In a classic contest, Hawthorn kicked the last three goals to defeat Port Adelaide by 6 points in the inaugural virtual Grand Final.
The Hawks led – barely – at quarter and half time, before the Power turned it on in the third, kicking away to a 13-point break at three-quarter time. But in the final stanza, Hawthorn surged back to tie it up at 79 points apiece with only minutes remaining on the clock. Mitch Lewis delivered the winning goal, with the Hawks resisting a final Port Adelaide surge to capture the premiership.
The Hawks finished 5th after the 11-game regular season, and won four finals en route to claiming the Virtually Season 2020 flag.
Port Adelaide’s Grand Final defeat was their only loss of the season.
Thanks to everyone who followed along with the season – it was a lot of fun during the cold, football-free weeks. Special thanks to the trusty model authors who fronted up each week with their simulations: Stattraction, Live Ladders, Aflalytics, and The Flag, who modeled the Grand Final.
Thanks to Stattraction, we have Coleman Medal results:
Yes, that’s a shared Coleman. Also a low-scoring Coleman, thanks to a simulation bug that afflicted the first half of the season and stole goals from each team’s main scorer. Also scores in general were down, since we were simulating 16-minute quarters.
Finals begin Wednesday June 3rd at 7:50pm EST and continue almost every night for the next week.
Since there is no actual football, we will do the next best thing: simulate it.
With the support of the world’s best football computer models, Squiggle will play out each and every cancelled game in real-time, as if it were really happening.
Goals. Behinds. Score worms. Quarter time breaks. They will all unfold here at the exact same time the match is supposed to be played.
It will look like this:
This will continue all season long, game by game, until actual games resume. We will track a virtual Ladder and Top Eight. If, God help us, we don’t get real football back by September, we will hold virtual Finals and award a virtual Premier.
This Thursday night at 7:25pm Eastern Time, Collingwood will play Richmond in the first virtual match in real-time, here on this site. You can check in and see it happen.
I believe Australia needs football. I need football. Or, in the absence of the real thing, a simulated version from computer models.
How It Works
Usually models make predictions about the most likely outcome of a game (e.g. “Collingwood by 4 pts”). But they can also generate batches of simulations, where if Collingwood is a 60% win chance over Richmond, then in 100 sims, Collingwood will win 60 of them. In the other 40, Richmond will win. (In a few, unusual things might happen, like a team scoring over 120 points.)
Participating models supply Squiggle with their sims. At match time, Squiggle randomly plucks one out and unspools it in real-time. No-one knows in advance which sim it will be.
My Promise To You
This is as rigorous a process as I can make it, drawing from the work of highly talented football analysts and math wonks who created the world’s best football models.
There will be no bias or fiddling. Just hard maths and cruel random variation.
It’s not the real thing. But it’s virtually season 2020.
Here’s Squiggle’s own in-house ladder prediction for 2020 (not to be confused with the Aggregate Ladder, which combines this plus predictions from many other AFL models).
This prediction accounts for:
Trades, retirements, delistings and returns
2020 preseason form
Injuries to players listed as “Season” or “Indefinite”
The league was very even in 2019, so it’s going to be harder than ever to make a good ladder prediction. But this is what I’ve got:
Squiggle’s top teams at the end of 2019 were Richmond, Geelong, Hawthorn, and Collingwood. The Cats were widely lambasted for their post-bye form last year, but it wasn’t actually that bad – it was just clearly less good than their 11-1 start (at a percentage of 151%).
The Hawks had a strong finish, Collingwood were 4 points shy of a Grand Final, and Richmond were, well, Richmond.
Notably absent from Squiggle’s 2019 Top 4 were West Coast (8th), Brisbane (5th), and, despite their late surge, the Bulldogs (6th). Squiggle was bearish on the Eagles throughout 2019, primarily because of their reliance on high goalkicking accuracy to win matches – something that, despite much effort, no team has ever been able to sustain for long.
