Numerology: MLS stats gurus take on the salary cap
Welcome to Part 2 of our interview with four MLS performance analysts. Today we'll be looking at how they face the unique challenges of MLS, what they look for in a player and how they think the game should be played.
Click here for Part 1.
Devin Pleuler: What challenges does MLS’ single-entity structure and salary cap pose for you, your job and performance analysis in general? Are other things easier?
Timothy Crawford – New England Revolution: The salary cap just ends up making things more interesting. Without it, the goal would simply be to assemble the best team money can buy. With the addition of the cap constraint, the game is more complex and it allows every team to be on a somewhat level playing field looking for a different advantage other than how much money they can spend. In MLS, analysts can help find the best way to maximize the same (or at least somewhat similar) resources that every other team has. While MLS tries to keep the playing field as level as possible, it’s my job to help the technical staff find “valuable” players.
David Lee – New York Red Bulls: I think the salary cap and single entity structure are actually a huge benefit to the potential performance analysis can have on a team. Trades for example are unique in soccer in MLS and this type of deal (player-for-player) allows the possibility of doing detailed analysis on the possible impact of each player involved in our team to, hopefully, make informed decisions. It has also allowed me to do some detailed statistical analysis into the roster compositions of each team and come up with some ideas for how successful teams in MLS are built and just gives us a little more information, which hopefully helps to guide our recruitment strategies.
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What do you believe is the most under-valued player characteristic in MLS?
Rui Xu – Sporting Kansas City: Scheme-fit/synergy with teammates. Soccer’s very interesting because teams are composed of a group of individuals with very specific and unique skillsets, who have the potential to become greater than the sum of their parts. That’s not unique to the sport, but I think it’s a little more obvious with soccer in that if you have RB/RW pairing that synergizes, they are constantly overlapping and covering each other’s mark, which creates a lot of pressure on the defense. If they are not on the same page, the defense can be a lot more organized and more difficult to break down.
For example, if you have a CM who can drop passes on a dime, but none of his teammates make the right run for him, then he’s not very effective. If there’s a RW who always makes smart, darting runs but doesn’t have teammates who can make pinpoint passes, then he’s not very effective either. If you put both of these two on the same team, then their combined worth is greater than just the “true talent levels” of the individual players.
Pleuler: What tools are used by your club for performance analysis? What improvements could be made to these tools? What capabilities do you wish you could have in the future? Are any of these tools open-source? Should they be?
Lee: We currently use Prozone to provide us, postmatch, with match videos and detailed statistical breakdowns of every MLS match while we use Sportscode as our main video platform and particularly in a live environment to create statistical reports and instant on-demand video during the game for our coaching staff as the main two pieces of software.
Neither of these are open-source and, while I can understand why it would be a nice idea to have them as this, I think the reality is it would be too difficult to achieve. One of the biggest problems when it comes to "coding" (creating the statistical information) a soccer match is the operational definition of each possible event needs to be very precise to ensure the consistency of the data.
Working towards an open-source project with many people being able to code games (and it would be impossible for one person to code the number of games required individually) I believe would create more problems than there currently are in how reliable and accurate the data becomes, which can at least be lessened when one company owns the analysis. The integrity of the data in an open-source environment would be questionable which would be a big failure when the No. 1 issue for teams is the accuracy of any data if we're going to make important decisions on the basis of this data.
Pleuler: What are your thoughts on “anti-football”? Does it exist? Is it damaging to the growth of the game? Could decisions via performance analysis be construed in such a way?
Crawford: It all revolves around what your objectives are. If your objective is to maximize points, then the data may steer you in that direction. If your objective is to score lots of goals, then the data may take you another way. As an analyst, we have to take the team’s objectives and, hopefully, figure out a means to help achieve them.
Lee: I don't think "anti-football" exists; one of the beauties of our game is the very different styles that teams can play and have the same effect: winning matches. Personally, I like watching Barcelona play just as much as the next person and in an ideal world I think most people would like to see more teams try and play and possess the ball and move as well as they do. I think the defensive stance many teams take which is considered "anti-football" is actually a good thing for the game as it will challenge the best teams to be even better and come up with strategies to beat this type of system.
There is definitely a train of thought that performance analysis has the potential to take the "fun" away from the game and less about individual talent but I, perhaps obviously, vehemently disagree with this viewpoint. That's not the intention of me or anyone I know in this position and never want to stifle the creativity of any of our players but actually help them to use this to even better effect by giving them information on when/where to use it perhaps to more likely create a goal.
Xu: Of course it exists. It exists in every timed sport, and it usually occurs when one team is hugely favored, and I think that it’s a very rational tactic in those cases. Think about it mathematically; there is a larger variation in performance over a smaller sample size, so the team playing “anti-football” is trying to keep the ball in play for as little time as possible, and relying on that variation to eke out a point or three.
You see it in American football, with the underdog running the ball a lot to waste time and have as few possessions in the game as possible, and capitalizing on fumbles or interceptions by the other team’s offense in their own half. You see it in basketball, with the underdog running down the shot clock every time, to create as few possessions as possible, and then capitalizing on fast breaks off of turnovers. This type of play is just an artifact of playing a timed sport, with a relatively wide disparity of team talent within a league.
I think that the concern that performance analysis might lead to less attractive soccer is a valid one, but not one that I necessarily buy into. You could make the argument that it happened in baseball (higher OBP = more runs = longer games; needing to steal at 75 percent rate to be valuable = fewer steals = fewer exciting plays, etc.), but I think that, ultimately, fans want to see a winning team. I would guess that they are more inclined to go to the stadium to watch a winning team play “unattractive” soccer vs. going to the stadium to watch a losing team play attractive soccer. There’s also the fact that statistical analysis can change how fans watch the game and how they come to appreciate the game. Rather than buy into traditionally accepted narratives, fans may start to think more analytically during a match, which makes it more interesting to them.
That ends Part 2 of the interview. Check back on Thursday as we tackle the problems of formation vs. shape, and the sticky wicket that is possession.