Most soccer statistics are role-dependent - something we've discussed repeatedly in MLS context... but that basic truth has an important corollary when talking about player acquisition: roles are universal. If you transfer a player across teams or leagues, the success of his actions may change along with contextual difficulty and his role-dependent stats may change due to coach's discretion, but you can otherwise use past performance to predict the future.
Readers of SounderAtHeart may not be completely familiar with Andreas Ivanschitz or Nelson Haedo Valdez (though the deluge of transfer window information and discussion in these pages have likely resolved that issue to some degree), but may well be familiar with some MLS analogues. So, let's return to the set of top 90 (by minutes played) starting MLS attackers (forwards and attacking midfielders) in 2015, and add to this the performances of Valdez and Ivanschitz since 2009. 4 metrics spread out the dataset quite well: simple passes per 90 minutes, cross&long pass percentage of total passes; attempted dribbles per 90'; attempted aerials per 90'. Taken together, these split attackers into distributors, ball handlers, and vertical targets.
I've also plotted the individual season numbers for Ivanschitz (green triangles) and Valdez (red squares). The initials sit next to the data point representing overall average performance since 2009.
Take notice of the outliers, to make a few examples. The top aerial rate belongs to Adam Jahn of the San Jose Earthquakes, the top dribble rate to (who else) Fabian Castillo, the highest passing rate to Sacha Kljestan and Federico Higuain, and the longest distribution to (surprisingly) Fabian Espindola, Carlos Rivas, (less surprisingly) Sebastian Giovinco, and Pedro Morales. The "dust bunny" distribution of the aerial plot notably demonstrates the lesser role in distribution played by conventional target forwards.
Now, we want these metrics to fit in the same range of values within the dataset for the sake of comparison (i.e., one parameter should not influence comparisons between players more than another), so for each value I subtract the minimum value in the dataset and divide by the range (maximum - minimum), then calculate the Euclidean distance (remember this) to the sum of performances for Valdez, and then do the same for Ivanschitz.
|Player||Distance to Valdez||Player||Distance to Ivanschitz|
|Luis Solignac||0.071||Mauro Rosales||0.168|
|Tesho Akindele||0.078||Brad Davis||0.181|
|C.J. Sapong||0.081||Sebastien Le Toux||0.194|
|Ryan Hollingshead||0.150||Graham Zusi||0.194|
|Fanendo Adi||0.153||Rodney Wallace||0.197|
|Patrick Mullins||0.156||Ethan Finlay||0.199|
|Sebastian Jaime||0.164||Kelyn Rowe||0.222|
|Jairo Arrieta||0.171||Cristian Techera||0.235|
|Robbie Findley||0.176||Gabriel Torres||0.238|
|Lamar Neagle||0.178||Shea Salinas||0.246|
Valdez is not so dramatically different in role from Lamar Neagle, the player he most prominently replaces in Seattle's tactical setup, though he has a higher passing rate, a lower giveaway rate (apart from 2010, which seems an outlier) and better success rates on aerials and dribble attempts (even without any adjustment for league context). Distribution length for Ivanschitz in his last couple of years would rank with Giovinco and Morales... the average performance at ~21% is fairly typical for creators from the attacking midfield.
Notably, neither Valdez or Ivanschitz are high volume passers. I've previously discussed Seattle's difficulty in adapting reserve personnel to a possession game. The new acquisitions likely won't change that, though they certainly pass more frequently than Neagle and Chad Barrett. In games they both play wide in midfield, we should expect a greater possession responsibility to fall on the center... or for Seattle to shift away from the high-pass-volume approach it took early in the year.
Raw data for this work has been collected from OPTA via whoscored.com.