Thursday, January 24, 2019

The Wooden Finger Is Finally Getting Into the AFL Tipping Business

After almost a decade of my AFL Power Rankings, I’m caving in. (Or I’m expanding my horizons, if you want to look at it that way.)

I created my Power Rankings simply so I could get a better indication of each team’s strength than the ladder was showing me. I’ve never been that interested in using it to publically tip the results of matches. (Privately, I’ve done so for several years in various office football tipping competitions – not that I ever expect it to win the competition.)

But seemingly EVERY other ‘rankings system’ does tips. And it is interesting to see them. So yes, starting this year the Wooden Finger is getting into the AFL tipping ‘business’.

How does it work?

To get the predicted net margin of the home team:
To get the expected probability that the home teams wins, I am using a standard deviation of 36 points or six goals for the men’s league, and 18 points or three goals for the women’s league. Maybe it should be a bit more, but since I do all of my HGAs in terms of goals, and for my purposes it doesn’t make much difference, I’m going with those.

AFLW Round 1 predictions

Let’s start with my predictions for Round 1 of the new AFLW season, which is kind of nice in that there are less ranking systems that do AFLW tips.


Two notes of caution though, related to the entry of two new teams into the AFLW competition this year. First, the ranking points for the two new teams – Geelong and North Melbourne – are of course not based on any previous matches, but are sort of based on their premiership odds. Second, the entry of those teams has resulted in a fair amount of player movement, particularly from Collingwood to North Melbourne. It may take a couple of weeks for the ranking points to adjust to the ‘new’ strength of each playing group.

So there you go. My heart still lies in ‘explaining’ performance rather than predicting it. Nevertheless I hope these tips add another interesting and informative dimension to the rankings each week.

Tuesday, January 22, 2019

Which AFL Club Has The Easiest Fixture in 2019?

When the 2019 AFL fixture was released Champion Data tweeted this table, ranking each team’s fixture from hardest to easiest.


Champion Data rated Collingwood as having among the hardest fixtures, and St. Kilda as having among the easiest. So did Rohan Connolly. So did HPN Footy. So did FMI. Spoiler alert: I’m going to as well.

Note the shadings in the table above though. Those shadings indicate how Champion Data ranked the strength of each team – e.g. the ‘strongest’ teams are West Coast, Richmond, Melbourne, and Geelong. Champion Data copped some criticism in the comments under their tweet about those rankings. Oh boy, did some people get annoyed about that.


In particular, there was criticism that Geelong – who finished eighth in 2018 – was ranked in the top group, while runners-up Collingwood were not. Some people were incredulous that a team that was in the last finals spot and then eliminated in the first week could be ranked above another team that made the Grand Final. Yes, it may sound a little strange, but on this one my rankings agree with Champion Data.

Few would dispute that Collingwood had a better finals series than Geelong last year. Over the season as a whole though I’d say that Geelong was better, or at least they were similar. In the home and away season Geelong scored about as many points as Collingwood, and conceded about 150 points less. The Cats won two less matches, but had a much tougher fixture than the Magpies. Collingwood played lower teams Brisbane, Carlton, and Fremantle twice, while Geelong’s only ‘easy double-up’ was Gold Coast. Switch those fixtures around, and the Cats probably finish higher going into the finals.

One point of all this is that, while I don’t know exactly how Champion Data come up with fixture assessment, I expect it is very similar to how I do it. My ‘groupings’ would also be similar, with the exception that I would have Essendon rather than North Melbourne ranked in the top eight after its strong finish to 2018.

The other point is that, while the fixture won’t in itself make you a ‘good’ team, it can sometimes make a fair difference to where you finish on the ladder.

Rating each team’s fixture in 2019

My method for rating the fixtures is to add up the ranking points of all the team’s opponents over the season, while adjusting for home ground advantage. This means that the fixture rating is determined by:
  • which five teams the team plays twice, as well as that a team plays every team at least once except itself; and
  • net home ground advantage over the season.
As Champion Data’s table implies, it is the ‘double-ups’ that matter the most. I rate St. Kilda as having the easiest fixture this year, as it plays Carlton, Fremantle, and Gold Coast twice. On the other hand, I rate Collingwood as having the hardest ‘double-ups’, as it plays Melbourne, Richmond, and West Coast (and Essendon) twice.


