It’s a commonly held belief in football and indeed sport circles that athletes peak in their late 20s. HPN have decided to test this by measuring average player output in several key measures to see how players of different ages perform.

Below is the output curve for AFL players we derived from player data over the last decade:

It turns out that, on average, players hit their peak output the year they turn 27 and more or less hold it it until age 30 or 31.

It also seems that old players don’t get much worse. The 31, 32, 33 and 34+ cohorts don’t drop off very much, with the average 33 year old player still producing more than atypical 25-year-old.

The enduring output of older players makes intuitive senseas the league selects for talented 31 year olds more successfully than talented 19-year-olds. There’s far fewer 33-year-olds in the league because by the time players hit their late 20s, if they’re not still good enough, they are dropped or retire to make way for younger players as the pitiless procession of time marches ever onward.

The average retirement age for an All-Australian calibre player is around 32.4, the average for other players is around age 31. The end often comes very quickly, and seasons where a player doesn’t manage a single game are not included in this sample.

Below we’ll explain how this all comes together, and potential uses for the data.

The method

We assembled data on goals per game, disposals per game, games played, and Brownlow votes per game and have broken that up into age cohorts. Every season by a player from 2005 to 2014 is an individual data point.

For example, Daniel Hannebery turned 23 in 2014 so his 19 games that year, 0.58 goals per game, 25.2 disposals per game, and 0.58 Brownlow votes per game are attributed to the 23-year-old cohort of AFL players.

Collectively this approach gives a sample of over 6000 player-seasons from which to draw trends including 644 seasons by 21-year-olds, 498 seasons by 25-year-olds, and even 49 seasons aged 34 and up. It’s also blind to individual players, so gives us the picture of the average output of each age cohort.

The data

Here’s how the data for each contributing factor looks:

Naturally enough, young players get less games on average. The inclusion of games per season is important to the overall output measure because it implicitly factors in things like form risk, and injury durability.

(Players can no longer debut the year they turn 18 so this cohort of players is quite small – the last players to debut this young were in 2009 – Watts, Ziebell, Hannebery, Savage, Walters, Sidebottom and Shiels.)

Goals per game and disposals per game show similar movements towards the late 20s peaks, but different patterns for old-timers. Disposals hold up late into long careers while goals per game drops off past age 33. This would seem to point towards the type of players who have longer careers – less forwards, more midfielders or defenders.

13 of 49 records in the 34+ sample is Dustin Fletcher and blokes named Harvey. Ruckmen, defenders, and forwards all feature more prominently than true forwards which are limited to Richardson, Hall, Goodes and Grant, while only Buckley and Brent Harvey appear as goal-a-game midfielders. The 34+ sample is probably too small to draw reliable inferences from.

Brownlow votes, a measure of player quality, demonstrate the same pattern of rising towards the magical 27-year-old mark. They also hold up late into careers, providing further evidence that longevity is its own indicator of quality. It’s not that an individual player aged 33 or 34 will win the Brownlow or that players who get votes get more of them… it's simply that there’s less players who don’t get votes playing well into their 30s.

We also looked at clangers per disposal (which gently decline with age) and hitouts per match for ruckmen (which display the same improvement pattern towards age 27) but did not factor these into the multifactor output measure.

Putting it all together

These four variables fed into the multifactor output measure shown at the top of this post. Each was converted into a measure of “percentage of peak output” and then a simple mean taken of the four measures.

The resulting table of outputs looks roughly like this, with players peaking the year they turn 28:

We’ve also given estimates of how much output players have left. A typical player is over 50% “spent” at the end of the year they turn 26 (that is, on average players will have had 50% of the goals/games/disposals/Brownlow votes they can expect to have for their career as a whole). An elite player, with a later retirement age, might expect their career to be half over in terms of output at the end of the year they turn 27.

Use for estimating trade value

The initial impetus for this was in improving how we assess trade value. Last off-season we assessed every trade deal by comparing expected future output of picks and players, using the common currency of “expected career games” (with weightings for quality).

Our intention this season is to use this age cohort data to better project the “remaining career output” valuation of players. This will be the subject of an upcoming post.

Projecting improvement

We can use also use this output curve to project a pure age effect for each club’s list. This measure focuses only on the players who were at the club in 2014 and continue to be there in 2015. It measures how much improvement – relative to the rest of the competition – each club can expect in 2015:

In reading this chart, please remember that this is a raw cohort effect completely blind to anything other than player ages. There are a number of things this measure specifically does not do:

It doesn’t account for lost quality from retirements and trades and it doesn’t account for gained quality from traded-in players. This means that although Collingwood show as expecting a relatively high degree of improvement from their players, that’s due to the sampling of players who are still at the club. Collingwood lost a number of 2014 contributors (Beams, Lumumba, Ball, Maxwell, and probably Keefe and Thomas) which probably sees them static or going backwards just because the players which will show this relative improvement were previously relatively fringe contributors.

Similarly, it makes no allowance for Brisbane’s probable improvement from gaining Beams, Christensen and Robinson, or Port’s gain of Paddy Ryder. Balancing North gaining Waite and Higgins at the expense of Greenwood is also way beyond the scope of this exercise.

It doesn’t factor in contributions by very new but highly rated players. The contributions Patrick McCartin, Isaac Heeney, Jesse Hogan or Tom Boyd might make to their respective clubs are ignored here due to the limitation to players who have 15 career games.

It doesn’t factor in injuries and other misfortunes. Given that players peak in their late 20s and most players are younger than that, this model makes the pie-eyed optimistic assumption that every player improves and thus contributes their improvement. No club goes backwards in raw terms, with even Fremantle projecting as having its 15-game plus players getting 3.28% better on average. Of course in the real world, players get injured or experience other issues (for example, Collingwood are considered to have Keefe and Thomas as available…).

This is a raw measure of each club’s continuing list of players from last year and how they move along the output curve, relative to other clubs.

We can see that, all things being equal, GWS should expect by far the most improvement from their players. Most of their list and Gold Coast’s are below 24 years old, where the big year-to-year output gains occur. This graph should illustrate very vividly just how much upside these two teams have as a result of the concentration of 3 seasons’ of young talent in their lists. Other clubs with supposedly bright young futures just cannot expect anything like the same automatic improvement to fall into their laps.

Fremantle, Hawthorn, and Geelong on the other hand will be relying on other sources of improvement. This could be from their game plans, or their new trades or drafting gems, or a renewal from of injured players, or dumb luck, or whatever it is Ross Lyon intends to do.