An exploratory analysis of the top 20 AFL goal scorers during the
2023 season was performed. Data was collected using the r package
fitzRoy, which scraps data from various sources such as AFL tables and Footywire.
The number of goals each player scored for each game of the 2021 season was summed and then sorted by the top 20. This list is provided in the table below:
library(fitzRoy)
data <- fetch_player_stats_afltables(season = 2023)
| ID | First.name | Surname | goals | Playing.for |
|---|---|---|---|---|
| 12421 | Charlie | Curnow | 81 | Carlton |
| 11713 | Taylor | Walker | 76 | Adelaide |
| 12563 | Nick | Larkey | 71 | North Melbourne |
| 12025 | Toby | Greene | 66 | Greater Western Sydney |
| 12199 | Joe | Daniher | 61 | Brisbane Lions |
| 12277 | Charlie | Cameron | 59 | Brisbane Lions |
| 12017 | Jeremy | Cameron | 53 | Geelong |
| 12655 | Oscar | Allen | 53 | West Coast |
| 12349 | Kyle | Langford | 51 | Essendon |
| 11548 | Tom | Hawkins | 49 | Geelong |
| 12321 | Jesse | Hogan | 49 | Greater Western Sydney |
| 11954 | Luke | Breust | 47 | Hawthorn |
| 12639 | Brody | Mihocek | 47 | Collingwood |
| 12594 | Aaron | Naughton | 44 | Western Bulldogs |
| 12454 | Eric | Hipwood | 41 | Brisbane Lions |
| 12851 | Oliver | Henry | 41 | Geelong |
| 12983 | Jye | Amiss | 41 | Fremantle |
| 12728 | Ben | King | 40 | Gold Coast |
| 12083 | Jamie | Elliott | 39 | Collingwood |
| 12704 | Jack | Lukosius | 39 | Gold Coast |
We then investigated the top 100 goal scorers of the 2023 season and tabulated this against their respective teams. Overall, Collingwood had the most players in the top 100 and West Coast had the fewest. This is clearly reflective of the actual results (as per the ladder standings) for the season.
Whilst goals scored are important (more goals = wins), we have to be cautious when interpreting these results. In particular, all positions (including defense) were lumped together, so many of the good non-goal scoring players were excluded from the top 100 list.
Interestingly, an inspection of number of kicks by goals scored (per game) reveals a very unique distribution:
Here, it appears that more kicks = more goals up to a certain point only. This is unlikely to be true however. What’s most likely occurring is that we are picking up on other positions as well within this plot - which future studies should investigate.