Of course, it is likely that some teams will perform very differently in 2019 to 2018. In 2018 teams that played Adelaide and St. Kilda twice had easier fixtures than I initially expected, while teams that played Melbourne and North Melbourne twice had tougher fixtures.

St. Kilda’s ‘80-point’ advantage in the fixture compared with an average team isn’t by itself going to make up their -500 point differential from last year. If the Saints significantly improve though it may well help them with a finals push. It probably helped Richmond to a better finals spot when they improved in 2017, and as mentioned above it probably helped Collingwood last year.

St. Kilda finally wins out in the fixture

I’m in no way a Saints fan, but they were definitely overdue for some ‘love’ from the fixture. They had one of the worst fixtures last year, and the year before that, and in 2015 and 2014 as well.

St. Kilda’s tough luck in the fixture in recent years was well covered in Squiggle’s article ‘How The Fixture Screwed St. Kilda’. In recent years the Saints have had tougher ‘double-ups’ than a team that finished in their position typically would. Also while net home ground advantage is usually fairly minor, it has mattered more in St. Kilda’s case. The Saints have tended to get less home matches against non-Victorian opponents compared with the amount of times they have had to travel across the border.

Again, the fixture by itself didn’t make St. Kilda miss the finals last year, and it likely won’t get them in the finals this year if they don’t otherwise improve. It’s good for them though, after recent years, to have a fixture that is a bit kinder to their chances.

Wednesday, January 16, 2019

Hello Quinn Wheatley


AFL WOMEN’S Power Rankings 2019: Ranking AFLW’s Two Newest Clubs

In a month’s time the AFL Women’s (AFLW) competition will kick off its third season. At the same time I will start up the third season of my weekly AFLW ‘Power Rankings’. These rankings aim to give a more accurate reflection of the ‘current’ strength of each team than the ladder does. They adjust each team’s results for the strength of its opponents, as well as whether they played the match home or away.

For my rankings though the start of the third AFLW season brings with it a new challenge. Two new teams will be joining the competition – the Geelong Cats and the North Melbourne Tasmanian Kangaroos. (Next year will be even more challenging.) How should I rank these two new clubs?

Initial ranking points: look at the premiership odds

I faced this type of situation before when I was trying to work out how to initially rank the eight clubs in the AFLW’s first year. Back then I decided the teams should not be rated as equal, since the ‘consensus’ view – as reflected in bookmakers’ premiership odds – was that they were quite different in their ability.

This also looks to be the case this year for Geelong and North Melbourne. North Melbourne are rated as a very strong side, and have the second-lowest odds to win the premiership, after last year’s premiers the Western Bulldogs. Meanwhile Geelong are rated as a relatively weak side, with the longest odds to win the flag.

Therefore I am going to start North Melbourne off on a relatively high rating of about +5 points, which is what the teams that were initially the highest ranked started on in 2017. Conversely I will start Geelong on a relatively low rating of about -7 points, which is the same as the lowest ranked team at the beginning of 2017. (There is a bit more behind my decision, but I don’t think the full method is either interesting or ‘scientific’ enough to go into all of the specifics here.) All of the teams’ ranking points are also adjusted slightly, to keep the average number of ranking points across teams at zero.

This will start North Melbourne off in fourth spot on the rankings, and Geelong in second last. The rankings update pretty quickly though because of the small number of matches, with 25 per cent of a team’s ranking determined by its most recent match alone. Hence a much better indication of the strength of these teams should emerge within a couple of rounds of the new season, as it did in 2017.

Home ground advantage: think GWS

As there is only a small history of AFLW matches to draw from, I base my adjustments for home ground advantage (HGA) on the adjustments I use for the men’s league (see table below). While I haven’t done a big review of my men’s league HGA adjustments since those rankings began in 2010, they are still based on far more data than we have for the women’s league to date.


In the men’s league I give Geelong the same HGAs as NSW teams against Victorian clubs whenever the Cats are playing in Geelong. Therefore, my HGA for the Cats in Geelong will be based on that of GWS. Following this rule and using my HGAs from last year would give Geelong an HGA of four points when playing against Victorian or NSW teams in Geelong, and eight points when playing against other clubs.

What to do for North Melbourne, which will play its home games in Tasmania? In the men’s league my HGAs for Hawthorn and North Melbourne when playing in Tasmania are smaller than their HGAs when playing in Victoria, as they play less often there. That doesn’t seem right for a genuine ‘Tassie Kangaroos’ team though. Alternatively, I could give the Roos the same HGAs as the other ‘Melbourne clubs’ – that is HGAs against non-Victorian teams at home, but no HGAs against other Victorian teams.

