google.com/ccc?key=0An71msoJrWK2dHdxUzNIS2loMWJoUDFBZzlQdWdyVlE&hl=en
It’s tabbed at the bottom by year. If you have any questions, let me know!
by Chris Spurlock on Jan 1, 2011 4:38 PM EST up reply actions
Do you have the by-year WAR figures?
Or did you just total up manually? I can only see team tables by year, so to add contract info would (essentially) be starting over.
My Work: Henkakyuu
by jmaciel on Jan 1, 2011 10:11 PM EST via mobile up reply actions
I'll let others comment on methodology—I'll stick to the visuals.
Awesome job, and love that it’s toggle-able. How did you build it? Did you lay it all out by hand in Flash or are you some sort of Flex wizard that can drive this from a CSV? If the latter, I could see you repurposing this for a lot of uses. Great work, Chris!
On Twitter: @baseballtwit
It was all built in Illustrator...
…and then imported into Flash. I have a sick love affair with Illustrator because I feel like I have more design control. The only thing Flash was used for was to navigate between the three keyframes I have the charts in.
Thanks for compliment, though! I’m loving your HOF interactives, BTW. Great stuff.
by Chris Spurlock on Jan 1, 2011 4:46 PM EST up reply actions
If you'd like to keep your work iPad & iPhone friendly...
A little bit of dabbling with jQuery would allow you to toggle between the views as well. No Flash, no plugin, no complaints from iOS users. :)
But I could also see Flash being quite handy for building upon this.
Thanks for the compliment as well! More stuff up my sleeve… gotta keep the envelope a’pushing!
On Twitter: @baseballtwit
This should be a zero sum, at least in my mind
If someone loses WAR in a trade, then someone is gaining it. Further, just to use an easy example, Teixeira: he was going to FA no matter what (with Boras as his agent) Texas shouldn’t get a debit for his time with the Yankees, which is pure FA contract. If he had stayed with Texas, they would have had the same exact opportunity to sign him as they did after they traded him.
The problem with it not being a zero sum, is it makes it look like a smart strategy is doing nothing (like the Giants did) and ending up 10th by doing nothing.
Also, I must be missing something, but the excel table doesn’t match up with the table here. For example, here Colorado is -2.8 and in the table +3.5.
Juan "Doesn't Cheat The Game" Perez, future CF for the World Champion San Francisco Giants.
The thought and effort here is great,
but there are some serious flaws, both in terms of approach and completeness. The Rangers, for example, don’t appear to have acquired Josh Hamilton?
I've got a problem with the methodology
You shouldn’t be penalizing teams for what the players do for other teams after going through free agency. Texas controlled Teixeira through the 2009 season. They traded him July 2007. That is the window they should be judged upon, because at the time of the trade they had no means to maintain Tex beyond 2009. They would have had to compete with 29 other teams to land his services in 2010.
You’re trying to measure the opportunity lost by Texas for trading Teixeira. After 2009 29 teams theoretically “lost out” on having Tex produce for them in 2010 but no one would suggest you penalize the non-Texas sweepstakes losers for missing out.
The monster at the end of this blog.
How did the A's get, in 2007, a negative 0.5 war from Chris Carter
when Carter made his MLB debut in 2010?
"So, the A's new organizational philosophy involves adding Viking relievers? God save us all."
"Berserkers: the new market inefficiency."
-LonestarBall
nm, its total not yearly...
"So, the A's new organizational philosophy involves adding Viking relievers? God save us all."
"Berserkers: the new market inefficiency."
-LonestarBall
But I will say this, I think you have to calculate the WAR values based on team controlled time, as people have states above
If a team trades a player with 1 year left of team control, they should be penalized for that 1 year. If they trade a player with 3 years control, they should get penalized for those 3 years. And if they, say, resign a player at a later date after trading him, that should not count.
Also, how are draft picks received as compensation figured?
"So, the A's new organizational philosophy involves adding Viking relievers? God save us all."
"Berserkers: the new market inefficiency."
-LonestarBall
This is beautiful. I started a similar project once and gave up in the face of all the work you put in. Bravo!!!
Getting upset over a sporting event seems kind of ridiculous, until you remember that the people who get upset over sports have a remarkable ability to not get upset over the position of the toilet seat, the state of the bed, or the current location of a pair of underwear.

by 






























