Is the Change of Scenery Effect a Real Thing?
Last year, Dan Uggla hit .179 and was worth +0.5 WAR, eventually getting left off the Braves playoff roster. He’ll turn 34 next March. He is due $26 million over the next two years. And this winter, the Braves are going to try to convince another organization that he just needs a fresh start in a new location to salvage his career. Take him out of Atlanta, and maybe the bat speed will come back. Maybe he just needs a change of scenery.
In reality, it is much more likely that any observed change of scenery effect is really just positive regression to the mean, since you only really need new “scenery” when you’re coming off a bad year, leaving nowhere to go but up. Players who change teams in these situations likely underperformed in the prior year, leaving plenty of opportunity for improvement after they arrive in their new city.
Of course, it can go deeper than that as well. Sometimes, when going from one team to another, a pitcher or hitter acquires park dimensions that better fit their game or a clubhouse that might better fit their demeanor. Or maybe they’re a pitcher and they move to a better defensive team. Or they finally get platooned in their new city, allowing them to only play when they have the advantage. There are plenty of reasons why a player could be more effective on one team than another.
So, the change of scenery effect makes sense. It seems like it should be a real thing. However, I wondered how often we actually see players make these kinds of moves and whether we observe actual positive spikes in change of scenery players? The only way to answer that is to turn to the data.
To find out I pulled all player seasons since 1999 (15 seasons from present) with a minimum plate appearance (PA) total of 200 in each season of interest. I converted each player’s total WAR with the old team into WAR that would represent a full season (per 650 PA). I then calculated DeltaWAR — the change in player’s WAR per 650 PA between teams. I took players who had played with their previous team for three years — long enough where a change of scenery analysis would be warranted.
Over the last 15 seasons here are the cases in which the change of scenery was followed by a significant change in plus-value. All mid-season transactions have been excluded. The first few names may surprise you:
Best Changes of Scenery (since 1999): Please note that DeltaWAR is the +/- value that determines ranking.
Name | Team | Tenure | WAR | WAR/650 | Team | Tenure | WAR | WAR/650 | DeltaWAR |
---|---|---|---|---|---|---|---|---|---|
Ryan Raburn | Tigers | 2004 – 2012 | 2.6 | 1.0 | Indians | 2013 – 2013 | 2.5 | 5.9 | 4.9 |
Luis Valbuena | Indians | 2009 – 2011 | -1.7 | -1.5 | Cubs | 2012 – 2013 | 3.4 | 3.2 | 4.7 |
Michael Barrett | Expos | 1999 – 2003 | -1.3 | -0.4 | Cubs | 2004 – 2006 | 7.7 | 3.6 | 4.0 |
J.D. Drew | Cardinals | 1999 – 2003 | 16.2 | 4.8 | Braves | 2004 – 2004 | 8.6 | 8.7 | 3.8 |
David Ortiz | Twins | 1999 – 2002 | 1.5 | 0.7 | Red Sox | 2003 – 2013 | 38.8 | 3.9 | 3.1 |
Mike Lamb | Rangers | 2000 – 2003 | -1.2 | -0.6 | Astros | 2004 – 2007 | 5.0 | 2.3 | 2.9 |
John Buck | Royals | 2004 – 2009 | 3.7 | 1.1 | Blue Jays | 2010 – 2010 | 2.7 | 4.0 | 2.9 |
