Welcome to HPNFooty.com!

After two years on the catchy URL “hurlingpeoplenow.wordpress.com” we decided that it was time that we got a proper web domain and a better site.

Welcome to HPNFooty.com!

Along with all our previous content, the new site has a whole lot of interactive stuff to explore. The top navigation bar has links to our most popular/anticipated work – including a list of PAVs going back to 1988. Also up there is our new HPN Draft Pick Value Chart (as featured above) based on PAVs, and an AFL Trade Calculator – in order that you can work out whether your proposed hypothetical trade is “fair” or not, according to PAV and PAPLEY!

What’s PAPLEY? Well, PAPLEY is version one of our new career player projection model, developed over the last year. A brief description is at that page, and it also feeds the information in our Trade Calculator.

We think the new site is more responsive, has more cool information and looks better than the last one. This will be the last substantive post on this site – all new content will primarily go to the new site.

We will be continuing to make updates to the site across the summer as well – this is just the starting point.

Until then, have a look around and enjoy!

Cody and Sean.

Kicking six goals in a final is extremely hard to do, but for Stevie J it was basically worthless

Finals in the last ten years aren’t often decided by big bags of goals, instead they are typified by total team performances, grinding their opponents into submission. Indeed, since 2008 six or more goals have been kicked in a final just eight times, and the list of names is an enviable one:

There is one major surprise in this list of former All Australians, and it is Scott Stevens, whose next highest goal haul in a single game is 3 – a lightning in a bottle moment. The rest read as a list of the best non-Riewoldt forwards of the last ten years, the cream of the crop.

However, one of these eight performances isn’t like the others, and it is the one that happened most recently.

Last weekend, GWS pummelled West Coast. You could try to dance around the issue, and put some flowery prose in there, but it was a furious demolition of one football team by another. From almost the first bounce, it felt like the two sides were playing a slightly different sport. By halftime, the Giants led by 35 points.

HPN asked friend of the blog Matt Cowgill, from ESPN and The Arc, to use his in-game probability method to work out GWS’s chance of victory at half time.

Cowgill’s response – 96.5%. West Coast were all but out of the game at half time. Just two times in AFL Finals history had a side come back from a deficit of more than 40 points at half time – and on the performance of both sides, this wasn’t going to be a similar comeback.

What is perhaps more relevant to this story is that, until half time, Stevie J had just three disposals and zero goals.

When the game was more or less decided, the impact of Johnson had been minimal at best. His critical role in the first half was to lead into space, and he almost acted as a decoy for the West Coast defence at time. However, his actual tangible impact on the game was negligible.

After half time, the Giants continued on their curb-stomping ways, with one addition – Stevie J started kicking goals. Six of them. Johnson’s first goal for the game actually came after the Giants had stretched the margin to 42 points, further pushing the game out of reach. He then added another four for the quarter, before snagging one in the last. Some goals were incredibly impressive, others (like the one that Coniglio handballed to Johnson after a inside 50 mark) were of the cheaper variety. But kicking six goals in any game of football, at any level, is an extremely impressive feat – let alone in an AFL Final. We couldn’t do it at any level, and you probably can’t either.

Of the other seven 6+ goal hauls in finals in the last decade, all featured scoring involvement earlier in the game, and several efforts proved to be the difference between the two sides. For example, Franklin’s 2008 effort featured five first half goals, including the goal that put the Hawks in the lead for good in the first quarter.

Even poor Scott Stevens’s goals came at a time that the game was under intense pressure – his second goal put the Crows in the lead, his third and fourth stretched that margin despite their eventual loss.

All goals have the same value on the scoreboard. Every goal is worth six points, every behind worth one. But not every goal has the same impact on the end result of a game, which may be more important than the mere score value of a goal.

Stevie J had six goals, but they were worth almost nothing.

Finals Preview

Adelaide v Geelong

On paper, this one should be easy. The best team should beat the best player, no matter how good and versatile that player is. Adelaide, despite some slips and falls through the year, are a very good football team full of very good football players, from player 1 through 22. Geelong – not so much. We have shown in past weeks that Geelong (and the Tigers) perhaps have some of the best top end talent in the league, but seriously lack for depth at the bottom of their match day squads.


However, as we have mentioned in previous weeks, some of the Crows’ losses this year have been caused by smaller, faster attacks, such as against Melbourne in round 9. Tall forwards accounted for just five of the Demons’ 17 goals on the day, with the two contributing talls (Pedersen and McDonald) playing a rotating ruck-forward role throughout the game.

The two sides split their games this year, with Geelong winning by 22 in round 11 before Adelaide walked away with a 22 point win in round 18. In their win in round 11, the Cats were led by nine goals by their smaller brigade, including three each from Dangerfield and Menzel. In the Crows win, the smaller forwards kicked just three. The Crows defensive setup leans towards the taller side, despite their ability to launch slingshot attacks from halfback (often created by the now-missing Brodie Smith). If the Cats can afford to put Dangerfield up forward for extended stretches, or have the mercurial Menzel make an early impact on the game, they might be able to stretch the Crows defence to breaking point.

Gee v Adel PAVPG.JPG

For the Crows, the equation is much more simple – just play like they have all year. In this situation the onus is often on the notional underdog to spring a surprise, either tactically or from a personnel point of view. The reason for this is extremely obvious; because if both teams play to ordinary expectations, the favourite will probably win.

Adel v Gee PAVPG.JPG

The HPN model predicts a 12 point win to the Crows – not massive, but still a fair margin nonetheless.

Richmond v GWS

This one should be close. On paper the two teams are about as strong as each other, and the two games between them were low scoring affairs where the Tigers probably should have won both instead of just the one. Season average strength ratings suggest a 79-77 Richmond victory, which is interestingly close to the 78-75 result in the Shai Bolton Touched Goal match.


Defence has been Richmond’s strength, as well as GWS’ to a lesser degree. Richmond’s midfield wins a higher share of inside-50s, and GWS have been far more efficient inside forward 50.

It’s that interplay of the midfield and the forward-50 scoring efficiency which will be quite telling. Both teams have been criticised for the opposite extremes of their forwardline set up – Richmond for their small setup with only one true big forward, GWS for being too top-heavy but now forced to play smaller up forward.

In terms of team strength, the Tigers are still primed with no serious omissions.