Trades, Retirements, Delistings and Returns
Squiggle uses AFL Player Ratings to gauge the likely impact of list changes between 2019 and 2020, including the return of players who missed games late last year. This last factor is often the important one, as most clubs put out weakened teams towards the end of 2019.
On this measure, the most upside is in Fremantle (regaining Lobb, Ryan, Wilson, Hogan*, Hill, Pearce, Colyer, and Cox, while recruiting Acres and Aish), GWS (regaining Coniglio, Whitfield, and Ward, while recruiting Sam Jacobs), followed by Gold Coast, Collingwood, and Carlton.
At the other end of the scale, the only club to have gone backwards is Adelaide (losing Greenwood, Jacobs, Douglas, Betts), while Brisbane (losing Hodge), Richmond, and North Melbourne have relatively little to add to their sides in 2020.
There’s been a lot of talk about Tim Kelly, but despite his stellar numbers, his trade doesn’t single-handedly drag Geelong or West Coast out of the pack (in either direction).
2020 Preseason Form
The preseason usually contains a few hints about regular season form, and at this time of the year, we don’t have much else. The best pre-performers in 2020, after accounting for the quality of their opposition, were Gold Coast, GWS, St Kilda, Essendon, Port Adelaide and Melbourne.
The worst were Geelong, Carlton, Hawthorn, Richmond, Adelaide, and Sydney.
For most of the off-season, Squiggle rated Hawthorn a Top 4 team in 2020. But long-term injuries to Howe, Impey, and Hardwick have sent them tumbling to the lower reaches of the final 8.
Also hampered by long-term injury this year are Fremantle (Hogan, Hamling), Collingwood (Beams, Greenwood, Langdon), and Carlton (Curnow).
The punditry is big on West Coast this year, with the Eagles a popular flag tip and Top 4 lock. Most computer models, however, are much cooler, placing them no higher than 3rd and as low as 11th.
Models have a pretty good record in situations like this, when there’s a divergence of opinion but not because people know something that models don’t. However it shakes out, it’ll be interesting to watch.
Squiggle is high on the Bulldogs, ranking them 2nd, although only by a slim margin. What’s remarkable about the Dogs is how young they are: They’ve been fielding shockingly young teams for two years. Younger teams lose matches pretty reliably, so the ability of the Dogs to make finals in 2019 despite their age profile speaks to their potential upside.
More than any time since 2000 – perhaps since 1993 – we have a very even field entering the new season, so expect surprises! We could have a very volatile ladder, with teams surging and plummeting on the ladder, and a large middle cluster that sits within one or two games of each other.
If you want to do your own football analysis today – write an article, create a chart, build a neat online tool – you can’t legitimately acquire the most basic stats about AFL matches, not even the scores.
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The AFL could and should create an API: a simple online interface that publicly serves up very basic football data such as match scores in a computer-readable format. It could do this simply, cheaply, and without exposing any advanced stats that Champion Data rightly consider to be proprietary and valuable.
Dramatically lower the barrier to entry for anyone with an interest in building something on top of football stats, allowing them to get started with a bunch of basic, legal data.
Signal an interest in and acknowledgment of the growing amateur/semi-pro analytics community and its audience.
Grant the AFL some control over what’s happening. At the moment, it has a fence around every single piece of data, a bunch of tunnels going underneath, and no idea who’s digging them or why. If it added a gate to the fence, many people would use it, because gates are easier.
Today there are excellent free APIs for practically all major world sports, except AFL. There are dozens for cricket and rugby, and hundreds for soccer. In the US, you can’t move for tripping over a baseball, basketball, or football API. But for AFL: nothing.
Regardless of where you land in the wider debate over exactly which stats should or shouldn’t be kept secret, surely no-one is being served when basic match scores are kept under legal lock and key. Fixing this could create a platform for analytics innovation, discussion, and expansion.