However I’m going to take the view that, since Tasmania is their permanent ‘home turf’, North’s HGA against other Victorian teams in Tasmania should at least be as much as the Cats in Geelong. After all, Victorian teams have to travel further to Tassie than they do to Geelong. On the other hand, I don’t think I should make them any higher than when Victorian teams travel to Sydney. Let’s make North Melbourne’s HGAs the same as Geelong’s and GWS’ then.

Note though that in the men’s league I assume Geelong is not disadvantaged against Victorian teams when they play at other Victorian venues. In AFL, Geelong plays a fair amount of games at both the MCG and Docklands. In AFLW though that looks like it will not apply. Therefore I will also add a disadvantage for the Cats (and Roos) when they play elsewhere in Victoria.

One other thing – in general, I’m not going to use the same HGAs as I have the first two years. When I first came up with my women’s league HGA adjustments I didn’t know what the volume of scoring would be. Given the scoring we have seen so far, and since I am already making some adjustments to last year’s rankings because of the new clubs, I am going to take this opportunity to reduce them slightly.

In matches where GWS, Geelong, and North Melbourne play the ‘Melbourne clubs’ I’m going to reduce the HGA from four points to three points. In all other matches involving clubs from different cities I’ll reduce the HGA from eight points to six points.

These new adjustments do not make much difference to the ranking points, but seem more in line with the scoring we’ve seen over the first two AFLW seasons (indeed, they may still be a touch high). The table below lists the new HGAs, and compares them to the men’s league.



Revised rankings: Magpies now on top, but they are not the same team in 2019

As mentioned above, these revisions make little difference to the rankings (see table below). Collingwood regain the top spot it lost to the Brisbane Lions after the Grand Final. The Lions’ showing in the GF against the Dogs in Melbourne is now considered slightly less impressive with the reduced HGA.



While the Pies’ top ranking may seem peculiar given they only finished mid-table in 2018, it is because they finished the year off really well. They had strong wins against Melbourne and Adelaide, an away win against Brisbane, and a close loss against the Bulldogs. Given that Collingwood is in the weaker half in the premiership odds, maybe one should be thinking about the Magpies as a ‘good bet’ then?

Not so fast … what the premiership odds likely reflect that the rankings do not is that Collingwood lost some top players to North Melbourne, including Jess Duffin, Jasmine Garner, Moana Hope, and Emma King. The Magpies have also lost AFLW Rising Star winner Chloe  Molloy for the season due to injury. Top-end talent matters more in AFLW than the men’s league, and the forward prowess that we saw from Collingwood in the second half of 2018 is likely to be significantly curtailed this season.

Indeed you could make an argument for a more significant shake-up of the rankings given the off-season player movements. As I said above though, if these player movements do result in large changes in performance the system will correct quite quickly. For the most part the revised rankings are not too far off what ‘the market’ is saying about how teams are expected to perform this season, so I’ll leave the tinkering there.

Monday, December 10, 2018

AFL Statistics Series #2: Scoring a Behind – ‘Scoreboard Impact’ or a ‘Missed Opportunity’?

One point for ‘trying’

What is the ‘value’ of a behind in Australian rules? On the scoreboard it is of course one point scored for your team. That’s less than the six points for scoring a goal, but better than no points and potentially the difference between winning and losing.

A behind scored by an individual player is also recorded against the name of that player, as part of their contribution to the team’s score. In fantasy football leagues a behind makes a minor but positive contribution towards a player’s fantasy points total. So while it isn’t as good as a goal, it seems like something at least.

Is it a positive though? Every supporter has known the agony of his or her team losing a match through inaccuracy in kicking for goal. It’s even more agonizing when the players are missing shots for goal that are considered relatively easy.

Shots on goal are hard to come by, and six behinds are needed to obtain as many points as just one goal. Furthermore scoring a behind gives the ball back to the opposition for a kick into play, in contrast to the roughly ‘fifty-fifty’ chance a team has of getting the ball back again from the centre bounce that follows a goal.

With that in mind should we really consider kicking a behind favourably? Should a behind be seen more as ‘impacting the scoreboard’ or a ‘missed opportunity’?

