Nichols and Dime: Does Defense Get Better With Age?

As players get older, the belief is that they learn the tricks of the trade and get better at defense. During their first few years, they’re ill-equipped and unable to have a positive impact on defense, despite their superior athleticism and energy.

Do the numbers support these beliefs? We must turn to the always-useful Basketball-Reference.com. Using its Player Season Finder, I put together a spreadsheet containing every season from every player (minimum 500 minutes played) for the past five years. Using this data, we can see how Defensive Ratings change as players get older. Defensive Rating was developed by Dean Oliver, and it estimates the number of points a player allows per 100 possessions. Obviously, a lower number is better. To read more about it, check out the Basketball-Reference glossary. Let’s take a look at the chart:

overalldrtgbyage

I limited the age range from 19 to 36 to avoid outliers. On the x-axis, we have the age, and on the y-axis, the average Defensive Rating for that age. The results seem to confirm the common belief. Younger players tend to post higher (worse) Defensive Ratings than older players. Real life doesn’t work perfectly, so there are some fluctuations. However, the correlation is strong, indicated by the relatively large R^2 (explanation here). Therefore, there does appear to be something to the notion that players get better defensively as they get older.

We can also produce a similar graph using Defensive Win Score, a similar measure to Defensive Rating (for more information, check the glossary again). Basically, DWS is the amount of wins a player adds to his team through his defense. The chart is below:

overalldefensivewinsharesbyage

The R^2 is slightly smaller, but the general idea is the same. Players get better defensively as they get older. Not considerably so, but statistically significantly so.

However, we must approach these results with caution. Let’s say, hypothetically, that big men generally have lower Defensive Ratings. Let’s also say, hypothetically, that big men stay in the league longer than their shorter counterparts. These two scenarios would combine to make it look like players get better defensively with age. What’s a simple way to account for complications such as this? Take a look at the data position by position.

To start, let’s look at centers:

cdefensiveratingbyage

The results appear to be clear as day here. The line is a little wavy, but centers sure seem to get better defensively as they get older. The average for 35-year olds is over three points per 100 possessions lower than the averages for 19-, 20-, and 21-year olds. Do power forwards react the same way to age?

pfdefensiveratingbyage

Simply put, yes. These results tend to go with common logic. Many raw and young big men commit silly fouls, ignore help defense, go for the spectacular block too often, etc. However, we should not treat these results as gospel, as I will explain later.

How about small forwards?

sfdefensiveratingbyage

Just like the previous two positions, it appears small forwards age well, at least on the defensive end. The magic number for this position appears to be 29. Small forwards that were at least 29 years of age during the last five seasons performed much better on the defensive end than their younger counterparts did. Let’s take a look at shooting guards:

sgdefensiveratingbyage

We keep seeing the same results. No matter what position you look at, the story is the same. Players get better on defense as they get older. Finally, let’s take a look at the inevitable and see how point guards get better defensively with age:

pgdefensiveratingbyage

Woops. That trend line has an oh-so-slightly negative slope, but it’s not exactly a great fit for the data (the R^2 is practically 0). Clearly, then, point guards don’t follow the same path as other positions. Older is not better in this case. For a position that often relies so much on speed and quickness, this makes sense. However, even point guards in their prime (around the age of 27) don’t perform significantly better than the young ones.

To wrap this up, we can make the following statement based on the data: Except for point guards, players generally get better on the defensive end as they get older. However, there are a number of issues to address before we go too far and actually believe that bold statement I just made:

  • The statistic I used, Defensive Rating, is far from perfect. Defense is one of the hardest things to measure accurately with statistics, and this measure is no different. It is highly team-dependent. Good defenders on poor defensive teams will be underrated, and vice versa.
  • Although there is a correlation between age and Defensive Rating, that doesn’t mean it’s a causal relationship. It may not be that all older players are better defenders. Perhaps the only way to stay in the league if you’re getting older is to play solid defense, so the ones that don’t are selectively removed. Or maybe strong defensive teams like to acquire veterans, which boosts those player’s Defensive Ratings.
  • Finally, although it is a pretty large sample-size (five years of data for 1,641 data points), the data still could be misleading. For example, if there happened to be a strong crop of old centers during the past five years, that position’s results may be inaccurate. I limited the sample to five years because I don’t like using data that is very old. The style of the NBA changes constantly, so using information from say, 10 years ago, may not be smart.

