Weighted Player Ages

It’s become common to say that the NHL is getting younger. It’s an understandable assumption. Recent work has shown players peak earlier than previously believed, and young stars breaking into the league have received a lot of media attention. But is it actually true? How has the league’s average age changed over time? And are there any trends in team age that lead to overall success?

I looked into the age of the league’s players by creating averages weighted by different performance metrics such as points, shots, and time on ice. I used weighted averages because an unweighted measure does not account for how important a given player is to their team. For example, when figuring out how old the Islanders generally are, Eric Boulton’s 1 game played at age 39 should not count equally with Nick Leddy playing every night at age 24.*

This post has 2 parts. First, I used Hockey Reference data to create weighted ages for the past 31 seasons. I also look at a smaller but richer dataset from War On Ice to show that these weighted averages do not meaningfully vary regardless of the measure used for the weighting. Second, I looked at whether teams who performed well in a given year had any particular age compared to the rest of the league.

I found that from the mid-1980s to 2005, the NHL gradually got older from an average of 25 to 28. In 2005, the salary cap was introduced and the trend towards older players reversed. Instead, the average age fell by about a year between 2005 and 2010 and has remained flat since. Despite perceptions, the league has been staying at about the same average age for the past 5 years. Finally, the teams that performed well in the playoffs were not consistently older or younger than the rest of the league.

*Writing this sentence guarantees that Boulton will play another game between me drafting and publishing this post. My apologies, Islander fans.

Part 1 – Historical Trends

Hockey-Reference’s data goes back decades, which allows for a long view of how the league’s average age has changed over time. In the below graph, I weighted each skater’s age by their shots on goal:


HR Age By Shots

As mentioned in the intro, the league’s age has had three main phases since 1985:

  1. 1985 – 2005: The average age rose steadily from 25 years old to 28
  2. 2005 – 2010: With the introduction of the salary cap, the aging trend reversed and the league got gradually younger to about 27
  3. 2010 – Present: The average had remained flat at 27 years old

How valid is the decision to weight by shots on goal? The weighted age could be based on any of a number of different statistics that all represent a player’s general importance to a team. The figures are nearly identical when the weighting is done based on goals or points instead, but all of these measures are more basic than what is generally preferred in modern analysis. We don’t have more ‘advanced’ statistics with larger samples like shots or scoring chances for. However, we can get these measures for skaters in a shorter timeframe if we turn to War On Ice:


Average Age by Weight Measures

The “other weights” used here are goals, points, primary points, scoring chances, shots, and time on ice. None of these significantly change the absolute value of the average age or its trend over time. Weighing by AAV shows a similar trend, but the values are about a year higher because the structure of entry-level contracts ensures that money is more heavily weighted to older players. (Note that the absolute values are a bit off from Hockey-Reference’s due to differences in the date cutoff used to determine a player’s age in a given season. The year-to-year change is nearly identical in the overlapping years  of the two datasets.)

In sum, all of the different measures show the same trends. While not surprising, this rules out the possibility that, for example, younger players were producing a greater share of the league’s points but not getting additional ice time. Overall, this shows that there’s no significant downside to using Hockey-Reference’s shots on goal as a weight. It does not deviate much from preferable non-financial measures.

Part 2 – Team Age and Success

Does this data carry any importance for decisions being made by teams today? To answer this, I adopted a method used by Moneypuck in his How To Build A Contender series in which he focused on the four teams that made the conference finals each year. I compared the average age of those teams (the Contenders) to the rest of the league that year (the Pretenders):

Contenders and Pretenders

The contending teams tend to be slightly older than the rest of the league, but this is not always true and it is not by a large margin. Overall, I am reluctant to conclude that a particularly old or young team is beneficial.


No GM is going to make decisions based on his or her team’s average age, but it’s still an interesting topic from a descriptive perspective. I found that the age of the league has remained flat for the past few years, which is contrary to what many people believe. It remains to be seen if this trend will continue in the years to come. I would not be surprised if the increased use of analytics in NHL front offices lead to a shift towards even younger players on favorable contracts.

While not the most in-depth topic, there are a few other items that could be explored. First, it could be worth investigating the age distribution within each team rather than just the average. Second, in a future post, I’ll break down these weighted averages by team so that everyone can see how a team is structured compared to the rest of the league. At this level, there are also some interesting differences between the different weight measures. All of the data files and R code used in this post are available on Dropbox here.


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