Soccer Sabermetrics - Challenges

The Challenges of Soccer Sabermetrics

To continue on with my post from yesterday, talking about soccer sabermetrics, there's a few things to consider before I dig into the actual equations. I mentioned this briefly the previous post when I said:

Obviously the key difficulty is whereas measuring a single player's performance in baseball is relatively easy (each player performs, in essence, individually), it's harder to do for true team sports like soccer.

And I want to expand on that. In baseball, a batter performs on his own when he's hitting. Yes, he's reacting to the pitches, but it's his swing, his power, and his strategy that leads to hits or outs. The pitcher on the mound is relatively isolated as well. He works with the catcher, but the average catcher's efforts provide only a small amount of support to the overall effort.

That's not true on the soccer field. It's uncommon for a single player to act wholly on their own on the field, except, of course, the goalie, who is a special case (which we will deal with later). Absolutely, there are players who elevate the play of the whole team, and there are players, Lionel Messi for example, who can make fantastic plays on their own. But they're the exception and not the norm. But sabermetrics whole point is to calculate reliable non-biased statistics to measure individual players in their sport.

So two things need to happen:

1. We need to find a way to isolate an individual player's efforts from those of their peers.
2. We need to develop a set of statistics that indicate the overall ability of team as well.

Measuring the Individual Player

A good measure of an individual player's skill would be shooting efficiency. How many goals does a player make for every shot on goal? How many times do they have the ball stolen from them when they have possession? How many shots on goal does a player take over their total time of possession?

These types of statistics relate as closely as possible to what a single player can do on the field. Obviously most of these examples given are specific to offensive players, but they give the clearest picture of a player's contribution to the team. This is one of those challenging aspects of applying statistical models to individual players on a team sport. Relating it back to baseball again, leaving the whole DH vs. pitchers hitting discussion aside for now, every player plays offense, and every player plays defense. Not so in sports like soccer, American football, basketball, and so on.

Measuring the Team as a Whole

For overall team statistics? How long does the ball stay in a specific zone on the field? Does a team play 70% of their matches in the mid-field? Then maybe their forwards are underpowered. Do they play most of the match near their opponents goal? Maybe they've stacked most of their powerful players forward, and you need to adopt a strategy of long balls towards their goal.

The biggest concern in this class of statistics is that these can depend very heavily on the opponent. If you have an average team who faces four of the best teams in the league at the start of their season then the stats may be skewed unfairly in a negative direction.

Furthermore, as teams change, these statistics become invalid. Last year's "Total Defensive Power" may not apply when the keeper retires and the team sweeper gets traded. So each year you have to redo these numbers. Perhaps you could apply a modifier against the calculated number to reflect the number of personnel changes, but that seems like a poor practice right on the surface.

Handling the Challenges

Looking at these two classes of statistics, there are a few other problems which are apparent:

1. Not all players play in the same position all the time. You may have a player who moves around into several different positions. The statistics need to be tailored to the positions the player is in.
2. Not all players play the whole game. You may have a player who scores all of the goals in the first half and then needs to sit out the second. The statistics you generate should not be solely based on the overall outcome of the game, but zero in more tightly on the player themselves. Of course, if you have a player who routinely loses possession of the ball which leads to more losses, you should probably have a way to track that as well.

Unfortunately, or maybe the better word is realistically, this effort is a first draft. These methods and algorithms will be honed over time. I think it's better to keep them simplistic this first go round. The more complex they are, the more likely they are to have errors or biases we want to avoid. But as we apply the methods over time we will start see what needs tweaked where.

Alright, now I think we're ready to start talking actual algorithms.

Soccer Sabermetrics

I've been thinking a lot lately about how to apply the principles of sabermetrics to soccer. For those who don't know, sabermetrics is a set of advanced statistics computed against a player's performance in baseball. Starting in the 1980's, a scattered group of dedicated baseball fans realized that traditional baseball statistics, like ERA and batting average are not good measures of a player's true performance on the field. So they came up with new statistical methods which gave a more accurate picture of how valuable a player is in a game.

