Valuing individual soccer players more precisely and accurately is likely to require newer, better data. That is, goals and assists just won't get the job done anymore---not that it ever really did. It is no easy feat trying to pinpoint Graham Zusi's value to Sporting Kansas City, or Diego Valeri's Value to Portland, or Kyle Beckerman's value to Real Salt Lake. That said, there is a position that is probably a littler easier to value: the goalkeeper. I don't think it's a stretch to say that at least 90 percent of goalkeeping value is tied up in protecting the net---as opposed to distribution, for instance. Thus it is our mission to begin quantifying a keeper's ability to keep the ball out of the net, while attempting to control for his defense's ability. No more of this "Jimmy Nielsen is God's gift to the netting" BS. At the same time, we can assess the shooting traits of all field players.
With the current data available publicly, we can look at each shot's location of origin---as we have already done on the site for 2013---and then also each shot's eventual target on or around the goal frame. Knowing how close the shooter was to the goal and where he placed the ball can give us idea of whether a keeper should have saved it. With our newer version of Expected Goals, a statistic such as "Goals Above Average" could be created. Our second version of updated goalkeeper ratings can be found here.
Some components of each shot to consider:
- Shot Origin
- Shot Placement
- Headed or kicked
- Run of play vs. free kick/corner kick/penalty/throw-in
- Clean save, rebound in box, corner conceded, or clearance
And now, what can we do with it?
- Goalkeeper ratings
- Individual stabilization rates, as calculated by Russell Carleton for baseball
- Markov Processes: given the current state of the game, what's likely to happen next? How long will it take?
We are building the databases now, and with every new game in the data set, our understanding of goalkeeper values deepens.