The absence of Cameron, Mumford and Devon Smith should all be expected to hurt GWS again, but last week they more than coped without those three.


If we are to believe that partisan crowds are a factor in club performance, then this is the time for it to be a factor. The extremely loud, large and one-sided crowd on Saturday should be a fun test-case of home crowd influence. The Giants have mostly played off-Broadway in their limited tenure, their biggest crowd about 60k vs Sydney last year (which they won). Their next four biggest audiences have been games at Adelaide Oval ranging from 44k to 52k (which they’ve lost). Their 11 games at the MCG have pulled an average of 27k and a peak of 43k. If a team was ever to get overawed, this is the time.

HPN’s AFL Semi Final Previews – Can the Cats or Eagles spring an upset?

Geelong v Sydney

Although they are the away side, and finished the Home and Away season a few rungs lower on the ladder, practically everyone outside of the 3220 postcode has the Swans as raging favourites this week. The HPN Team Ratings agrees that the Swans should be favourites, but to a lesser degree than some.


Geelong actually finished the year ahead in two of the three HPN Team Ratings component areas, barely nudging the Swans with respect to offensive efficiency and the field territory battle. However, the Swans’ dominant defence seems to be the difference between the two sides. This is perhaps intensified further by Geelong’s inability to score against a slightly lesser Richmond defence this week.

The HPN prediction model has the Swans likely to win by about seven points, which is a lot tighter than the betting agencies, but right in line with The Arc’s prediction for the week.

Whilst the model doesn’t account for individual players just yet, the inclusion of Daniel Menzel this week should be able to provide another much needed avenue to goal this week, or at least as a decoy to stretch the Sydney defence. Also included was Darcy Lang, just a day before being allegedly told that he was not required for next season at the Cattery. Whether this serves as motivation or demotivation is anyone’s guess.

Gee v Syd PAVPG

One player towers over the rest there, and it is hard to see a Geelong victory without a significant contribution both in the middle and up forward by Patrick Dangerfield. The bottom of Geelong’s 22 is as poor as any other side still playing, so the top end of the list will have to pick up a lot of slack.


Sydney go in unchanged from last week, with the late change of Cunningham for Melican being kept for this week. Melican is a little unlucky, as he has performed excellently for a first year KPD – however with Sydney changing their structure a little he is the odd man out.

If selections are anything to go by, it appears (at least on paper) that the Swans have selected a stronger side, and a side that has more significant contributors at the back of the 22. On paper, the Swans should have a marginally better chance of winning that the formula predicts as a result.

GWS v West Coast

While the HPN model predicted a Port Adelaide win last week, we wrote in depth about how the absence of several key defensive contributors for Port may open the door for a West Coast upset. After 10 minutes of glorious bonus football, that came to pass, and West Coast barely edged out the Power in the sole shock (and close game) of the round.

GWSvWC.JPGLike the Swans-Cats game above, the underdog here (in this case the Eagles) has minor edges in two statistical categories (offensive and defensive efficiency), whilst significantly trailing in the battle in the middle. For the Eagles, the equation is similar to last week – they have to minimise the damage in the middle, or exploit missing opposition players, to have a real shot.

Luckily for the Eagles, the Giants are going in somewhat undermanned after a couple of untimely injuries last week.


The Giants are missing Jeremy Cameron (their second most effective forward according to OffPAV per game) and Shane Mumford, whose ruck spot will largely be covered by “ruck of the future” Rory Lobb. Structurally, this means that the Giants will go in with at least one – if not two – less true KPFs, depending on how you view Harry Himmelberg. Tomlinson and Patton should be tapped to spell Lobb at times, however the West Coast dual rucks might tire Lobb out more than a traditional solo ruck. Dawson Simpson has also had a very solid year in the NEAFL, and was more than serviceable in his two games at AFL level this year.

Lobb’s use in the ruck also deprives the Giants of their fifth most effective forward, with the seventh (Devon Smith) also missing due to injury. How the Giants will juggle this is anyone’s guess – perhaps similarly to the Essendon game earlier this year which saw significant contributions by Greene and Kelly. What is likely, however, is that their attack will be somewhat muted compared to what we have seen in recent years.

It opens the door, at least a crack, for the Eagles to capitalise on a slightly weaker opponent again.


On paper the Eagles have a slightly more even side with respect to Total PAVs per game for the bottom end of their list. Like last week, they are more or less selecting their strongest side (position adjusted), and one with strong contributors across all parts of the ground.

Like last week, they will have to establish alternative paths to goal to avoid the Giants double and triple teaming Kennedy early. The Eagles will have to be able to attack off the half back line, where they should be able to pick up some loose ball due to the Giants relative lack of tall targets.

The HPN model sees the Giants sneaking through by six points, but this doesn’t take into account the long-ish Giants injury list. If we had to tip a potential upset this week, it would be this game.

HPN Finals Preview – Port Adelaide v West Coast

Whilst the overall HPN Team Ratings may paint this game as a bit of a mismatch, the component scores are somewhat more favourable to the Eagles than first meets the eye and we must remember our prior analysis of the strange flat-tracky distribution of Port Adelaide’s apparent strength. As we said back then:

“Port Adelaide are the best side in the competition against weak opponents and they’re about as good as North Melbourne against the good teams.”

That’s based on quality of output as measured by our strength ratings, not just a tally of wins and losses. The question is then partly whether Port Adelaide can overcome their two-faced regular season output and manifest a performance worthy of their ladder position.


The Eagles had the 6th most effective attack this year according to the HPN Team Ratings, which will be matched up against the 3rd rated defence of the Power. This, however, doesn’t consider the significant outs to the Port Adelaide defensive unit.

Part of Port’s inconsistency comes down to the service their forwards receive from the midfield at times – plentiful but sometimes not to the right target or targets. Port will have to perform to the best of their abilities at this end of the ground to put up enough points to win. They certainly struggled as a collective against West Coast in the corresponding match at Adelaide Oval earlier in the year. Ryan Buckland recounted the tactics that led to the Eagles blunting Port’s attack despite 29 less inside-50s, the Eagles building a winning score with effective counterpunches. This is what an ineffective Port Adelaide attack and effective West Coast defence can look like.