Clint Barmes | Rockies | 2003 – 2010 | 4.0 | 1.0 | Astros | 2011 – 2011 | 2.9 | 3.8 | 2.8 |
Kelly Johnson | Braves | 2005 – 2009 | 7.7 | 2.6 | Diamondbacks | 2010 – 2010 | 5.4 | 5.2 | 2.6 |
Marco Scutaro | Athletics | 2004 – 2007 | 2.8 | 1.1 | Blue Jays | 2008 – 2009 | 7.1 | 3.6 | 2.6 |
John Jaso | Rays | 2008 – 2011 | 2.4 | 2.3 | Mariners | 2012 – 2012 | 2.6 | 4.7 | 2.4 |
Eli Marrero | Cardinals | 1999 – 2003 | 3.1 | 1.6 | Braves | 2004 – 2004 | 1.7 | 4.0 | 2.3 |
Adrian Gonzalez | Padres | 2006 – 2010 | 19.9 | 3.8 | Red Sox | 2011 – 2011 | 6.3 | 5.7 | 2.0 |
Carlos Quentin | White Sox | 2008 – 2011 | 6.1 | 2.0 | Padres | 2012 – 2013 | 3.9 | 3.8 | 1.8 |
Abraham Nunez | Pirates | 1999 – 2004 | -0.7 | -0.3 | Cardinals | 2005 – 2005 | 1.1 | 1.5 | 1.8 |
Marlon Anderson | Phillies | 1999 – 2002 | 1.8 | 0.6 | Devil Rays | 2003 – 2003 | 2.0 | 2.4 | 1.8 |
Juan Uribe | Rockies | 2001 – 2003 | 0.4 | 0.2 | White Sox | 2004 – 2008 | 7.6 | 2.0 | 1.8 |
Ben Davis | Padres | 1999 – 2001 | 2.0 | 1.3 | Mariners | 2002 – 2003 | 2.4 | 3.0 | 1.6 |
Josh Reddick | Red Sox | 2009 – 2011 | 1.6 | 2.6 | Athletics | 2012 – 2013 | 7.2 | 4.2 | 1.6 |
Derrek Lee | Marlins | 1999 – 2003 | 10.4 | 2.5 | Cubs | 2004 – 2009 | 22.3 | 4.1 | 1.6 |
Adam Kennedy | Cardinals | 1999 – 2008 | 0.2 | 0.2 | Athletics | 2009 – 2009 | 1.5 | 1.7 | 1.5 |
Mike Napoli | Angels | 2006 – 2010 | 11.8 | 4.3 | Rangers | 2011 – 2012 | 7.4 | 5.7 | 1.4 |
Gary Sheffield | Dodgers | 1999 – 2001 | 14.7 | 5.1 | Braves | 2002 – 2003 | 12.4 | 6.4 | 1.4 |
Randy Winn | Devil Rays | 1999 – 2002 | 5.2 | 2.0 | Mariners | 2003 – 2004 | 7.1 | 3.4 | 1.4 |
Miguel Cabrera | Marlins | 2003 – 2007 | 20.2 | 4.3 | Tigers | 2008 – 2013 | 35.1 | 5.6 | 1.4 |
Ryan Raburn is a surprising name, but his move from Detroit to Cleveland has been rather remarkable. Raburn was worth 2.5 WAR in only 86 games— around 5.25 WAR per 650 PA. In his 575 games with the Tigers, he accumulated a 2.6 WAR, which means he nearly surpassed his career WAR in only 86 games with his new team, and thus he ranks first with 4.88 DeltaWAR.
Cleveland utilized Raburn as a platoon player — something he was not in Detroit. Thus, this change of scenery performance has a lot to do with how his new team maximized his talents in a role that suited him best. Similarly, Luis Valbuena (ranked 2nd) was used as a platoon piece at third last season, where he broke out and had a career year — which goes to show how a change of scenery can lead to a player’s talents being maximized in a new role.
Notice how J.D Drew (ranked 4th) and Eli Marrero (ranked 12th) both left the Cardinals in a trade for the Braves during the 2004 offseason — delivering with them a surplus of 6 DeltaWAR. The caveat for the Braves? They gave away Adam Wainwright and Jason Marquis.
For guys like J.D Drew and David Ortiz (ranked 5th), these moves occurred in their primes. For Ortiz, there was an additional variable at play —Fenway was a match made in heaven and it’s hard to imagine him putting up the same numbers in the old Twin’s Metrodome, so park factors likely played a large role here as well.
And here are the 25 worst change of scenery performances in recent antiquity.
Worst Changes of Scenery (since 1999): Please note that DeltaWAR is the +/- value that determines ranking.