How existing player rating systems credit behinds

As I said in my first post in this series part of thinking here is perhaps to arrive at a new ‘player rating’ system. Both the Australian Football League Fantasy and SuperCoach (Champion Data) ratings give a player a point for scoring a behind. HPN’s PAV system also gives positive credit to a player for any point he scores, though as with the other systems a behind will have only a minor effect on a player’s rating.

In the AFL Player Ratings system however a player can lose rating points for missing a shot at goal. Rating points in this system essentially depend upon how a player’s action affects a team’s expected score. For example, a player taking a shot from 15 metres out would in most cases be expected to score a goal, so scoring a behind instead means the outcome was a lot worse than expected. The ‘penalty’ for missing is less if the player was taking a more difficult shot – say, from 60 metres out.


Kicking a behind could then lead to a net negative effect on the player’s rating. In the extreme if the player who missed the shot on goal gets no credit at all for creating the shot then the player has only hurt his team. On this view, it would be a similar situation to a player undoing the good work of his teammates by kicking the ball to the opposition, and it is well-known that a player loses points for this under the SuperCoach rating system at least.

Reading through the explanation of the AFL Player Ratings system for the first time did alter my view of what a behind was worth. Or maybe it just returned me to a more intuitive state of being a fan in the stands watching a player on my team miss a shot on goal – shaking my head and cursing as he ‘blew’ all the hard work of my team getting the ball up the field for a scoring shot only to get one point out of it.

Attributing a team’s points to player accuracy

Players can help their team score by contributing to the creation of scoring shots, and by taking scoring shots. Crediting players for the former is going to take a bit of work. I think though it’s relatively easy to give credit for the latter.

OK, a player is taking a shot for goal – what is the change in the team’s expected points from him converting or missing the shot? Under the AFL Player Ratings system this depends upon the expected points for the position on the ground that the player takes the shot from. However I only have public data and I don’t know where the shot was taken from. Therefore, let’s define the extra points from scoring shots as following:

Extra points created by player from taking scoring shots = Points scored by player – (League average points per scoring shot, excluding rushed behinds * Scoring shots by player)

In 2018 the league average points per scoring shot, excluding rushed behinds, was 3.85 points. Therefore, if a team creates a scoring shot and I don’t know where on the field the scoring shot was created from, I’m going to assume the value of creating one scoring shot is 3.85 points. These points can be attributed amongst the players who contributed to creating the shot, including perhaps to the player who took the shot itself.

But what is the value of simply taking the shot? That is, let’s ignore the player’s role in creating the shot, the metres gain from kicking to goal, and what happens after the score is kicked. Under the system above each successful shot by a player on goal adds 2.15 points, with the other 3.85 points going to the players that created the shot. On the other hand, if a player misses a shot he can be said to have subtracted 2.85 points from his team’s total.

This simple system does ignore shots at goal that go out on bounds on full, but I cannot get these from public statistics. Probably the bigger weakness though is it does not account for the difficulty of the player’s shots on goal, as the AFL Player Ratings system does. For example, Lance Franklin converted shots on goal in 2018 at about the league average rate. Franklin though is well known for converting longer and more difficult shots than your average forward. (One might also argue that the difficulty of shots varies at a team level – i.e. some teams create better shots than others.)

If we just use this simple system though, which players created the most value last season from scoring shots converted, and which players lost the most value? This will depend upon the accuracy of the player’s shots and his volume of scoring shots. Hence, the top players in terms of extra points added from converting scoring shots in 2018 included leading goalkickers such as Ben Brown, Tom McDonald, Jack Riewoldt, Luke Breust, and Tom Hawkins (see table below).


The ‘worst’ goalkickers do not ‘destroy’ quite as much value as the best goalkickers create (see table below). According to this system Jarryd Lyons lost about 28 points for his team in 2018 through his inaccuracy, less than half of the 63 points Ben Brown created.


The line from ‘good’ to ‘bad’ converter is relatively thin. There is little overlap among the ‘best’ and ‘worst’ converters if the same calculations are done for 2017 (though Ben Brown topped the list in both years), with Christian Petracca even flipping between the two.

On a per game basis the points gained or lost from simply converting scoring shots may seem relatively small. Even Ben Brown is only credited for less than 3 extra points per game from his accuracy. However in a league where a team scores on average 80-90 points per game – meaning that each of a team’s 22 players contributes on average about four points per game – goal accuracy can be quite significant.