Despite recruiting Sam Mitchell during the offseason, the Eagles went backwards this year relative to the league average, according to the HPN Team Ratings. They finished the year with the 14th best midfield score. By contrast, Port dominated the midfield territory battle all year, ending the year in 1st. If both sides performed to their expectations across the season, and there was the AFL game average 105 inside-50s across the match, Port would be expected to win 59 of those inside-50s to the Eagles’ 46.

If we ignore defence, and both sides score per inside-50 at their season long rates, then Port would rack up 97 points to the Eagles’ 81. When defence is factored in, we’d expect both sides to score around 7 points less – which doesn’t significantly help the Eagles’ cause. However, in round 7 on the same ground, the tally was 69 to 38, and Port still lost.

For West Coast to spring the repeat upset, they would either have to improve their forward or (more likely) defensive effectiveness to the levels they hit in round 7, or try to limit the expected Port Adelaide preponderance of inside-50s. If the Eagles limit the damage in the middle, they’re every chance of winning, especially with their forward potency and the vulnerability of Port Adelaide’s current defensive stocks.

Port Adelaide team selection


As alluded to above, those big bars of red to the right of the chart are the big concern for the Power this week – with three of their top six contributors for DefPAV per game (min. five games) missing this week. Jackson Trengove, mooted by many to be picked to cover that gap, hasn’t really played in a full time defensive role since 2015, as Port have attempted to turn him into an around the ground tall utility. A lot will be riding on Dougal Howard, Dan Houston and Tom Clurey – a group of relatively inexperienced players with massive roles to play this week.

Perhaps the best defence for Port this week is one based up the ground – denying West Coast the ability to even go forward. Port seemingly have a significant advantage in the battle for midfield territory, and a wide variety of hard running mids to throw through the mix.

West Coast team selection 


At the other end of the ground, the Eagles finished the year with the 4th best defence, with All Australians Jeremy McGovern and Eliot Yeo anchoring their defensive effort. Port have a lot of good attacking options, from Wingard and Dixon to Gray and other Gray and Boak, but in the heat of the game they have struggled to produce consistently. Unlike Port, West Coast are basically full strength across the park including down back.

A lot will rest on the retiring duo of Mitchell and Priddis to produce performances that call back to their primes in order to provide Kennedy and co. enough opportunities to score. Perhaps equally important for West Coast is the “and co.” part of that sentence – the Eagles desperately need one of Darling, LeCras or Darling to take the pressure off Kennedy and stretch the paper thin Port Adelaide backline.

If they can do so, West Coast have a fair chance of an upset, perhaps the only one of the first week of the finals.


HPN Finals Preview – Can Essendon bomb on the Swans parade?

As cold as the Swans were in starting 2017, they have finished equally hot. The same can be said for Essendon – just over the course of two years, and largely due to non on-field factors.

On paper, the Swans finished the year as a considerably better side than the Dons – which isn’t a knock on the Dons at all. Through their play all year the Bombers showed they deserved to play finals footy, however we would suggest that they wished they had drawn either the Power or Eagles in their return to finals.


After starting the year extremely strongly down back, Essendon’s defence rating took a hit over the second half of the year. Instead of having a top four defence, they ended closer to the middle of the pack – and more in line with most subjective analyses of their performance there. By contrast, the usually staunch Swans defence started out like a sieve, before remembering how to stop opposition forwards from scoring.

We can’t emphasise this enough – they remembered, and you better think long and hard about how you move the ball forward against this vice-like unit. Fortunately for the Dons, their forwardline, anchored by PAV All-Australian Joe Daniher, has scored efficiently and effectively throughout the season. Whilst the Dons have a clear anchor, it’s the variety of contributions from across the forward cohort that have done the most damage – players like Fantasia, Hooker and AMT stepping up to the plate and presenting alternate paths to goal.


Essendon are picking a mostly full strength side – with the exception of Cale Hooker. The Bombers have chosen to go with only one ruck, and Bellchambers is clearly the pick of the three options. Matt Dea and Mitch Brown are perhaps a touch stiff – with Baguley, Kelly and McGrath on the edge of the 22 according to PAV. Despite much being made of Josh Green’s absence, PAV suggests that the Bombers will be better without him, with the aforementioned forward options providing more value across the year.


The Swans are also picking a side more or less in line with their best 22 according to PAV. Aliir Aliir is rated as being one of their better defenders this year, albeit from a small sample size – and he hasn’t played since the Swans’ defence returned to league-leading levels. Whilst the omission of Tippett was one of the bigger talking points of the week, it was probably the right move (or at least according to PAV:


The HPN Team Ratings model sees the Swans winning the inside 50 battle by about half a dozen entries, and their staunch defence preventing Essendon from scoring effectively. That model predicts the Swans winning by about 17 points.

HPN Finals Preview – Can The Tigers Again Be A Force In September?


Richmond and Geelong have both been perceived by the wider footballing public as being teams with fatal flaws or issues throughout this season. Both are considered heavily dependent on the top end of their lists, led by players with fair claims to being the best in the game.

However, both find themselves with a shot at a home Preliminary Final – potentially against a suddenly vulnerable GWS. The loser will be tasked with beating (likely) Sydney and Adelaide just to make the last Saturday in September.

In short; the stakes are very high tonight.

This match looks like it should be close in terms of overall team strength, but the very contrasting line strengths of each team suggest it probably won’t play out like that as the coaches seek to amplify their strengths and cover their weaknesses.


Richmond have had the better midfield – averaging 9% more inside-50s than their opposition this year versus Geelong’s 5% extra inside-50s. The Tigers also have the second best defence in the league. By contrast the Geelong attack has been significantly stronger (4th in the league) and their defence is good, but not great. Geelong’s offence right now comes with a personnel and selection asterisk, however, and we’ll get to that a bit later.

Extrapolating these strengths into a projection suggests Richmond would win by a goal. The midfield balance suggests Richmond might expect to get a couple of extra inside-50s across the game, with their stingier defence suggesting that they would restrict Geelong to a slightly lower score. This is somewhat counteracted by the Tigers relatively impotent attack – which sat at just the 14th best in the league this year. The match may indeed end up decided by which side’s “weakness” (Geelong’s defence or Richmond’s attack) is a tiny bit stronger.

The HPN system suggests that this game will be the closest of the four finals, with the Tigers 84 to the Cats 77 being the score the system threw out. It almost certainly won’t turn out that way – but if it does, we brought it to you first.