Name | Team | Tenure | WAR | WAR/650 | Team | Tenure | WAR | WAR/650 | DeltaWAR |
---|---|---|---|---|---|---|---|---|---|
Andruw Jones | Braves | 1999 – 2007 | 54.4 | 5.8 | Dodgers | 2008 – 2008 | -1.2 | -3.3 | -9.1 |
Sammy Sosa | Cubs | 1999 – 2004 | 31.4 | 5.2 | Orioles | 2005 – 2005 | -1.3 | -2.0 | -7.2 |
Maicer Izturis | Angels | 2005 – 2012 | 12.8 | 3.0 | Blue Jays | 2013 – 2013 | -2.1 | -3.4 | -6.4 |
Tony Clark | Tigers | 1999 – 2001 | 5.5 | 2.7 | Red Sox | 2002 – 2002 | -1.5 | -3.3 | -5.9 |
Trot Nixon | Red Sox | 1999 – 2006 | 23.0 | 3.9 | Indians | 2007 – 2007 | -0.9 | -1.7 | -5.6 |
Albert Pujols | Cardinals | 2001 – 2011 | 83.0 | 7.3 | Angels | 2012 – 2013 | 4.4 | 2.6 | -4.7 |
Roberto Alomar | Indians | 1999 – 2001 | 18.9 | 5.9 | Mets | 2002 – 2002 | 1.4 | 1.4 | -4.6 |
Roger Cedeno | Mets | 1999 – 2003 | 0.9 | 0.4 | Cardinals | 2004 – 2005 | -1.7 | -3.9 | -4.3 |
Chone Figgins | Angels | 2002 – 2009 | 21.9 | 3.5 | Mariners | 2010 – 2012 | -1.1 | -0.6 | -4.1 |
Travis Hafner | Indians | 2003 – 2012 | 21.3 | 3.1 | Yankees | 2013 – 2013 | -0.4 | -0.9 | -4.0 |
Edgardo Alfonzo | Mets | 1999 – 2002 | 18.7 | 5.0 | Giants | 2003 – 2005 | 2.4 | 1.0 | -4.0 |
Mark McLemore | Mariners | 2000 – 2003 | 6.7 | 2.4 | Athletics | 2004 – 2004 | -0.7 | -1.5 | -3.9 |
Marcus Giles | Braves | 2001 – 2006 | 17.9 | 4.1 | Padres | 2007 – 2007 | 0.1 | 0.1 | -3.9 |
Rafael Palmeiro | Rangers | 1999 – 2003 | 19.7 | 3.8 | Orioles | 2004 – 2005 | 0.2 | 0.1 | -3.7 |
Scott Spiezio | Angels | 2000 – 2003 | 6.7 | 2.2 | Mariners | 2004 – 2005 | -1.0 | -1.4 | -3.6 |
Luis Gonzalez | Diamondbacks | 1999 – 2006 | 33.7 | 4.2 | Dodgers | 2007 – 2007 | 0.6 | 0.7 | -3.4 |
Jason Giambi | Athletics | 1999 – 2001 | 22.1 | 7.1 | Yankees | 2002 – 2008 | 20.9 | 3.7 | -3.4 |
Garret Anderson | Angels | 1999 – 2008 | 19.0 | 2.0 | Braves | 2009 – 2009 | -1.0 | -1.2 | -3.2 |
Chuck Knoblauch | Yankees | 1999 – 2001 | 4.3 | 1.6 | Royals | 2002 – 2002 | -0.8 | -1.6 | -3.1 |
Josh Hamilton | Rangers | 2008 – 2012 | 21.8 | 5.0 | Angels | 2013 – 2013 | 1.9 | 1.9 | -3.1 |
Pat Burrell | Phillies | 2000 – 2008 | 16.4 | 2.0 | Rays | 2009 – 2009 | -0.8 | -1.1 | -3.1 |
Ramon Martinez | Giants | 1999 – 2002 | 3.3 | 2.1 | Cubs | 2003 – 2004 | -0.7 | -0.7 | -2.8 |
Mark Teahen | Royals | 2005 – 2009 | 3.5 | 0.8 | White Sox | 2010 – 2010 | -0.8 | -2.0 | -2.8 |
Melvin Mora | Orioles | 2001 – 2009 | 26.4 | 3.3 | Rockies | 2010 – 2010 | 0.3 | 0.6 | -2.8 |
Melky Cabrera | Yankees | 2005 – 2009 | 3.0 | 0.9 | Braves | 2010 – 2010 | -1.4 | -1.8 | -2.7 |
Andruw Jones takes the crown and it isn’t even close! This one is forever burned into the minds of the Dodger faithful—and rightfully so at a -9.11 DeltaWAR — as Jones to the Dodgers ranks as the worst transition from one team to the other in the last decade plus. With the Braves, Jones averaged 5.83 WAR/650 compared to -3.28 WAR/650 with the Dodgers. Now, that is a large drop off in performance for a guy who once seemed destined to be a Hall of Famer.
