Homeward Bound: The problems of the ‘home’-rule

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The problems of the ‘home’-rule, and how to pick match-day’s best defensive players

A quarter to a third of the points of a defender come from shut-outs. Consequentially, everyone is constantly on the search for the strongest defense. A common advice in this situation is that a defense at home – that is to say, a keeper or a defender with a home game – is preferable to a defense on the road. Teams concede more goals away from home, or so the reasoning goes, and that is why, for example, it might be an idea to rotate your keepers (selecting a pair of goal keepers whose teams have an alternating schedule, using the home-away-rotation table), in order to maximize the home games.

Personally though, I never much liked that advice, and I’ll try to lay out my problems and my own approach below.

At first glance, everything is easy. Take the 2014 season: 388 goals against the home teams (HGA) vs. 536 goals against the away teams (AGA) in all of the 323 matches, or only 1.20 HGA per match vs. 1.66 AGA per match on average – which is to say that home teams, indeed, generally and on average concede less. If you pick any random defender or keeper, you best grab one that has a home game, because his chances for a clean sheet are higher. We have a rule.

The Problem

So isn’t that great? Why do I even write this article? Well, the key phrase is “pick any random player”. Usually, we do exactly the opposite: we pick a defender or a keeper we think (or know) is part of a good defense, which throws a spanner into this consideration. Averaging over all teams does not give us what we want: an answer to the question whether it might be better to play our good defender or keeper, even though he has an away game, or a different defender, who does not have a home game – but might be part of a weaker defense (since that is all we can afford, for example). To decide this, we have to separate the individual teams. Again using the 2014 figures, the result is this:

We see quite large differences, and that is the problem. To illustrate: Let’s assume it’s 2014 again, and you were one of the many people (including me) who had SKC’s Kronberg for a keeper because he was a great bargain. Do you need another keeper for their away games? Well – no. SKC’s defense isn’t the best, but it’s equally good away and at home: They allowed 21 goals at home, and 20 goals away. And the same is true for the Whitecaps: 19 goals allowed vs. 21 goals allowed is a negligible difference. If you bought into their defenses, swapping players does not make sense.

Of the other hand, for most teams it does make a difference. Assuming a correlation between a lack of conceded goals and clean sheets (there are outliers, but by and large, the assumption holds), you can, all things being equal (which they aren’t, see next section), improve your chances by transferring or benching players to increase the number of home games, resp. by picking players from defenses that have a larger number of home games than others in the first place. Most notable here is Seattle (0.94 at home, 2.0 away); together with DC United they are the best option for the keeper rotation-strategy (18 home games, 4 away games until the Gold Cup, GA/90 of 0.93), based on the above numbers.

But the point is, a general rule of “stick to home defenses” is likely to lead you astray, since if you try to force the issue – say, by playing a (shaky) Portland defender over a (quite good) Vancouver defender without looking at it further, just because the former has a home game and the latter does not – you may end up coming out worse for it. You need a table like the one above, to truly get to the bottom of it, which prevents it from being a simple rule of thumb – and that was the reason to create it in the first place.

Match Difficulty & Quantifying Defenses

That aside, however, the bigger issue is that the home/away difference is easily dominated by other effects. What if the home defender has a match against a team that has been churning out goals, whereas the away defender might face an offence that is struggling?

I therefore prefer a nuanced approach, tailored specifically to the situation. Does my defender or keeper play against a struggling offence, or against a red-hot one? For me, that is the most important question, and the most immediate way I decide who plays and who doesn’t. The match difficulty tables are a good first indicator for that. Only afterwards I would consider whether the player’s significantly worse on the road than at home, so that it might be advisable to swap him for that reason.

Last year, I in fact ignored the latter point most of the time. It is an interesting question, however, so I’ll sketch up how I would try to quantify what a ‘good’ defense is and what not.

At the beginning of the season, all anyone can rely on are the impression from watching the game. Numbers aren’t really useful, simply because there aren’t any. Later on, though, it’s possible: average the conceded goals, in, say, the last five home games resp. away games, and compare the numbers – that will give you an idea of what the defense of a team is currently like, and whether there is a difference between home and away games. A similar thing can be done to quantify the offence, if you want to have a measure for the strength of their opponent in the match, for example.

The scores of the last matches are conveniently accessible in the player info box in the Fantasy manager (Click on player → ‘View Information’ → ‘Schedule’-tab), so you only need a calculator and can operate directly in the game. Add the goals and divide by the number of games: that’s your average.

As an example, let’s look at the Whitecaps at two different points in 2014. On match #9, the first five home results were these: 4:1, 2:1, 1:2, 2:2, 3:2. (1+1+2+2+2)/5 = 1.6 goals conceded on average. This is worse than their overall average, and the reason for that is that their back line improved massively after Kendall Waston came in in the last third of the season: The last five home games went 0:0, 2:0, 2:1, 2:0, 1:0, with an average of (0+0+1+0+0)/5 = 0.2 goals conceded.

I don’t think it’s possible to learn too much from the individual results, since the outcome of a match depends on far too many variables, but averaging the results in such a way might just do the trick. I haven’t tried it myself – I’m looking forward to test it this season. If I find the time, I’ll evaluate the results in another article once the season is well under way.

Bottom line

Generally, we need to keep in mind that all we’re talking about here are probabilities. CS and the number of conceded goals over an entire season do correlate to an extent, but individual results are essentially random. Even if we somehow knew just what the numbers were, we still would have to decide whether increasing our chance for more points by X % is worth the money, a FT or even -4 points.

I think there are better rules than ‘stick with the home defence’, especially if you try to decide who to transfer in and out for the week. What’s important in my opinion are the actual match-ups, not so much where the game is played. Consequentially, I also never use keeper rotation to maximise home games. I prefer to spend the money elsewhere than on keepers that sit 50% of the time. On the other hand, that’s just me – figuring out different strategies than other people use is half the fun, so you might think this is all wrong, even as I hope you found it at least slightly useful. I’d be happy to hear your opinion.