One big reason to expect Richmond to win, unquantified by the HPN strength rating system, is that they’re fielding a full-strength team and Geelong don’t seem to be.

Richmond team selection

Richmond Player Approximate Value (PAV) per game, selected and not selected players


Richmond is perfectly primed for this match, missing just one player who played ten games this year in Jayden Short. Injury wise, the Tigers have been lucky this year and able to select from their entire list except five-gamer Nathan Drummond. HPN therefore assumes that the team selected is their preferred line-up, for at least this finals series. The Player Approximate Value scores we’ve derived seem to mostly agree with their selection calls (for example, the omission of Miles and Morris).

A look at PAV per game suggests that the most valuable players outside their selected 22 might be defenders Jake Batchelor and Reece Conca, but their per-game ratings are off tiny samples of games this year, and both were dropped after bad losses. Sam Lloyd would be a candidate up forward, but it’s a close run thing for offensive value with the selected Butler, Rioli and Castagna.

Speaking of small sample sizes, on a per-game basis Townsend is the most valuable offensive player in the league right now because of course he is. That means in his two games he’s contributed the second-most value per game to the Tigers this year. Richmond has struggled to find a reliable, permanent, secondary avenue to goal for a long time now and over the course of the year as a whole, their 14th ranked offence attests to their struggles. However, Townsend has very recently provided new hope as the Tigers caught fire late against two sides with nothing to play for. Make of that what you will.

On a per-game basis, the two most valuable players in the competition in Martin and Dangerfield are both playing tonight. PAV thinks Dangerfield has been the more valuable of the two, but they’re both ahead of anyone else:


Dangerfield and Martin (and Zorko) are all prototypical attacking midfielders, providing significant attacking power with goals, assists, inside-50s and the like, in addition to their midfield work. Martin has been effectively Dangerfield’s equal in the midfield, but the star Cat has been better at helping his team hit the scoreboard overall – as demonstrated by his five goal game as a hobbled effective full-forward against the Hawks.

Geelong team selection

geelong PAVPG2
Geelong Player Approximate Value (PAV) per game, selected and not selected players

The Cats are not quite as well primed for this final. When we compare the PAV per game of the named sides, in comparison with Richmond, the last three or four spots on the Geelong team look to be filled by very fringe talents.

They’ve probably named close to their strongest midfield (Joel Selwood’s fitness pending) except for George Horlin-Smith, and their defence likewise looks close to full power. However, oddly given their decent forward strength compared to Richmond this year, their named attack looks strangely underpowered and may have holes, especially in the wet.

Menzel’s omission comes as a surprise as he’s been their third most valuable forward this year both overall and per game. Their most valuable named offensive contributors look top-heavy as a result – with McCarthy out for the season, Cockatoo’s pace also unavailable, and Motlop struggling for form, Menzel was their most valuable available small/mid forward this year. Along with Menzel, the cult tall Wylie Buzza is also out without Rhys Stanley returning from injury, which is probably a concession to the conditions. Ahead of Menzel, the more marginal Parsons and Parfitt remain in the side. Both of them look promising, and have contributed in bursts, but not consistently.

Menzel’s ostensive direct replacement, Zach Guthrie, has not yielded much value according to PAV. We’d assume he’s in to play a backline role on a small Richmond forward or as a defensive forward, but we aren’t really sure what he’s for. He doesn’t even have a bio on the Geelong website.


Off a modest sample size of seven games, Horlin-Smith (whose fitness is questionable) might also have been a worthwhile inclusion in a mid-forward role, if available.

Most of Geelong’s major offensive contributors have been talls or Dangerwood. Hawkins and Dangerfield are the only named players averaging over a goal a game. Other talls such as Zac Smith, Harry Taylor, Rhys Stanley, Wylie Buzza and briefly Aaron Black have contributed at various levels at different stages of the season. The table below shows the top ten players for per-game offensive value for Geelong. The preponderance of talls and of players with a handful of games such as Horlin-Smith and McCarthy helps to illustrate Geelong’s odd forward line dilemma.

Top ten players for per-game Offensive PAV value, Geelong, 2017


As a side note, PAV per game suggests we all may be sleeping on Sam Menegola as a jack of all trades contributor; he’s sixth in the squad and fifth in the selected side for PAV on a per-game basis, due to sitting eighth in midfield and offense PAV per game, as well as 14th for defence.

Last year in the preliminary final, Geelong’s good season came to a halt in the face of an inability to find scoring opportunities against a stifling Sydney defence, in spite of a preponderance of bombarding inside-50 entries. In spite of Richmond’s season-long offensive struggles and the similar apparent team strengths overall, if Geelong’s scratched together small and mid-sized forward options and their midfielders can’t contribute on the scoreboard, they could well be in for a repeat dose against Richmond.

HPN Finals Preview – Can The Giants Clip The Crows’ Wings?

A lot of ink has been spilt about how GWS saw their season nearly wiped out by a massive injury toll, but this match is more likely to be shaped by a singular Adelaide injury.

Due to injury and suspension absences, it has been difficult to get a grip on just how good GWS actually are this year, with their middle of the season run looking more like a team who missed the finals than sneaking into fourth. The HPN Team Ratings have them as being the 9th best for midfield movement, 8th best at converting opportunities into points up forward and 4th best at defending when the ball gets down back.


They are almost certainly better than this.

How much better? We don’t know yet, but if they revert to last years’ form where they had the 2nd best Offensive and Defensive ratings, and 6th in the middle, they would be in with a fair shot at winning the whole damn thing this year.

Adelaide by contrast took a solid 2016 performance and improved significantly this year, finishing the year with the best Offensive rating, second best Midfield rating while sitting “only” seventh down back. On paper, Adelaide should both get the ball inside their forward 50 more often AND score more effectively when they do so. When adjusted for the expected opposition defence this week (GWS have been relatively stable in defence this year), Adelaide would be expected to score an extra point every ten inside-50s for each side – which might cause a blowout if GWS can’t batten down the hatches or win the fight in the middle.

We’ve taken an experimental step in forecasting the finals using the HPN Team Ratings, and these are predicting a win for Adelaide by about 15 points. Using this system we expect Adelaide to get around six extra inside-50s and to convert them on the scoreboard at the better rate they’ve achieved all year.