Remember, if a player comes to your team with a certain reputation for producing — the price to acquire that player will be larger than to acquire a player with no reputation. It’s a simple theory. If a player has some level of performance with his prior team and your team is paying to sign this player as a free agent, that player is more likely to regress from his previous level of talent to something of lesser value. The correlation between a player’s amassed WAR with his previous team compared to their DeltaWAR with their new team is -0.50 — meaning the larger their previous sum of WAR the smaller their change in performance will be. Once again this illustrates the point of the greater reward in signing a Raburn than going out and signing an Andruw Jones or Albert Pujols. Simply signing players with potential to grow obviously has less risk and a much higher reward — meaning more bang for your buck. Obviously it’s harder to find a sleeper in a free agent class than it is to identify a big name like a Pujols or Hamilton.
For that reason, free agency is a “what have you done for me lately” kind of game. As Derek Jeter walks into the Yankees office and receives a one year 12.5 million dollar deal, he is not receiving that money to play as a 12.5 million dollar player. He is receiving that money as a sign of respecting what he has done in the past. Little of what is given to players is done on a predictive assessment of their value — rather descriptive in hindsight. Just take a gander in the WAR totals prior to leaving in “Worst 25 List” compared to the “Best 25 List” list — there are a lot of players who were highly successful then fell off a cliff with their new teams:
Here is a histogram of the DeltaWAR of player moves from team 1 (6 seasons or more) to team 2:
6 years with previous team, no WAR cutoff:
Here 80% of the moves resulted in a DeltaWAR below zero — while a three year threshold with the prior team yielded 65% of the DeltaWAR’s being under 0. This is not a normal distribution and is skewed left from the center —which sits at just over -1 DeltaWAR. However, what happens to the distribution when we look at only players with a certain amount of amassed WAR prior to the move, meaning what does a distribution of smaller, less established players look like:
Amassed 5 WAR with previous team and minimum of three years prior to the move:
Now here we have around 55% of the DeltaWAR over 0 — with the distribution’s mean and median above 0. As you can see if a player had less than 5 WAR prior to the move they are more more likely to give their team a positive return in former talent level — in hindsight.
Now, lastly, let’s look at what happens when a team signs/acquires a bigger name over the offseason:
Three year previous team threshold and amassed 15 WAR minimum:
Here the distribution is widely skewed left towards the negative. What does this tell us? That signing more established players rarely means that a change of scenery yields improved production — in fact, you can imply the opposite.
Now, I am not saying if you sign Omar Infante over Robinson Cano this offseason that Infante has a greater probability to give you a surplus value. I am saying, given what we know about the transitions in the past, there is less risk in signing a player of lesser “talent” because any fluctuation in his play will be worth more in proportion to the value of his contract. If they break out, then your reap the benefits. If they play terribly — below their established talent level for their career — then you don’t play them and you eat the remaining cash. It’s not the popular way to play the market but its a way many small market teams find success.
Some teams have optimized their payroll with the same mindset above:
Here are the teams that have performed best in DeltaWAR since 1999
No. | Team | DeltaWAR |
---|---|---|
1 | Astros | 5.7 |
2 | Cubs | 4.4 |
3 | Reds | 2.6 |
4 | Tigers | 0.8 |
5 | Pirates | 0.7 |
6 | Rays | 0.2 |
7 | Rangers | 0.1 |
8 | Braves | -0.8 |
9 | Brewers | -1.1 |
10 | Giants | -1.8 |
11 | Twins | -1.8 |
12 | Indians | -2.3 |
13 | Diamondbacks | -3.4 |
14 | Marlins | -3.5 |
15 | Royals | -3.8 |
16 | Red Sox | -4.0 |
17 | Nationals | -5.3 |
18 | Rockies | -5.3 |
19 | Cardinals | -5.4 |
20 | Blue Jays | -5.8 |
21 | White Sox | -5.9 |
22 | Athletics | -6.2 |
23 | Phillies | -6.5 |
24 | Mariners | -6.6 |
25 | Padres | -8.7 |
26 | Mets | -9.2 |
27 | Angels | -11.0 |
28 | Yankees | -11.7 |
29 | Orioles | -14.8 |
30 | Dodgers | -16.5 |
The Astros — who have historically had a low payroll — top the list, furthering my theory earlier that smaller market teams are likely to be more successful in free agency. By taking lower risk players rather than taking established players who have a predetermined level of talent — one that is more likely to be overvalued — they have a lot less to lose and a whole lot more to gain. Thus, it’s not surprising to see some smaller market teams — or those who have been rebuilding for the past decade plus — near the top. Please not that the Cardinals, widely regarded by most to be the best run team in baseball, are near the middle of the list. This is due to the fact that they do a great job of building through the draft and cultivating their farm system.