It is even more significant in evaluating a player’s contribution to an individual game. A player scoring four or five behinds without scoring a goal could very well obliterate every positive contribution he has made for the game. Few ‘possession chains’ a team or a player is involved in result in scoring shots; ‘wasting’ those that do is significant.

VERDICT: Creating a scoring shot is valuable. Scoring one point rather than six points with that shot is generally a MISSED OPPORTUNITY.

Wednesday, October 31, 2018

AFL Statistics Series #1: Which Statistics Matter The Most (Apart From The Scoreboard)?

Introduction

This is a first in a series of posts that I’ll do about statistics in the Australian Football League. The posts will be about which AFL statistics I think matter – that is, what I think they tell us about how AFL teams and players go about scoring and stopping the other team from scoring.

Yes, there is a lot of writing out there already about AFL that uses statistics and numbers, and a lot of good writing. This is just how all of those statistics make sense to me. I hope if you’re reading this you find something in here that’s useful for you too.

A lot of the thoughts I’m going to talk about here came about as a result of me trying to devise a method of rating AFL players, without having access to the detailed data that Champion Data use to devise their ratings. We may still get to that in the end. It turns out though that to work out how each player contributes to winning a game you need to first think about how teams go about winning them.

Points differential: the most important statistic of all (duh…)

In their AFL Prospectus 2018, Champion Data made this obvious but important point:

“… we are asked [:] What’s the most important stat? As respectfully as possible we answer with POINTS FOR. It’s the one stat that guarantees a win … We go on to explain it’s more about how you get to that point.”

Of course points for compared with points against is important. There is a position here though that may not be quite so obvious. Some would argue that only the win or the loss matter, and not the margin of victory or defeat. Margins though tend to be a better predictor of future performance. Close wins may bring exhilaration and relief, but in general a team should take more comfort out of a comfortable win than a close one.

Metres gained matters

Metres gained gets some bad press, perhaps because it sounds like ‘a stat too far’. An article on The Roar last year even went so far as to call the statistic ‘irrelevant’. The main argument was that it doesn’t take into account the outcome of the possession – a long kick to the opposition would be credited with many more metres than an effective handball backwards to a teammate. “While it is impressive to see a player average over 300 metres gained a match,” the author says “the statistic is mostly empty in its meaning.”

The article makes some good points, but I disagree that metres gained is irrelevant. Indeed to me, there is hardly anything more fundamental to performing well at Australian rules football than gaining metres. When you’re watching your team, apart from when they’re actually in the action of kicking goals, what do you most want them to do? You want them to GET THE BALL CLOSER TO THEIR GOALPOSTS and GET THE BALL FAR AWAY FROM THE OTHER TEAM’S GOALPOSTS!

Now a critic of metres gained may point out that it isn’t so great if you kick 50 metres straight to the opposition. That’s true – ‘effective’ metres would probably be a better measure. We’ll get to more about keeping possession later.

Kicking the ball 50 metres to the opposition though isn’t necessarily a horrible outcome, despite what I will say later on about the value of turnovers. Now if the opposition run the ball down the field and score a goal off your turnover that is obviously a bad result. That worst-case scenario is relatively uncommon though – only about 10 per cent of possession ‘chains’ end in goals, and on average those ‘chains’ only last for about three disposals and gain about 45-50 metres. In other words, even if you kick 50 metres to the opposition it’s unlikely the other team will punish you by running the ball down the field and kicking a goal (obviously depending on where the ball is, and how badly you butcher the kick). More likely is that the ball may come back to your team within a few possessions, and back around where you started.

What about an effective kick across the ground that gains no metres but sets the team up for a shot at goal? Isn’t it true that metres gained isn’t very good at accounting for that? That cross-ground kick however is only valuable if the TEAM gains metres on a subsequent possession. If the opposition stops the ball before it goes any further then it’s just a kick across the ground that didn’t help much. The objection to metres gained here is more about crediting the total metres gained by the team to the individuals in that team – how much did that cross-ground kick help the team to score? – not about the value of the total metres gained by the team itself.

Metres gained matter. In each of the four AFL seasons since the statistic was made public in 2015 no other relatively common used statistic – except statistics directly related to scoring, e.g. score involvements and goal assists – has been more positively correlated with points differential (see table below).