Team Selection

Adelaide Crows Player Approximate Value (PAV) per game


The big opportunity for GWS is the absence of Rory Sloane, one of the league’s elite midfielders. According to PAV, our new player value system, Sloane had the third highest MidPAV per game of any player in the league this year – a massive hole to cover.

This statistical view is well supported by subjective perceptions. Whenever Sloane was tagged out of a game or otherwise ineffective, the Crows’ gameplan appeared to fall in a heap. Greenwood has been named to ostensibly replace Sloane, but effectively the entire midfield group will be asked carry the slack. Sloane is by far the most valuable player to the Crows. The Crouches are approaching his midfield output but the MidPAV per game difference between Sloane and a decent soldier like Richie Douglas is about 40% – enough of a window to give GWS a shot to win that battle. On a total PAV per game approach, the Crows have effectively selected their strongest possible team minus Sloane and Otten from their top 22 across the season. Structurally, however, Otten is the lowest rated of the taller Adelaide defenders, and Knight (who is effectively replacing Otten) has a higher DefPAV rating per game.

The one outlier from this bunch is Jake Kelly, a player considered by PAV to be the second least valuable to play at least 20 games this year. Kelly undoubtedly fills a critical role for the Crows, able to switch between smaller and taller defenders, and cover ground, but he struggles to hit the stat sheet with any impact unlike some others who fill that switch-defender role at other clubs. Adelaide haven’t found an upgrade for Kelly this year but we suspect they would like to do so.

GWS Giants Player Approximate Value (PAV) per game


GWS are also picking near full strength side aside from some calls on the fringes, based on 2017 performances according to PAV. Interestingly, Josh Kelly has already become the Giants’ most valuable player in PAV terms.

18 of the selected GWS 22 fell within their top 22 according to PAV per game, with all of their top 15 selected. The absences are all likely explained by structural factors other than the loss of Devon Smith.

Dawson Simpson rated at 16th for GWS per game this year, on account of his “75% of Shane Mumford” routine, with Devon Smith (17th), Johnson (21th) and Taranto (22nd) the others from the top 22 to miss. Adam Tomlinson sits 23rd, but he plays a crucial structural role for the Giants as a tall and mobile defender able to slide to almost any mid-to-tall forward – expect to see him for spells on Tom Lynch this week. Johnson has had a well-documented difficult end to the season and his absence is understandable.

PAV-based selection (probably a while off being a thing anyone does) would have opted for Tim Taranto (22nd) over either Himmelberg (27th) or de Boer (32nd) to replace one of Smith or Johnson, but it is worth noting that both de Boer and Himmelberg are probably more versatile than the forward-oriented output Taranto has produced this season. With the six most forward-productive Giants already selected, that versatility may have swayed the selection table.

Overall, in spite of the selection of more players outside top-22 in PAV per games terms, it looks as though the Giants are running closer to their preferred strongest side with only some marginal calls at the fringes. The reason for this is simply that the Crows face a big question mark over how they will perform without Sloane, who is by a wide margin their most valuable player.

The 2017 PAV All Australian Team

Selection Rules

Instead of picking the top 40 players from 2017, and picking a team from there, we have decided to go down a slightly different path instead. Out of interest, here are the top 40 players according to Player Approximate Value (PAV):

AA40 2017.JPG

As you can see, there just aren’t enough defenders available to fill a team in this manner, and the number of small forwards is also a little lacking.

Similar to the AFL Coaches Association All Australian Team of 2016, we have implemented several selection rules to guide us. Firstly, we wanted to pick as versatile a team as possible, with a hybrid attack, leaning to the shorter side.

We have instituted a limit of 15 PAVs in order to make the side. That covers the top 96 players this year, with Dan Hannebery falling just on the wrong side.

We decided that the back six should be made up of two to three tall defenders, and three to four smaller defenders. In practice we will identify these by their DefPAV, however overall PAV will come into consideration for the smaller options.

The forward is selected with a slightly different mix – we wanted two or three tall forwards followed by a bunch of small/mid-sized options. We didn’t predetermine the small/mid mix because we have seen a number of different, versatile structures with small forwards come to the fore this year. The KPFs are chosen by OffPAVs, and the smaller options taken as a hybrid of OffPAV and total PAVs. More than anything, we have tried to pick a bunch of players than can rotate through the forward line and create mismatches, and can spell the first-choice midfield if required.

In the middle we don’t have pure wings, but the team shouldn’t lack pace/creativity on the outside. We think it contains a multitude of options through the middle, including from the forward line and from the bench.

The bench is filled by the next best available. We also tried to ensure that there is a second or pinch hit ruck option available to give the number one ruck a chop out.

The team

AAPAV 2017

The PAV AA side shares a lot of players with the true All Australian side, with 16 common members and six changes. Of those changes, a different structure or rules for selection would have put several of the official All Australians in our team.

2017 AA Team.JPG

Jeremy McGovern was a consideration, however he didn’t have a high enough pure DefPAV score, as he spent some time up forward in 2017. However he made several early drafts of the team. If a third tall defender were required, Daniel Talia had the third highest pure DefPAV rating, but only had 14 PAVs overall. Eliot Yeo was also a little unlucky, as he had a high number of total PAVs but lacked the gaudy defensive totals of those who made the final cut. In the end, the call was a direct decision between the stellar Hibberd and Yeo, and we opted for the more specialist defender, even if he had slightly lower total PAVs.

Looking to the midfield, Zach Merrett and Josh Kelly narrowly missed selection for this side, and both were in the top 20 players overall according to PAV. If more specialised outside mids were required, both of them would be the choices ahead of a couple of midfielders we’ve named. However, it should be noted that neither are “truly outside” – if you were looking for that, guys like Tom Scully would come into consideration.

Joel Selwood was a little further back in 33rd, however on a per-game basis he would have made the side. Matt Crouch ended up just one spot behind Selwood in 34th for the year. All of Kelly, Merrett, Selwood and Crouch had great years, but were just edged out by others.

Also in that unlucky mix are Taylor Adams, Nat Fyfe and Brad Ebert – one could argue a case for their inclusion, but we ended up sticking with the raw data. None are bad choices, are all are arguably worthy. Sydney’s Josh Kennedy would also have been close to selection had he played one or two more games as well. Clayton Oliver, considered unlucky not to make the real All-Australian team by many, was hurt by the influence of the Melbourne co-captains, Jones and Viney. Jones in particular was likely in line for a spot in the PAV All Australian side (and perhaps the real one) until injuries got the better of him.