Meanwhile, Dodger fans should close their eyes — same with Angel fans. A triplet of Jones, Pujols, and Hamilton signings have done their damage. With the Dodgers and Angels, the Yankees come in near to last place. Despite the Yankees being the “gods” of free agency or snagging the biggest names through trade, it seems that the players they haul in, as a group, generally underperform, since they are more often buying high than buying low.
Time will tell for 2014’s free agent pool. Will the big names win out or will teams turn to cheaper lower risk options? The Red Sox won the 2012 off-season by pursuing value free agents, but if everyone pursues the same strategy, maybe those free agents won’t be values anymore.
Max Weinstein is a baseball analyst. He has written for Fangraphs, The Hardball Times, and Beyond the Box Score. Connect with him on Twitter @MaxWeinstein21 or email him here.
A couple of problems with this:
You talk about bounce back season, which is year over year, but then take the average of the player’s career with their previous team to compare. This vastly skews your numbers, especially on a guy like Pronk. Also, you yourself talk about the effect of platoons, but do nothing to account for this confound and instead encourage it by averaging each player’s WAR over 650PA. This again greatly skews results, Rayburn a perfect example goes from +2.5 to an artificially inflated +5.9 on the season (comparable to Jacoby Ellsbury). Instead had you taken only the previous year and not added nonexistent PAs he would have still netted a 4.0 WAR upswing (-1.5 in’12 to +2.5 in ’13).
So great idea for an article, TERRIBLE execution.
I meant “change of scenery” not bounce-back; but my point remains the same that you have artificially inflated certain numbers.
I have to agree, the phenomenon is a guy having a bad year one place and then having a better year with a change of scenery. If you want to study that you need to look at players with only bad years in year one, look at what the change does and then compare that to normal ascension to the mean that would be expected if they had stayed put.
But inflating the WAR for a guy like Raburn proves the author’s point.
The point of using WAR/650 isn’t to say that Raburn was worth 5.9 WAR with the Indians, it is just a way of turning WAR into a rate stat. When speaking of “change of scenery”, we want to know how much better or worse the player was when he played. How much he played is circumstantial.
Noting that he was used differently by the two teams is legitimate. I don’t see it as a problem though. Part of the point of the article is that players on the lower end of the scale generally have greater upside, and are more likely to provider equal or better performance for a new team. Part of the reason for this is that these players are often flawed, meaning a team who know how to use him correctly can maximize his value for minimal cost. The Indians took a flawed player in Raburn and maximized their value from him by using him in a platoon.
A guy like Cano does not have this option, because a team who pays him is going to pay him to start, so the main variable at play is the rate at which Cano’s performance will decline with age.
*When I say they have a greater upside, I mean upside relative to how much they are being paid, or potential to exceed the value of their contract.
Thank you Bip for seeing the reasoning behind my methodology. I think the point was lost in the arguments over what constitutes a change of scenery candidate.
I am not arguing that the author is saying Rayburn is comparable to Ellsbury; I know that is not what he means. But that was an extreme example, just from his own sample size it artificially inflates Rayburns “jump” much more than a guy like Michael Barrett. Because you put Rayburn only in favorible situations then extrapolate those numbers over a full season you create an illusion. Whereas a guy like Barrett who faced both favorible and unfavorible matchups dos not have such a luxury. Max, I understand why you wanted a universal PA but it is specious reasoning. There is a reason why many players don’t reasch 650 PA. Sure is you want to assume that a guy who get 550 PA in all situations but just had a few days off will have the same metrics over 650, I get it. But to assume a platoon player will continue with the same numbers in sitations his own manager is actively avoiding using him in is just erroneous. By extrapolating WAR over 650 PA you are making some very flawed assumptions. It is not what defines change of scenery that I take issue with. Instead, I see the reasoning for your methodology, but it was unneeded instead just go straight WAR. I mean isn’t that why it exists to give the most realistic portrayal of comparitive value possible?
Exactly. Raburn was a change of scene candidate because he was used by his manager in unfavorable situations, and his new team used him properly, which improved his performance as a rate stat.
Obviously a guy who plays at a 6 WAR/650 rate for half a year is less valuable than one who plays at a 6 WAR/650 rate for a whole year, and Raburn obviously could not be the latter, but there is still value in having a guy that plays like an all star some of the time.