31st August 2011 Category: Statistical Analysis

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When analysing the effectiveness of a ruckman, it’s often the ‘hitouts’ column that draws the most attention. But just like with kicking and handballing, some players are more effective than others. 

The table below focuses on statistical areas relating to the tap-work of ruckmen. Including: Hit-outs (HO), Hit-outs To Advantage (HTA) and Effective Hit-outs (%EffHO) 

The difference between 'Hit-outs To Advantage' and 'Effective Hit-outs'
- Hit-outs To Advantage: refer to when a player taps the ball directly to a teammate from a stoppage.

- Effective Hit-outs: refer to hit-outs that result in retaining team possession - and ultimately first disposal. 

Notes:

  • The table is sorted by percentage of Hit-outs to Advantage (%HTA).
  • The rank on the left refers to Hit-outs per game (HO).
  • When it comes to delivering effective hit-outs, it’s the heavy built ruckmen (typically stand and tap ruckmen) like Mark Jamar, Darren Jolly and Shane Mumford that deliver the best results.
  • For the most part, ‘Hit-outs To Advantage’ and ‘Effective Hit-outs’ go hand in hand, but there are exceptions. Robbie Warnock is an example of a ruckman that gets flattered by the effectiveness of his midfielders. The numbers indicate that Warnock is good at tapping to a general area and gaining ground for his team, but not necessarily skilled at tapping directly to the advantage of a teammate.
  • By these measures, Sam Jacobs is perhaps the most misleading ruckmen in the league. Jacobs is ranked 5th in the AFL for hit-outs per game, but ranks toward the bottom in hit-outs to advantage and effective hit-outs.

Hit-out statistics (per game) 2011: 

Rank (HO) Player GP HO HTA %HTA %EffHO
6  M Jamar (MELB)   14    29.2     12.1     41.4    50.9 
11  D Jolly (COLL)  12 24.8 9.8  39.5   54.0 
3  S Mumford (SYD)  16 32.8 12.8  39.0   50.1 
23 T Bellchambers (ESS) 13 20.5 7.7 37.6 46.6
8 D Cox (WCE) 21 28.0 10.5 37.5 44.8
2 A Sandilands (FRE) 12 34.3 11.7 34.1 48.1
25 N Naitanui (WCE) 19 18.1 6.1 33.7 44.5
18 B Hudson (WB) 16 22.5 7.4 32.9 48.3
28 Z Smith (GCS) 19 17.0 5.5 32.4 48.9
4 M Leuenberger (BL) 21 32.0 10.3 32.2 45.5
1 T Goldstein (NMFC) 20 36.2 11.3 31.2 48.5
7  R Warnock (CARL)  17 28.1 8.5  30.3   50.2 
9 B Ottens (GEEL) 16 25.2 7.6 30.2 45.7
 5   S Jacobs (ADEL)   18   31.9   9.6   30.1   44.8 
19 M Bailey (HAW) 13 21.0 6.2 29.5 47.6
17 B McEvoy (STK) 20 22.6 6.6 29.2 44.2
22 D Brogan (PORT) 11 20.5 5.8 28.3 43.8
15 C Wood (COLL) 11 23.5 6.2 26.4 47.9
13 A Graham (RICH) 13 23.8 6.0 25.2 48.5

19th August 2011 Category: Statistical Analysis

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Grant Birchall has only failed to get more than 20 disposals in 5 games this season. 4 of those games have been losses. If there was ever a barometer for a team, it’s Birchall for Hawthorn.

Birchall averages 25.1 disposals a game in Hawthorn wins, but only 17.5 in losses. The difference represents a percentage drop of 30% - greater than any other player at the club.

Carlton’s plan to stop Hawthorn, starts with Birchall.

Notes:

  • Good teams have recognised Birchall’s influence - 3 of Hawthorn’s 4 losses have been inflicted by Geelong and Collingwood.
  • Birchall is currently ranked 17th in the league for total effective disposals, and of those top ranked, Birchall is 2nd only to Scott Pendlebury in percentage of effective disposals. Birchall’s disposal efficiency on the season stands at 77.2% (Pendlebury - 78.3%). Birchall efficiency hasn’t been affected in losing games.
  • Birchall is ranked 13th in the league for uncontested possessions per game.

Birchall's win/loss averages:


GP DSP KCK MRK HBL TKL R50 UCP %DE
Wins 15 25.1 15.1 7.1 10.1 1.5 3.4 18.5 76.2
Loses 4 17.5 10.0 5.5 7.5 2.3 2.0 13.8 78.9
% Diff. - -30.4% -33.6% -22.9% -25.5% +46.7% -41.2% -25.8% +3.5%

18th August 2011 Category: Statistical Analysis

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Watching Melbourne on the weekend, it seemed like every time they went inside 50 it was Nathan Jones or Clint Bartram taking them there. 