Good teams like West Coast and Richmond had less disposals last year than their opponents, and lower teams like the Bulldogs and St. Kilda had more. Richmond were smashed in hit outs and clearances, and West Coast were behind on tackles. The higher teams though almost always had positive metres gained differentials over the season (see table below). It is one of the few relatively common statistics that you can reliably count on good teams being ahead in.  

[EDIT: Metres gained differential in a single match should, by definition, ALMOST reflect goal differential. Nevertheless, metres gained are still highly correlated with scoring.]    

Once you view gaining territory as an important indicator of a football team’s ability to score goals, the importance of some other AFL statistics falls into place. Inside 50 entries – a statistic that has been noted by others to be highly correlated with winning – indicates metres gained by measuring the number of times a team gets the ball past a particular point on the ground, one it has to pass over in order to score goals. An inside 40 or inside 30 measure would also indicate this.
(Rebound 50s indicate metres gained as well, but since they indicate metres gained in a team’s defensive part of the ground they are negatively correlated with winning. Put inside 50s and rebound 50s together and you get some of the way to a decent proxy for metres gained.) 
It also indicates why the number of kicks that a team or player records is generally important for winning (other than, of course, it is the only way to score goals), and why one kick is generally more important than one handball – more kicks often leads to more territory gained. Conversely though it also explains why just amassing kicks sometimes does not lead to success; for example, two short kicks of 20 metres get a team no closer to goal than one long kick of 40 metres.
All of this is not to say however that an individual player’s contribution to their team’s performance should be primarily measured by metres gained. The AFL leaders in metres gained per game last year were Jayden Short, James Sicily, and Nathan Wilson. Nobody thinks that these are the very best players in the league. (Maybe they should … but probably not.) That is because what these players don’t do as much as some other players is win their teams the ball in the first place.
Turnovers are the main source of scoring shots
In Australian rules football, the significance of individual possessions in helping a team score can sometimes seem hard to work out. The ball can pass back and forth between teams several times before anyone has a legitimate chance to score. Teams can also have very different styles when in possession of the ball, with some teams preferring a ‘high-possession, low-risk’ game, and others preferring to be more direct.
Let’s try and simplify it then. Obviously if you have possession of the ball you are the only team that can score until your ‘chain’ of possessions is broken. We’ll call any unbroken sequence of possessions by a team – whether of one possession or ten – a ‘possession chain’.
Let’s say that a possession chain for a team can start in one of three ways:
  • the team gets a ‘clearance’ – i.e. it clears the ball from a ball-up, either from a stoppage or a centre bounce at the start of a quarter or after a goal
  • the opposition turns the ball over; or
  • the opposition scores a behind, giving the team a kick into play.
Let’s also say that a possession chain ends in one of three ways:

  • the team scores a goal or behind – a successful (or at least partially successful) possession chain;
  • the team turns the ball over; or
  • the possession chain is ‘stopped’, due to a ball-up, or because the quarter is over, or because the scoreboard is on fire – basically any unsuccessful possession chain that does not result in the ball going directly back to the opposition.
(That may not be completely technically correct according to how Champion Data defines these terms, but I think it’s close enough for the purpose of my main point here.)

Therefore, for a team we will say that:

Possession chains started = Possession chains ended

Clearances + Opposition turnovers + Opposition behinds = Scoring Shots + Turnovers + Stopped Possession Chains

Or, more importantly:

Scoring Shots = Clearances + Opposition turnovers + Opposition behinds - Turnovers - Stopped Possession Chains

For example in 2018 premiers West Coast averaged 24.7 scoring shots per game. By the definition above they started 117.9 possession chains per game, from 36.6 clearances, 71.6 opposition turnovers, and 9.7 opposition behinds. Of the 93.2 unsuccessful possession chains they had per game, 67.7 of them were turnovers, and 25.4 were stopped possession chains.

The bottom team in 2018 Carlton averaged 17.9 scoring shots per game. By the definition above they started 109.7 possession chains per game, from 35.0 clearances, 62.3 opposition turnovers, and 12.4 opposition behinds. Of the 91.9 unsuccessful possession chains they had per game, 67.3 of them were turnovers, and 24.6 were stopped possession chains.

What’s the main difference in the possession chains of those two teams? Clearances, behinds, and stopped possession chains are all similar. The main difference is West Coast started more chains through opposition turnovers – about the same difference as the difference in scoring shots.