Josh J Kennedy had the third highest OffPAV score (hampered by missing games), but the early decision to focus on a multi-dimensional forward line pushed him out. In a real game we imagine a rotation of Ryder and Kreuzer to play as the third tall forward, with Bontempelli, Martin, Parker and Dangerfield also able to fill a marking forward role depending on rotations. However, an alternate structure could be to move Martin to the centre, Wines to the bench, and Shiel out of the team.

We’ve picked Martin as a HFF because we wanted to fit an extra elite midfielder in the team, and both Dangerfield and Martin would also have qualified as small forwards. We took this liberty and ran with it, but Martin would be expected to run through the middle for most of the game.

Paddy Ryder easily makes the bench for the side, and forms a very athletic and versatile ruck duo with Kreuzer. Although Cotchin is rated higher than Wines overall, we opted for Wines in the middle in order to add grunt at the opening bounce (Wines also shades Cotchin for MidPAV). Bontempelli was a little down on last year but still had a year most would envy, and Shiel provides both grunt on the inside and class on the outside in the last spot on the pine.

Whilst we can’t say that this hypothetical side would beat the real hypothetical side (especially with 16 of them wearing two jumpers), we feel that they would give them a good run for their money.

McGrath may not have been the most valuable Rising Star

Young players have it pretty rough in footy. Learning a new level of game in a newly professional environment, many straight out of high school, it’s little wonder that even the best first-year kids don’t instantly end up in the upper echelons of the competition.

This makes evaluating young players very hard – we look for signs of future performance rather than just their present contributions – and the Rising Star award seems to do likewise. Voting for the Award is done on a 5-4-3-2-1 basis by a panel of experts and we have no clear idea why they vote the way they do, but we assume it’s a combination of both present output and intangible perceptions of potential, plus the bloke from South Australia voting for his former team’s nominee.

Andrew McGrath has today been awarded the prize, with 51 votes out of a possible 55 (nine of eleven judges gave him maximum) and the full leaderboard was as follows:

  1. Andrew McGrath – 51
  2. Ryan Burton – 41
  3. Sam Powell-Pepper – 35
  4. Charlie Curnow – 27
  5. Eric Hipwood – 10
  6. Sam Petrevski-Seton – 3
  7. Lewis Melican – 1
  8. Tom Phillips – 1

This post makes use of the Player Approximate Value, or PAV, method of player valuation which we unveiled yesterday. Below is a chart of the PAVs we have derived for each player nominated for the Rising Star this season, as well as some of the most notable non-nominees.


(We are still working on a “PAV per game” calculation that allows comparisons across seasons which contain different lengths due to finals, but here the simple calculation is valid because nobody has played finals in 2017 yet)

Applying the PAV to this year’s Rising Star candidates suggested that Sam Powell-Pepper was the most valuable to his side this year followed closely by Ryan Burton. The winner, Andrew McGrath from the Dons, performed less well. Sean Darcy, who wasn’t even nominated, was most valuable on a per-game basis in his stint as ruck for Fremantle and the other two who might have merited nominations for season output were Matthew Kennedy and Jarrod Berry. Only Jason Castagna played every game this year.

These scores aren’t necessarily great by league standards – SPP was 157th overall this year, while Burton was the 51st best in defensive PAV – which illustrates just how steep the learning curve and how hard the road ahead for even the best young players.

Why didn’t McGrath top the PAV for Rising Stars?

HPN thinks the answer to this question is that McGrath seems to have played as a non-rebounding mid-sized defender type, with a lot of “empty carb” disposals. His main notable characteristics were, according to the AFL website’s article, that he ranked among candidates “first for handballs, second for disposals and second for effective disposals”. A lot of voters for traditional awards, especially those decided post-season, look for counting stats as an easy indication of ability.

PAV doesn’t incorporate raw disposal counts into any of its valuations, and he has clearly he performed less well than some other Rising Star players in PAV-associated things like clearances, inside-50s, tackles, rebound-50s, etc. His most notable rating was a 4.9 in Defensive PAV, the fifth highest overall, suggesting he did pretty well in terms of one percenters, marks and avoiding giving free kicks. However, PAV suggests that if a defender should have been chosen, then that person should have been Burton.

With a more mature group of players around him, such as Heppell, Merrett, Hurley, Goddard, Kelly, and to an extent Watson, the critical disposals often fell to their hands, where Burton was asked to carry a far greater load for Hawthorn, and SPP was asked to do a lot in the centre of the field from day one for Port Adelaide.

We don’t doubt for a second that McGrath may end up the better player of the three vote leaders (he was pick one for a reason), but Essendon had the luxury of easing him into football as a cog with a less-damaging role, and giving him excellent support. McGrath has obviously performed the role with sufficient promise and aplomb to satisfy the voting judges.

Introducing Player Approximate Value (PAV)

One of the oldest questions in global team sport is: what is a player really worth?  To come up with a workable answer for this, we have leant heavily on work undertaken by Bill James, Doug Drinen and Chase Stuart, and looked at several different sporting codes and how they attribute player value within the team environment.

This post will describe in detail the player valuations we’ve derived under a method we’re calling Player Approximate Value (PAV). We’ve given hints of these valuations in past posts such as this one about recent retirees and this one running through statistical “awards”. We are planning to use the values we’ve derived here to replace earlier methods of trade and draft valuations, and will continue running other PAV-based analysis, so you’ll see a lot more of it in future.

Valuing players

Much of the modern advanced sport analysis can be traced back to one man: Bill James. From the publication of the first The Bill James Baseball Abstract in 1977, James has created a language to describe the sport beyond it’s base components, and has emphasised using statistics to support other obvious judgements.

In 1982 James introduced a concept called the value approximation method, a tool to produce something he called Approximate Value. He did so by stating:

“The value approximation method is a tool that is used to make judgements not about individual seasons, but about groups of seasons. The key word is approximation, as this is the one tool in our assortment which makes no attempt to measure anything precisely. The purpose of the value approximation method is to render things large and obvious in a mathemtatical statement, and thus capable of being put to use so as to reach other conclusions.”