Melbourne finished the game with a total of 44 inside 50’s. Jones and Bartram were collectively responsible for 11 of those entries. The problem for Melbourne was that Jones and Bartram, on the day, operated at a combined disposal efficiency of 54.5%.

When it comes to inside 50’s, it’s not a matter of how many, but rather who takes you there.

The table below looks at the top 5 ranked players for total inside 50’s at each club this season. The idea is to find out who each club is using to kick them inside 50. The table doesn’t include forwards like Travis Cloke, Mark LeCras and Adam Goodes. The table is ranked by the disposal efficiency of each clubs top 5 inside 50 players. 

Notes:

  • As with most performance indicators this season, Collingwood and Geelong lead the way.
  • Disposal efficiency can be misleading, this is why the table includes kicks to advantage. Hawthorn for example rank toward the bottom in disposal efficiency (%DE), but are fourth in kicks to advantage (KTAdv).
  • The column showing percentage of total inside 50’s provides an indication of a teams reliance on stars. For example, Carlton generate over 40% of their total inside 50’s from Simpson, Judd, Murphy, Scotland and Robinson. The only team that is more reliant than Carlton on their top 5 is Gold Coast.
  • Sydney are the lowest ranked team by disposal efficiency. They compensate for their poor entry, by retaining the ball once it's kicked inside 50. Sydney are the league leaders for tackles inside 50.
  • Some teams are conscious of putting the ball in the hands of their best users. Goddard for St Kilda, Deledio for Richmond , Scotland for Carlton, Duffield for Fremantle and Robert Murphy for the Bulldogs are probably the best examples.
SA = Score assists, %DE = Disposal Efficiency, KTAdv = Kicks To Advantage (refers to the total of the 5 players), TKL I50 = Tackles Inside 50 (refers to the team total). Column 3 - I50's figure represents the number of Inside 50's by the five players. The figure in brackets (Tot. I50's) represents the teams total inside 50's.
 
Team Top 5 players for total inside 50's (%DE) I50's (Tot. I50's) % of Tot. I50's SA %DE KTAdv TKL I50
COLL Swan (70.5), Pendlebury (78.3), Thomas (68.0), Wellingham (68.6), Ball (71.3) 387 (1239) 31.23 180 71.3 508 201
GEEL Corey (70.3), Selwood (69.5), Kelly (68.7), Bartel (73.7), Chapman (73.2) 417 (1208) 34.52 174 71.1 506 165
STK Montagna (63.6), Gram (68.1), Dal Santo (72.3), Goddard (77.1), Jones (69.6) 302 (957) 31.56 113 70.1 473 163
CARL Simpson (67.8), Judd (66.8), Murphy (74.8), Scotland (75.5), Robinson (65.4) 467 (1120)  41.70  209 70.1 580 212
NM Wells (67.4), Swallow (70.5), Harvey (68.5), Ziebell (61.6), Adams (75.6) 384 (1051) 36.54 162 68.7 409 159
BRIS Black (71.3), Polkinghorne (61.9), Rich (61.4), Rockliff (74.7), Leuenberger (72.4) 314 (915) 34.32 117 68.3 393 127
ADEL Thompson (68.1), Van Berlo (67.7), Reilly (74.1), Dangerfield (65.7), Douglas (63.3) 313 (965) 32.44 124 67.8 398 124
MELB Sylvia (66.3), Moloney (69.0), Jones (67.8), Martin (68.6), Petterd (63.3) 351 (976) 35.96 138 67.0 338 138
ESS Zaharakis (67.2), Stanton (66.8), Howlett (69.5), Melksham (61.4), McVeigh (69.6) 359 (1115) 32.20 133 66.9 443 150
PA Boak (69.4), Pearce (61.4), Broadbent (63.4), Hartlett (68.6), Thomas (71.1) 269 (867) 31.03 100 66.8 328 145
WCE Shuey (70.0), Embley (63.9), Rosa (72.4), Priddis (69.4), Nicoski (56.4) 349 (1025) 34.05 155 66.4 344 173
FRE Pavlich (61.3), Hill (65.2), Fyfe (62.7), Lower (69.1), Duffield (73.8) 311 (930) 33.44 136 66.4 371 192
WB Griffen (60.0), Boyd (62.8), Ward (67.7), Cooney (62.3), Murphy (78.8) 382 (968) 39.46 134 66.3 433 144
HAW Mitchell (65.7), Shiels (64.0), Sewell (66.6), Lewis (68.7), Hodge (65.9) 359 (1061) 33.84 150 66.2  500  150
RICH Cotchin (59.2), Deledio (71.3), Jackson (60.9), Grigg (69.6), Martin (65.5) 390 (970) 40.21 142 65.3 441 131
GCS McKenzie (58.9), Ablett (66.1), Rischitelli (64.4), Swallow (64.1), Brennan (65.6) 385 (867) 44.41 130 63.8 330 100
SYD Kennedy (59.9), O'Keefe (56.1), McVeigh (65.0), Jack (59.9), Hannebery (65.3) 358 (1032) 34.69 122 61.2 294  206  

16th August 2011 Category: Statistical Analysis

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Breaking down the performance of the Suns' top recruits.

