People say a lot of stuff about PDO and there are a lot of ways in which it gets attacked. It’s a weird little stat, not very commonsensical. Counter- intuitive, in fact. And whole screeds have been written to try to take it down from the base out. None of those have worked because PDO actually does what it’s supposed to do. It just doesn’t do anything more than that.

What PDO does–the only thing that PDO does–is highlight those players or teams who are getting better or worse results than they ought to be given how skilled they are. That’s all it does. That’s all it’s meant to do. It does that very easily and very efficiently.

To arrive at a PDO number, you add on-ice save percentage to on-ice shooting percentage. Most of the time we use 5v5 numbers but you don’t have to. It works a bit better that way because power plays and penalty kills have different levels of scoring than 5v5 play and every player/team sees a different mix of PP/PK and 5v5 time. So just leave the smaller chunk out. Obviously, for a team, on-ice numbers are all numbers.

With me so far? Good.

To interpret a PDO number, you look at the distance from 100. For instance, right now, 5 games into the season, Nashville Predator Filip Forsberg has a PDO of 114.7. It’s pretty high. It’s the 8th highest PDO in the league among skaters with 50 or more minutes at 5v5. Forsberg has yet to be on ice for an 5v5 goal against. He and his linemates are scoring on 14.7% of the shots they get on goal.

The greater the distance from 100, the more likely there will be a change. If it’s low, it will go up. If it’s high, it will go down. This is called regression to the mean, and the NHL (or any hockey league), the mean is exactly 100. Always. By definition. Every shot in the league is either a goal or a save. There aren’t any shots in the league that are not goals or saves. Thus league save percentage plus league shooting percentage is always and invariably 100. The average, then, is mathematically defined.

But, you say, there’s no reason for Filip Forsberg’s on-ice save and shooting percentage to equal 100. They’re not related to each other. How can the ability of his linemates to score affect the ability of his goaltenders to make saves?

They don’t. And they don’t have to. In fact, if they did–if everyone’s on-ice shooting and save percentages were always 100–PDO wouldn’t work. The value of PDO lies in it’s ability to show how far away one particular player or team’s experience is from the average. Basically, PDO takes advantage of a feature of how the numbers fall to describe a particular slice of the season.

An analogy: Imagine that you flip a coin 5 times and get HHHTH. You know that the average will be 50% heads, not 80%. The average is mathematically defined. You understand that if you keep flipping that coin, if you add data, it will–whether gradually or precipitously–move closer and closer to 50%. It will regress towards the mean. It may take 3 more flips to reach exactly 50% (all tails); it may take 20 more flips; it may take 1000 more flips. But it will get closer and closer over time.

In the meantime, that 80% heads rate tells you that randomness has had a strong effect on the outcomes you got in those first five flips.

The same is true of Filip Forsberg’s season. As he adds data, his shooting and save percentages will regress towards the league mean of 100. But just like flipping a coin, it may take 3 more games; it may take 20 more games; it may take more games than there are in a season. But, like flipping a coin, it will get closer and closer over time. In the meantime, you know that randomness in terms of the timing of goals both for and against has had a strong effect on Forsberg’s first five games.

What about talent? Some guys are better shooters than others. Some goalies are better.

Yes, this is true. However, two things are acting on PDO to bring it into line.

The first is that this is on-ice performance, not individual performance. Individual players have very little ability to consistently affect the shooting percentages of their linemates. And there are 5 players on the ice. Steven Stamkos may be able to score on 12% or more of all the shots he takes, but the 4 other guys he skates with aren’t. And Stamkos has very, very little control over his goalie’s save percentage. So as accurate as Stamkos may be, his on-ice shooting percentage will not be that high.

The second is that there’s a relatively narrow band of performance in these statistics. Goaltender performance is notoriously clustered across the league, for instance. It falls between about .895 and .939 (5v5) over a season the vast majority of the time, even accounting for goalies who don’t play much. Shooting performance occurs in a slightly larger spread, but there are still bounds to it. Only two players in 2013-14 had a personal 5v5 shooting percentage 20% or above. Only 18 (out of 792) shot 10% or above at 5v5.

Combine those two things with a reasonable level of ice time and you end up with PDO falling within a quite narrow band every year, for both players and teams.

However, almost no one gets to exactly 100. Some teams and players are in fact better at maintaining a slightly higher PDO than others. Some teams have both accurate shooters and great goaltending. Some players have both great linemates and great goaltenders. Some players and some teams are genuinely bad at both. These are players and teams we consider to be above or below average at shooting and goaltending. Their ability to be above or below average doesn’t negate the average. Nor does it negate the measuring system that shows where they are above or below average.

Again, if everyone did get to 100 every time and sit there, PDO wouldn’t tell us anything. It would be meaningless. The value of PDO lies in its ability to show distance from the mean.

If you’ve gotten this far you’ll notice that I haven’t even used the word “luck” yet. That’s because this word really seems to trip people up quite a bit. It calls up so many connotations for people: undeserved, fluky, without cause. None of those meanings are relevant here.

Instead PDO highlights the effect of randomness on a small sample. It says that if you add more data, you are more or less likely to see different results than you have so far. Filip Forsberg is more likely than not to be on ice for a goal against at some point in the 2014-15 season. It’s unreasonable to believe that he wouldn’t be. It is not reasonable to believe that the Predators will continue to see the same results from having him on the ice as they have so far.

In other words, the results that Forsberg has thus far experienced are probably not very representative of what his whole season will be, not due to anything he is or is not doing, but due only to the fact that he got a bunch of heads in a row. It doesn’t say anything about his skill, just about the difference between his sample so far and what is most likely to happen over the next 77 games.

PDO is a measure of variance more than it is of something as nebulous as “luck” or “Truth.” It’s one of the best predictors of the near future that we currently have and it really does what it says it does. It just doesn’t do anything else.