The resultant product produced by James was inexact, but able to generally differentiate bad seasons from good seasons, and good seasons from great. James used basic achievements to apportion value, based on traditional baseball statistics. Over the years James experimented with a series of different player value measures, but he revisited Approximate Value several times, most notably in 2001. However, much of James’s later efforts focused around other methods of player valuation, and Approximate Value remains an often overlooked part of his prior work.

In 2008 Doug Drinen, of Pro-Football Reference, decided to adapt James’s original formula to evaluate which individual college postseason award was most predictive of future NFL success, but was confronted by a lack of comparable data for football players. This initial effort, while a noble attempt, was critized for using very basic statistics – games played, games started and Pro Bowls played. Whilst the results largely conformed with logic, notable outliers existed – ordinary players that saw out lengthy careers on poor teams.

Unwittingly, we created a similar method to both the original 1982 James formula and the first Drinen formula, which we used to create a Draft Pick Value chart. The method created a common currency that could be used to value the output of players drafted from 1993 to 2004, and to also predict the future output of players (1993 is considered by most to be the first true draft, as it comes two years after the cessation of the traditional under 19 competition and after the various AFL zones were wound back).

This produced this chart, as linked.

The most common criticism of the chart was, like the original Drinen analysis, it was too narrow in ignoring the quality of games versus the quantity of games played. For most players, the relationship between games played and the quality of the player is relatively linear – bad players tend not to play a lot of football before they are delisted. Due to the strict limitations placed on AFL lists, and the mandatory turnover of about 7% of each side each season, players who fail to perform tend not to stay in the AFL. A small modification we made in 2016 was to add a component of quality – namely a weighting by Brownlow Medal votes, which applied a weighting for Brownlow-implied value of players selected at each draft position above and beyond just games played.

However, the original formula still had the issue of valuing Doug Hawkins as having a better career than Michael Voss – which is patently ridiculous. And the modified formula, though doing a better job of valuation, still felt slightly incomplete.

Later in 2008 Drinen came up with the measure we know today as Approximate Value, by splitting contributions into positions and determining positional impact on overall success. Whilst it still is an approximate value measure, it was far more accurate than any other NFL value measure to date. Approximate Value is still used as a historical comparison tool of player value, worth and contribution across a variety of applications, not limited to draft pick value charts, trade evaluation and the relative worth of players across careers.

What have we done

Player Approximate Value, or PAV for short, is a partial application of the final Drinen version of AV, but applied to the AFL after a range of testing. In the vein of CARMELO and PECOTA, it is unashamedly named after Matthew Pavlich, who happens to be one of the most valuable performers in recent years under the PAV measurement now proudly bearing his name.

Basic AFL statistics are very good at determining a player’s involvement and interaction with play, but relatively poor in evaluating how effective that interaction was. On the other hand, basic statistics are reasonably effective at determining how good a team is both across a season and within each individual game. Drinen’s AV, and now PAV, both combine these two elements.

PAV consists of two components – Team Value and Player Contribution.

Team Value

When developing AV, PFR recognised that the team is the ultimate in a team sport, an approach that we fundamentally agree with. PFR split up an NFL team’s ability into two components – offence and defence. Both were evaluated on points per drive adjusted for league average.

Luckily, we accidentally stumbled on a similar approach in 2014 when trying to determine team strength, however we split strength into three categories corresponding with areas of the field – offence, midfield and defence. Unlike American Football, possession in the AFL does not alternate after a score, and turnovers aren’t always captured in basic statistics. However, after learning from Tony Corke that inside-50s are one of the stats which correlate most strongly with wins, we landed on an approach of utilising them to approximate the “drive” of the NFL.

The formulas, similar to those used in the HPN Team Ratings, which are all ratios measured as a percentage of league average:

  • Team Offence: (Team Points/Team Inside-50s) / League Average
  • Team Midfield: (Team Inside-50s/Opposition Inside-50s)
  • Team Defence: This is a little more complex.
    • Defence Number (DN) = (Team Points Conceded/Team Inside-50s Conceded)/ League Average
    • Team Defence = (100*((2*DN-DN^2)/(2*DN)))*2

All three categories are inherently pace-adjusted, and as such there is no advantage to quick or slow teams racking up or denying opposition stat counts.

Each season is apportioned a total number of PAV points (we’re just saying “PAVs”) in each category, at a rate of 100 * the number of teams in the competition. For example in 2017 there were 1800 Offence PAVs, 1800 Defence PAVs and 1800 Midfield PAVs, or 5400 PAVs overall. This ensures that individual seasons are comparable over time, regardless of the number of teams in the competition at any time.

Unfortunately, inside-50s have only been tracked since the 1998 season. For seasons before then, we have utilised points per disposal, which roughly approximates the team strengths of the inside 50 approach. There are some differences but they are relatively marginal overall – with very few club seasons moving by more than 3%.

We feel that these three basic statistics can articulate the strength of a team better than any other approach we have seen, and it happens to match the approach taken when creating AV.

Player Involvement

This is the part where HPN has deviated from the approach of Drinen and James. As positions are not strictly defined and recorded as tightly in Australian Rules as in the NFL, it would be impractical at best to use positions as a starting point for developing a player value system.

Instead, we considered that the best way for us as amateurs from the general public to identify a player’s involvement was through those same basic and public statistics. Whereas the team value as calculated above used a relatively small number of statistical categories, player involvement can be much more complicated.

To allocate value, we relied on a number of intuitive decisions, statistical comparisons and peer testing, refining until the results were satisfactory.

The first attempt we made with the guidance of Tony Corke’s statistical factors that correlate with winning margin, then making some subjective decisions made from there. This attempt produced “sensible” results and also correlated reasonably with Brownlow medal votes.

The formulae were then fine-tuned by testing subjective player rankings on a group of peers. The formulas were also tested further against Brownlow Medal votes, All Australian selections, selected best and fairest results and Champion Data’s Official AFL Player Ratings.

Although no source is perfect, PAV was largely able to replicate the judgements of these other sources, especially that of the Official Player Ratings. Generally, if a player has a higher PAV across a season, they will receive more Brownlow Medal votes:


In the end, PAV and its results were tested on a wider scale via blind testing on the internet (stealing the approach taken by Drinen when he created AV), and the results largely confirmed the valuations taken by PAV. The formulae for each line are:

  • Offensive Score = Total Points + 0.25 x Hit Outs + 3 x Goal Assists + Inside 50s + Marks Inside 50 + Free Kick Differential
  • Defensive Score = 20 x Rebound 50s + 12 x One Percenters + (Marks – 4 x Marks Inside 50 + 2 x Free Kick Differential) – 2/3 x HitOuts
  • Midfield Score = 15 x Inside 50s + 20 x Clearances + 3 x Tackles + 1.5 x Hit Outs + Free Kick Differential

The weightings and multipliers used in each component formula will necessarily look a bit arbitrary, but are the results of adjustment and tweaking until the results lined up with other methods of ranking and evaluating players as described above.