Gary Ablett: A+

The overriding doubt with Ablett’s move, was his ability to lead a young team. The visual evidence suggests that Ablett has handled the extra responsibility as well as any first year captain. On an individual level, Ablett’s performance has been equal to, or greater, than his previous two seasons with Geelong.

  • Ablett's disposals have dropped and his tackles are up - a mark of the team having less possession.
  • Ablett is having to win more of his own ball than last season - contested possessions and frees-for up.
  • Ablett’s playing style has changed slightly - he’s having to play more direct, and with less support - kicks per game steady and handballs per game well down.

Year Team GP KCK HB DSP MKS GLS TKL FF FA CP CLE %DE PR
2011 GCS 17 14.9 14.2 29.1 2.2 1.0 5.8 1.9 0.8 15.9 6.7 66.1 7.68
2010 GEEL 24 14.1 17.4 31.5 4.4 1.8 4.2 0.9 1.1 14.1 5.5 75.0 8.01

Nathan Bock: A

Bock is the league leader in rebounds off 50 - over the past 5 games, he’s averaged 11.2 rebounds per-game. His performance throughout July and August has lead to talk of All Australian selection. Bock has provided stability for a lightweight Sun's defence.

  • Bock is winning significantly more of his own ball and taking responsibility for distributing once he gets it - both his contested possessions and rebounds off 50 are well up.
  • Bock is one of the few recruit to have held steady marking numbers and increased contested marks.
Year Team GP KCK HB DSP MKS CMK TKL CP PR
2011 GCS 18 14.6 5.4 20.0 6.9 0.7 1.7 6.2 6.71
2010 ADEL 13 12.1 7.6 19.7 7.0 0.4 1.6 4.5 6.37

 

Michael Rischitelli: B+

Coming off a career year for the Lions, Rischitelli started the season well but has faded slightly over the past month. The drop may be due to his extra workload with the Suns.

  • Rischitelli has made slight improvements in tackles, clearances and contested possessions, the rest of his numbers remain steady with last season.
Year Team GP KCK HB DSP MKS TKL CLE CP %DE PR
2011 GCS 18 11.8 11.4 23.2 4.6 5.6 4.9 10.9 64.4 6.95
2010 BRIS 22 12.6 11.4 24.1 5.7 4.4 3.9 9.8 70.3 7.03

 

Jared Brennan: B

Brennan made a positive start to the season but has struggled with injuries in the second half of the season. Known predominantly as an attacking player with the Lions, Brennan's become a more accountable player with the Suns.

  • Improved tackle numbers and an increase in contested possessions are good signs for Brennan. 
Year Team GP KCK HB DSP MKS GLS TKL HO CP PR
2011 GCS 19 11.6 7.3 19.0 4.5 0.5 4.8 0.6 10.6 6.64
2010 BRIS 18 12.9 6.8 19.7 5.7 0.5 3.7 1.4 8.4 6.99

 

Campbell Brown: B

Brown’s great gift to the Suns is his contribution to establishing a positive club culture. His hardness and commitment is unquestioned, and on that front he's delivered as expected. Performance wise, Brown’s numbers are steady with his last season at Hawthorn.

  • Brown's Player Rating has dropped significantly from 2010 to 2011.
Year Team GP KCK HB DSP MKS TKL CP 1% PR
2011 GCS 14 8.7 5.1 13.9 3.9 2.1 6.3 6.1 5.72
2010 HAW 17 8.4 5.2 13.6 5.1 3.2 6.2 4.8 6.43

 

Jarrod Harbrow: C+

Like Rischitelli, Harbrow signed for the Suns on the back of a career best season in 2010. In 2011 most of Harbrow's stats have either held steady or dropped.

  • Harbrow drop off in inside 50's is an indication of his increased defensive responsibility.
  • Harbrow has suffered a significant drop in disposal numbers.
Year Team GP KCK HB DSP MKS TKL I50 R50 CP PR
2011 GCS 19 13.0 7.5 20.5 3.6 2.7 1.5 5.8 6.8 6.46
2010 WB 22 15.4 7.3 22.7 5.6 2.1 2.4 5.5 6.6 6.69

 

Josh Fraser: B+

Fraser’s career looked finished at the end of 2010 and without the addition of the Suns, may have been forced into retirement. Fraser’s contribution to the Suns in 2011 has exceeded expectation - statistically he’s back to the level he was at in 2006/2007. 