One such example is On-Base Percentage plus Slugging (OPS). Traditionally, a player's offensive abilities is measured through batting average. However, a player's BA is measured as their hits divided by their at-bats. Hits are not the only way a player can get on base. Players can get on base by getting hit, or by getting walked. You may have a fearsome hitter who gets intentionally walked, resulting in a lower average, even though he's consistently making it to first base. (Insert your own crude joke here about balls, first base, and hitters.)

What happens when you start to measure players through sabermetrics is you find players who are undervalued by traditional thinking, but are highly valuable during the game. It was the application of sabermetrics that allowed the Oakland Athletics to win consecutive World Series championships with no-name players on a shoestring budget.

So with this high-level overview, you can start to see the appeal of sabermetrics, especially if they can be applied to another sport. It lets you see things in different way. You feel like Neo in the Matrix. You see the code underneath the game. Maybe a player that appears undersized on the field actually prevents twice as many goals against your team compared to the player who looks more robust. Maybe a player doesn't score ever but assists on every goal. She would be just as valuable up front during an attack as a player who makes the goals. The new insight lets you reasses your players and their abilities. As a geek and as a soccer coach, this appeals very deeply to me.

Obviously the key difficulty is whereas measuring a single player's performance in baseball is relatively easy (each player performs, in essence, individually), it's harder to do for true team sports like soccer.

But I have been putting some thought into how to do it, and I think I have some good equations to start with.

I will begin posting the equations here for discussion and refinement.

I hope you're willing to join me on this discussion.

Thanks!

Yesterday's Loss in Soccer

The kids' loss in soccer yesterday is still sticking with me.  I'm not sure why, though I know that I was hoping to win.  The team we faced was very physical, and I haven't taught my team to be like that, so I guess I was hoping for skill to win over violence.  Violence is probably too strong a word, but my daughter's knees are bruised up this morning and scraped.

You who know me know that I don't worry about bruised and scraped knees per se, it's part of childhood, but I don't like it when it comes at the hand of kids who are routinely pushing my little girl to stop her from dribbling the ball.

Very frustrating.

Plans for Soccer - I'm Coaching Two Teams! (Maybe)

Both Owen and McKenna want to do soccer next year, which is great, but they will be on different teams and they're both demanding I coach them, which is not so great. I've been talking to my wife about what I'm going to do, especially because we haven't been sure whether Owen's been serious about soccer but the paperwork came today asking me if I was going to volunteer again, so I agreed to coach both teams.

It sounds nuts. It is nuts. It was hard at the beginning coaching one team, but I enjoyed the hell out of it. I got to spend time with my friend Jeff which was awesome, spend time with my kids, and make new friends, so those were all pluses. My kids really love soccer and both are decent at it, so I want to continue to encourage their interest.

I don't even know if they'll let me coach two teams or not. Some of the other coaches have done it in the past, so it shouldn't be a big deal, and Jeff has said that he might coach this year too, so maybe I'll let him have a team and take a back seat. I don't know yet.

What I do know is I really love coaching, more than anything I can remember in a long time, and as long as I enjoy it I'm going to keep doing it. Hell, at this point, if I could get paid to do it full time I'd jump at the chance. I mean that seriously.

Soccer Practice Yesterday!

I ran my first soccer practice yesterday.  It went very well.  I've got 9 kids on my team, including my two, and we played a lot of games.  I made it clear to the parents that my goal is not to win the World Cup, or even to pressure the kids into winning their games, but rather to teach them the fundamentals of playing soccer and having fun.  One of the things I said clearly was "Even if we lose every single game we play I will consider this season a success if the kids come back for the spring season".

I truly mean that.

And the great thing with coaching at this level (U-6) is that I get to be a big kid.