This is week three in HPN’s series on new metrics to evaluate the performance of AFL players and teams. Last week we looked at the Player Team Contribution Statistics, and the week before we introduced the Player Rate Statistics.

This week, instead of looking at player based performance measures, we thought we’d look at some team based measures. We’ve chucked up the whole dataset for 2018 here and for past years here. For the past three years we’ve used most of these in our weekly preview pieces when we discuss team strengths and weaknesses, so you might have seen parts before if you are a regular reader.

In the discussions that we normally have at HPN HQ, we usually break them down to two different categories – performance indicators and style indicators. Let’s start with the performance indicators.

Performance indicators

CR: Clearance Ratio

IFR: Inside 50 Ratio

Clearances aren’t always considered to be strictly an indicator of how well a team performs on the field. We consider it the most borderline of the performance measures and don’t incorporate it into the HPN Team Ratings directly.

However, a team that generally wins the clearance battle also wins more inside 50s (and create more opportunities to score), which makes it worthwhile to track.

What may be notable is the sides that are strong at one element but weak at the other – such as the inside-50-strong but clearance-weak Geelong sides of 2011 to 2014, or the movement-weak but clearance-strong Suns of 2011. Ablett was formerly in one side and then left for the other – perhaps the difference for both sides. Generally if you are good at both elements, you will be a good footy team:

And sides weakest at these two elements are very bad at AFL level football:

PPIF: Points per Inside-50

Opp PPIF: Opposition Points per Inside-50

This measure looks at how efficiently a team can score when given the chance, or how miserly they are down back, and feeds directly into the HPN Team Ratings – which we will talk about in more depth next week.

Port Adelaide stand out in this measure, with their 2004 side being a powerhouse at each end of the ground.

This seemingly correlates even more strongly with success than the I50s/Clearances component, since presumably clubs value scoring and stopping power at a premium. Again, at the bottom end of the list is a bunch of bad football sides, but a slightly different list of them.

Also strongly related to these measures, but with slightly different outputs, are:

PPD: Points per Disposal

Opp PPD: Opposition Points per Disposal

GPIF: Goals per Inside 50

SSPIF: Scoring Shots per Inside 50

Opp GPIF: Opposition Goals per Inside 50

Opp SSPIF: Opposition Scoring Shots per Inside 50

These are mostly similar measures of the same broad thing – efficiency ratings relating to conversion of I50s to scoring, measured using goals (which are important) and shots on goal (which accounts for accuracy). SSPIF, since it looks at raw scoring shots, can tell us a bit about the kinds of goalkicking opportunities being taken. Not all scoring shots are the same (look at Figuring Footy for more info), and comparing PPIF and SSPIF can also find out who is (broadly) getting good, high value shots at goal, and converting them, and who is struggling with either shot location or accuracy.

PPD doesn’t quite directly measure scoring potency but can be a measure of how efficiently a team uses the ball around the ground – PPD rank substantially lower than a PPIF rank could mean that a side overuses the ball or prioritises maintaining possession in general play.

Style indicators

Broadly speaking, style indicators are things where teams vary quite a lot in a way that doesn’t really correlate with overall success in the competition. They can be things which indicate particular teams are going well, even while other successful teams don’t rely on or exhibit a strong ratings in the same area.

MIFIF: Marks Inside 50 per Inside 50

Opp MIFIF: Opposition Marks Inside 50 per Inside 50

These measures look at what sides are better at finding marking targets in the forward line, and conversely which sides are better at shutting them down. While it is generally easier to score from set shots, some very effective (and efficient) attacks have made do without being near the top for marks per inside-50. That said, you will notice that the very good Geelong sides of 2007-8 sit at the top of the differential loist while terrible sides like the early expansion outfits sit at the bottom.

This probably suggests that while actively prioritising marks is a preference or personnel driven decision, other good teams still naturally find targets periodically anyway and be at least okay in this regard.

TH: Total hitouts between both teams across a season

HW%: Percentage of the total hitouts won by the team

Some teams use a dominant ruck as a key part of their structure and approach. Some clubs like to create lots of stoppages to sap momentum and generate their own.

Total hitouts in games for each club (i.e. across both sides) is more about the frequency of stoppages caused across the year. Unfortunately, we don’t have it as a “per game” measure yet – but it is still useful at face value.

Hitout counts for games as a whole are most useful is when paired with the hitout win rate, which provides a broader look at which sides play to their ruck strengths. For example, the Perth sides with Sandi and Cox/Naitanui generated lots of stoppages then won plenty of hitouts. Conversely some sides like Gold Coast in 2011 and 2014 had games featuring plenty of stoppages but were smashed in the ruck contests at those stoppages

CPR: Contested Possession Ratio

K:H: Kick to Handball Ratio

Here we are really looking at measures of directness with regards to ball use and ball movement, but each of these is really open to interpretation about what’s going on, and requires some other contextual analsis.

Looking at the Contested Possession Ratio first, this is the share of all a team’s touches which are contested. A high figure here could be suggesting winning the ball “at the coalface” and dominating stoppages, dispossessing the opponent, winning ground balls, and the like. It could also suggest a team struggling for clean ball use and creating situations which require them to win contested ball rather than retain it in an uncontested way. They could be lacking communication and running support players, not hitting targets, and so forth. A look at other stats and whether a team is succeeding or not can help illuminate what’s going on with this ratio.

Similarly, a team kicking a lot more than handballing is probably trying to be direct with the ball or to maintain possession. They could be bombing it long to contests at every opportunity, or they could be using short chip kicks to manouvre up the ground. A team handballing a lot may be struggling for marking targets, it may be trying to move the ball via running, or may be finding itself pressured out of kicking.