As the collection of several of these measures only commenced in 1998, we have also adapted another formula for the pre-1998 seasons which correlates extremely strongly with the newer formula. Whilst we feel it is less accurate than the newer formula, it still largely conforms to the findings of the newer formula. This formula was created by trying to minimise the standard deviation for each player’s PAV across the last five seasons of AFL football. Around 5% of players have a difference in value of more than one PAV between the new and old formulas.

We will publish the pre-1998 formula in the not-too-distant future.

Putting It Together

The final step combines individual player scores and team strength calculations to produce the final PAV for each player. This is done in two steps.

Firstly, the individual component scores for each team are compiled. Each player’s individual player score is converted to a proportion of total team score, telling us the proportion of value they contributed to that area of the ground.

Secondly, the team value (i.e. team strength as outlined above) is multiplied by the proportion of the component score for each player.

An example will help illustrate this.

In 2016 the Blues midfield earned 96.71 Midfield PAVs across the whole side (being below league average). Bryce Gibbs accrued a Midfield Score of 3984, and the team tallied up 37702 in midfield score in total. As a result, Gibbs contributed 10.567% of the total Midfield Score for Carlton, and receives that part of the 96.71 Midfield PAVs that Carlton had gained – or 10.22 MidPAVs.

These calculations are done for every player in the league for every side. The overall PAV value for each player is merely the three component values added together. For Gibbs in 2016, this is his 10.22 MidPAVs with 6.86 OffPAVs and 3.21 DefPAVs for a total of 20.29 PAVs all up. Which is pretty good.

What PAV should be able to tell you

Two key advantages of PAV, we feel, are that it can be replicated based entirely on publicly available statistics, and that by using a pre-1998 method, we have derived a fairly long set of historical values.

While HPN intends to publish PAV to a finer degree than PFR, there still remains a great deal of approximation in the approach. This is especially the case for pre-1998 values, which rely on a far smaller statistical base. We cannot definitively state that these are the exact values of each player relative to other players; however we feel that the approximation is closer than any other method that has as long a time series made with publicly available data. It is possible, and indeed likely, that some lower-ranked players are better players than those above them in certain years.

What we are more confident of is that the values are indicative of player performance relative to others across a longer period of time. Or; in that given year, player X was likely more valuable than player Y, or at least to their team.

As it draws its fundamental values from team rankings, it is much harder to draw a higher value from a bad team than it is a good team. This scales player value to more highly rate performance in a good side, and specifically it highly rates players in good parts of the field in good sides.

As a group, players with a PAV of 18 should be better (or have had a better year) than those who are ranked with 16. As a rule of thumb a season with a PAV of over 20 should be considered to be a great season, with any PAV over 25 should be considered exceptional. This varies slightly for different positions – an All Australian key position defender may have a lower overall PAV than a non-All Australian midfielder, but with an extremely high rating in the defence component.

Below is a list of the players with the highest season long PAVs between 1988 and 2016:


2017 isn’t finalised yet, but the top end of the list to date is populated with Brownlow Medallist years and players considered to be the absolute elite of the league over the past two decades. While there are some year-on-year PAVs that conflict with common opinion, these top-end player-years do not contain any. Yes, that Stynes year was that good.

On a career basis, the top rated players should be fairly uncontroversial:


The top ten players on this list not only had successful careers, but also incredibly long careers as well. Note that this is current to 2016, so Gary Ablett Jr has more value to come.

Every player made multiple All Australian teams, and a majority were considered at different points of time to be the “best player in the game”. As such, PAV ends up being a measure of not only quantity of effort but also of quality.

What are the weaknesses of PAV?

Like almost any rating system, there are always blind spots – especially in early phases of development. Like in almost any rating system in any sport, there appears to be a slight blind spot in valuing truly pure negating defenders. Consider Darren Glass, possibly the finest shutdown KPD of the AFL era. He is somewhat overlooked from an overall perspective by PAV:


Glass’s Defence PAV still remains elite during this era, but he provided little to no value to any other part of the Eagles’ performance across the period. It’s worthwhile to compare Glass to the namesake of PAV for a comparison:


This is a lesson to sometimes look beyond the headline figure to the components that make it up. It’s worthwhile look beyond the Overall PAV figure for the relevant component figure for the player’s specific role, especially for specialist players. We can also see with a player like Pavlich that his shifting role over his career is revealed by PAV. Generally, a component PAV of more than 10 for a specialist player will place them in contention for an All Australian Squad selection (cf. Glass above), if not selection in the side itself.

Occasionally a season pops up that defies conventional wisdom, such as Shane Tuck’s highly rated 2005 season, or Adem Yze, who rates so highly via PAV as to suggest he was under-recognised throughout his career.

However, Insight Lane brought a very interesting observation to our attention this week, from Bill James himself:

As noted at the top, we’ll be applying this system throughout the draft and trade period to evaluate trades and draft picks, and probably in a lot of other analysis from here on out, as well. Stay tuned in the coming days for an All-Australian team based on PAV.

In our time developing and testing PAV, it has usually confirmed our conventional thinking, but occasionally surprised us. Which makes us think we might be on the right track. With system comes the ability to analyse, so the goal for us in developing this approach is to emulate and augment subjective judgments with a systematic valuation, rather than to create a value system alien to an actual “eye test”.

If you have any comments or questions about PAV, please feel free to contact us via twitter (@hurlingpeople), or email us at hurlingpeoplenow [at] gmail [dot] com. We are more than willing to take any feedback on board, and if you want to use or modify the formulas yourself, feel free to do so (just credit us).

Thanks to all that provided help, assistance and the reason for the development of PAV, namely Rob Younger, Matt Cowgill, Ryan Buckland, Tony Corke, James Coventry, Daniel Hoevanaars… and everyone we are forgetting here. We will add more when we remember who we have forgotten.