Can i find similar players using a clustering method like the k-mean algorithm? I am working on a data mining project on NBA data. I want to make a recommendation system similar to the google one, where you search for players and you get recommendation for similar players. I intend to make such system based on their stats. My data looks like this

14  Tony Allen  709     357     15386   2178    4580    0.476   102     363     0.281   2076    4217    0.492   0.487   1220    1701    0.717   804     1567    2371    942     995     299     964     1675    5678

15  Al-Farouq Aminu     431     228     9988    1119    2592    0.432   188     607     0.31    931     1985    0.469   0.468   530     731     0.725   618     1724    2342    488     413     245     540     813     2956


One approach I have in mind is using k-means clustering, but I am not sure how I will use the clusters to find similar players. Each cluster will have hundreds of players, I will need further filtering. 

Does anybody have any suggestions/tips for handling this problem?
For finding similar objects, k-means does not make much sense.

k-means is based on similar objects. If squared deviations don't work for your data then k-means will not work either.

Thus, instead of using k-means, just use a nearest neighbor search without k-means.