Interestingly, both measures have shifted over the last two decades. Teams collectively has the lowest kick to handball ratio (i.e. handballed a lot) and the lowest contested possession ratio (i.e. had a lot of uncontested possessions) in 2009, an era perhaps defined by the wave-running Cats and their imitators. Since then, contested ball has rebounded a bit while kicking frequency has increased.

K:UM: Kick to Uncontested Mark Ratio

Opp K:UM: Opposition Kick to Uncontested Mark Ratio

Kicks versus uncontested marks tells us how frequently a team is kicking the ball and finding a free teammate. This is a proxy both for clean foot skills and a preference against hack kicks out of packs or kicking to contested marking situations.

Unsurprisingly, Hawthorn’s precision chip-kicking sides feature prominently in this list as sides who had an uncontested mark every 2.5 kicks or so; but interestingly so does Paul Roos’ first year in charge of the Swans – a style that perhaps stands in contrast to what they’re famous for doing a couple of years later.

The difference between the rate obtained and the rate conceded could indicate how much a team is preventing their opponents from finding easy targets while doing so themselves, but it may also represent opponents simply trying to kick long and contest the ball at ground level while the chip-kicking side in question does not.

Teams near the bottom for this measure include some pretty good North Melbourne sides, a decent Sydney, and really bad Carlton and Gold Coast sides. It’s probably fair to say this is direct kicking footy and Pagan’s Paddock in its best form. While at its worst it’s sides who can neither hit targets or pressure their opponents.

What about this year?

Good question. Here is the 2018 data (correct to end of round 3), or you can find the most up to date version on this page. We will try to update by Wednesday each week (if possible).

Teams Year GPIF SSPIF MIFPIF Opp GPIF Opp SSPIF Opp MIFPIF TH HW% CPR K:H K:UM Opp K:UM CR IFR PPIF Opp PPIF PPD Opp PPD Adelaide s2018 0.268 0.476 0.202 0.202 0.399 0.215 214 146% 0.380 1.318 2.686 2.995 1.119 1.031 1.815 1.411 0.247 0.200 Brisbane Lions s2018 0.250 0.458 0.174 0.259 0.453 0.271 239 137% 0.410 1.388 2.895 2.302 1.238 0.847 1.708 1.747 0.235 0.264 Carlton s2018 0.207 0.343 0.136 0.281 0.439 0.246 226 75% 0.400 1.426 2.846 2.898 0.958 0.988 1.379 1.842 0.212 0.284 Collingwood s2018 0.230 0.348 0.161 0.247 0.380 0.181 218 151% 0.380 1.182 2.748 2.711 1.000 0.970 1.497 1.614 0.203 0.223 Essendon s2018 0.268 0.450 0.275 0.255 0.497 0.273 196 94% 0.390 1.231 2.819 2.269 0.873 0.903 1.792 1.770 0.249 0.247 Fremantle s2018 0.232 0.415 0.189 0.261 0.431 0.248 210 188% 0.380 1.419 2.431 2.585 1.000 1.072 1.573 1.739 0.226 0.232 Geelong s2018 0.309 0.518 0.281 0.237 0.441 0.194 249 59% 0.360 1.273 2.433 2.947 0.885 0.747 2.065 1.624 0.245 0.267 Gold Coast s2018 0.196 0.356 0.178 0.156 0.353 0.150 232 125% 0.470 2.158 3.505 3.676 1.183 0.942 1.337 1.133 0.202 0.192 Greater Western Sydney s2018 0.270 0.402 0.247 0.227 0.364 0.195 235 63% 0.370 1.377 2.475 2.890 1.105 1.130 1.753 1.500 0.259 0.205 Hawthorn s2018 0.260 0.439 0.220 0.269 0.397 0.212 232 109% 0.410 1.456 2.710 2.584 1.072 1.109 1.740 1.744 0.277 0.253 Melbourne s2018 0.242 0.457 0.226 0.268 0.500 0.196 250 169% 0.430 1.248 3.289 2.859 1.077 1.348 1.667 1.841 0.275 0.234 North Melbourne s2018 0.196 0.392 0.165 0.172 0.351 0.195 234 107% 0.450 1.504 3.868 3.371 0.849 0.908 1.373 1.213 0.212 0.187 Port Adelaide s2018 0.260 0.462 0.237 0.229 0.389 0.132 255 56% 0.380 1.537 2.575 2.822 0.969 1.174 1.763 1.535 0.250 0.203 Richmond s2018 0.251 0.423 0.211 0.284 0.414 0.173 222 68% 0.420 1.391 3.201 2.770 0.908 1.080 1.680 1.833 0.283 0.265 St Kilda s2018 0.182 0.351 0.221 0.241 0.464 0.241 203 48% 0.330 1.265 2.195 2.549 0.796 0.928 1.260 1.669 0.166 0.233 Sydney s2018 0.286 0.435 0.201 0.235 0.392 0.145 254 87% 0.420 1.384 3.051 3.055 1.008 0.928 1.864 1.566 0.253 0.228 West Coast s2018 0.253 0.393 0.230 0.236 0.429 0.261 233 309% 0.400 2.035 2.614 2.508 0.916 1.106 1.657 1.609 0.283 0.258 Western Bulldogs s2018 0.186 0.416 0.329 0.292 0.439 0.339 216 60% 0.320 1.493 2.223 2.375 1.115 0.942 1.348 1.901 0.194 0.289

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