Returning to our scoring shot formula above, let’s now look at scoring shot differentials, or scoring shots for the team less opposition scoring shots. With a bit of mathematics we can show that:

Scoring shot differential = Clearance differential – 2 * Turnover differential – Behinds differential – Stopped possession chains differential

Maybe it’s just me, but I found this really interesting when I worked it out. Turnovers are not only more common than those other components they count for twice as much in this equation. When there is a stoppage one team’s possession chain ends, but then each team has about a 50 per cent chance of starting the next possession chain. When the ball is turned over, one team’s possession chain ends and the other team’s begins.

The importance of turnover differential can be seen when we compare how teams got their scoring shots in 2018 (see table below). Minor premiers Richmond were last by some margin in clearance differential, but they were way ahead in terms of (inverse) turnover differential. West Coast and Melbourne also rated highly in either causing opposition turnovers, or not turning the ball over themselves. Unsurprisingly, bottom teams Carlton and Gold Coast rated poorly in terms of turnover differential.

Turnover differential does not explain everything, as there are other ways to start possession chains. 2018 runners-up Collingwood gave up a lot of turnovers, but they were good at getting clearances. 2016 premiers the Western Bulldogs were fantastic at winning clearances. It is just that it is less likely to get a high differential through clearances or stoppages rather than turnovers as there are less of them. Hence, clearance differential is less correlated with winning than turnover differential is.
In terms of valuing players this suggests that not only are players with high clearance numbers such as Tom Mitchell and Nat Fyfe important for starting possession chains, but so are defenders who get a high number of intercepts such as Alex Rance and Jeremy McGovern. Though the question then is how important is the individual player who records the clearance or intercept to the team getting possession? How much of the credit should go to the ruckman getting the hit out, or the structure of the team defence?
Given how fundamental I said metres gained were how then does turnover differential relate back to that measure? If the main aim of Australian rules is to score by getting the ball close enough to your goal to do so, then the way to progress the ball down the ground is to get possession of the ball and keepisng it. The best possessions are those that help the team to gain a high number of metres with a relatively low risk of giving the ball back to the opposition, or of the ball being ‘stopped’. On defence, your aim is to stop the other team doing this.
Sounds simple, right? Well, it’s easier said than done. Also, what may be complex about Australian rules is the many ways you can go about doing this.
Goal accuracy: converting those shots at goal
Another statistic that I think is important is goal accuracy, though not quite in the same way as the other main statistics I have covered above.
Goal accuracy – the percentage of shots a team has on goal that are goals (scoring shots, if kicks out of bounds are not available) – is somewhat important to performance over an entire season. Last season, finals teams Sydney, Hawthorn, Collingwood and West Coast were good at it, but Richmond and GWS were not. In 2017 the leaders in goal accuracy were non-finalists Melbourne and the Brisbane Lions. Scoring shot creation is generally more important to performance over a season than scoring shot conversion is, with teams being reasonably close over a season in terms of the rates at which they convert.
I would say where it matters more is changing the outcome of a single game, which is even more important if that game is a final. In a single game there is more variability in scoring shot conversion than over a season, and the results can swing the match significantly. We see this in some of the comparisons between final scores and ‘expected scores’ for a game.
To state the obvious, six behinds are needed to gain as many points as a single goal. Given that the difference between premiers West Coast and last-placed Carlton was only about seven scoring shots per game you want to convert those chances when you get them. Or given that goal accuracy tends to even out over the season, you want to convert those chances when they are most important. (West Coast almost didn’t in last year’s Grand Final, until Dom Sheed did.)
Conclusion
In Australian rules football the ways for teams to score are:
  •  get possession of the ball, and keep it;
  • gain metres while you have the ball in order to get a shot at scoring; and
  • get as many of those shots at scoring through the goal posts as possible.

For defence the ways to stop the other team from scoring are:
  • try to get back possession of the ball, or otherwise get a stoppage;
  • if you haven’t got the ball back yet stop the other team from getting the ball down the field far enough to have a shot at scoring; and
  •  if the other team does get a shot a scoring, try and limit the chance that it is a goal.
This is essentially how I am going to talk about the value of AFL statistics in this series. I’ll mainly evaluate teams and players by how good they are at doing these things. I also plan to talk about how the evolving nature of statistics has given us a better picture over time of the effectiveness of teams and players. Some conclusions will be obvious, but some may be less so. In the end, we may yet even get to that 'player rating' system.