UPDATE: After doing some more research, we may have to re-think things. Thanks to suggestions by Ryan Parker and Mike G at the APBRmetrics board, I decided to plot the average change in Defensive Rating (the difference between the current year and the last) for each age. It is below:

defensiveratingchangebyage

Looking at the graph above, we notice a couple of things. First, over the last five years, players of all ages tend to get worse defensively on a year-by-year basis. Whether it’s because of improving offenses or declining defenses, scoring has increased during each of the last five years.

More importantly for this study, we see that older players are declining faster than younger players are. For example, during the last five years, a 26 year-old is likely to have a Defensive Rating 0.5 points higher than he did a year ago. On the other hand, a 35 year-old is likely to have a Defensive Rating 1.5 points higher than he did a year ago. The difference between old and young isn’t much, but we can probably say that old isn’t definitively better than young.

Like I said in my original post, selective bias may be a problem. After all, this most recent research doesn’t dispute the fact that as a whole, when you look at all the old players, they tend to be better defensively than the young players. But that’s not because they got better as they got older. The data shows this. What we may be able to say now is that aging doesn’t improve your defensive abilities, and if you want to stay in this league as a veteran, you better be good at defense, because teams will “selectively remove” you from the league if you’re not.

Check out Basketball-Statistics.com for much more like this, where I presumably get things right the first time.

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I agree with Nick. This measurement needs to be horizontal, not vertical. My first thought would be to take all the players available at the end of the data set, and simply track those persistent players over their careers, and see if there is an improvement. That would eliminate the depression in the first few years as ineffective players washed out of the league.

It may not be fair to track only the players who still played at 36. Maybe instead only include players who have a 10 year career. Also, it would be interesting to track the players not based on age, but on how many years they have been in the league.

It might be nice to see an analysis on an individual level, i.e. does player A's defense get better with age. Then you could aggregate the results. Using this method should allow you to control for bad defenders being weeded out of the NBA at an early age.

a good attempt - but defence is impossible to measure quantitatively...which is no fault of yours.
unless they start tracking completely subjective items such as - "great vs average vs bad":
close-outs
help/rotation
communication
intimidation
shot challenges
box outs
loose ball hustle

This seemed pointless, interesting and pointless. Which is odd I suppose

I absolutely loved this.

Great work. I can't find the stats (I know Wayne Winston has them and won't share them with me although he has posted some in his books), and you may be able to get them from basketball reference if you asked nicely, but I was wondering if you could use adjusted minus for defensive ratings.

Wayne Winston has it in his book, where the Mavs stats team both adjusted +/- and seperated them into simply adjusted plus and adjusted minus. If you use just minus, I think it may be a better use than just defensive rating, and see if the correlation is similar (I'm guessing it is).

the strangest result of these graphs is that there is a distinct valley for all positions at age 34. it seems strange that 34 would be the age at which players have a defensive revelation, although it might be related to the fact that older players can only get on the court if they play good defense.

Methinks you may be missing the boat on this one, but cannot clearly tell from your writeup. The problem I see is that you appear to lump all players by age. However, a player that cannot compete at the NBA level will be gone within 2-5 years, while the higher-ability players stick around the league longer.

Couple longetivity-based-on-ability with the fact that older players get more calls than younger ones (I'm from MN - take a look at footage of KG early years vs now for a clear indicator of veteran calls), and you have clear reasons why these factors should indicate that older is better.

Are you saying Derek Fisher isn't a defensive stopper anymore?

Seems like you would need to track the SAME player over yrs, since the above stat has an attrition bias (i.e. crappy players have crappy ratings, but are out of the league, or play fewer than x minutes, after x number of yrs)

Hi there -

You might want to consider an age squared term in your regression. Because we might expect defensive performance in increase with age, but at a decreasing rate.

Just a thought.

Great work. The PG thing is bad news for Bulls fans, heh.

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