  • Fraser has improved in all the key areas for a ruckman - improved hitout numbers, more contested possessions and more marks.
Year Team GP KCK HB DSP MKS TKL HO CP PR
2011 GCS 14 8.5 6.4 14.9 4.0 1.6 13.6 6.9 6.15
2010 COLL 9 5.8 4.4 10.2 3.1 2.0 10.1 5.4 6.02

12th August 2011 Category: Statistical Analysis

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The term "staging" is a blanket term that can be interpreted in a number of different ways. In this article the term "staging" is used to cover everything from feigning injury to accentuating or manipulating contact.

Earlier in the year, Angus Monfries caused a stir when he admitted to playing for free-kicks. At the time Rodney Eade said: "He's the best out of the competition [at staging for free kicks].”

But who else is up there? Who are the best stagers in the AFL? In an attempt to find the answer, we’ve taken a look at the top 40 free kick winners in the competition.

The first thing you notice when looking at the top 40 is that it’s dominated by ruckmen. 4 of the top 10 spots are occupied by ruckmen - Dean Brogan (1), Todd Goldstein (5), Mark Jamar (7), Dean Cox (8).

For the sake of this study we’ve omitted ruckmen. Ruck contests lead to an unnatural number of free kicks, which gives ruckmen more opportunity than other players to win free kicks. Players that have played less than 10 games this season have also been omitted.

There are certain players that are expected to receive free kicks. Players that get themselves to a lot of contests (the likes of Andrew Swallow, Gary Ablett, Matt Priddis) and players that regularly put their head other the ball (Jude Bolton, Luke Ball and Jordie McKenzie).

All of the players mentioned above are in the top 40. The consistent statistics with all of them (apart from free kicks) is that they all average a high number of possessions (20 plus per game) and a high number of tackles (5 plus per game).

So to get an idea of who (statistically) draws the most free kicks - with the least amount of opportunity - we’ve divided (in the table below) each players average number of free-kicks-for per game with their average possessions per-game and their average tackles per-game. 

The equation: Average Free-Kicks-For Per Game  --DIVIDED BY-- (Average Possessions Per Game + Average Tackles Per Game).

The theory behind the equation is:

  • The more a player has the ball, the more opportunity they have to win free kicks - meaning they don't necessarily "stage" for them.
  • The more a player tackles, the more likely it is that that player wins free kicks - as opposed to "staging" for them.

We're trying to find the player that draws the most free kicks with the least number of opportunities. 

Rank FKPG Rank Name Games FKPG PPG TPG FKPG/(PPG+TPG)
1 16 Kurt Tippett (ADEL) 15 1.9 11.1 1.9 0.146
2 39 Jonathan Brown (BRIS) 10 1.6 12.4 0.7 0.122
3 11 Drew Petrie (NM) 18 2.1 14.3 3.0 0.121
4 9 Chris Dawes (COLL) 13 2.2 14.9 3.6 0.119
5 24 Patrick Dangerfield (ADEL) 18 1.8 16.2 2.7 0.095
6 21 Adam Selwood (WCE) 18 1.8 16.9 2.1 0.095
7 35 Clint Bartram (MELB) 11 1.6 15.4 2.9 0.087
8 13 Matt Thomas (PA) 16 2.0 17.1 6.4 0.085
9 29 Scott Thompson (NM) 19 1.7 17.2 2.8 0.085
10 33 Allen Christensen (GEEL) 13 1.7 16.2 3.8 0.085
11 24 Angus Monfries (ESS) 18 1.8 17.7 4.0 0.083
12 2 Joel Selwood (GEEL) 14 2.7 27.3 5.8 0.082
13 30 Alex Rance (RICH) 15 1.7 18.9 2.7 0.079
14 13 Heath Hocking (ESS) 14 2.0 18.9 7.0 0.077
15 6 Andrew Swallow (NM) 19 2.4 25.2 6.4 0.076
 
So to get down to the top five, there are certain players that have to be ruled out: 
  • Honest players that are subject to a lot of physical attention - Tippett, Brown, Petrie and Dawes.
  • Small players that are likely the victims of bad tackles and are seen to be honest players - Bartram, Christensen.
  • Elite tacklers that "win" a lot of free-kicks - Thomas and Swallow.

Taking into account the table and considering the visual evidence from week to week, the top 5 stagers in the AFL are:

Patrick Dangerfield: Instead of standing up in tackles, Dangerfield lets his body go in order to accentuate contact.

Adam Selwood: If you do an image search on Selwood, you'll see a lot of images of him throwing his head back while being tackled.

Scott Thompson: Takes a different approach to winning free-kicks to the rest of the list. Thompson annoys his opponents until they snap, then makes sure that the contact can be seen.

Angus Monfries: Often wins soft free kicks by falling forward in tackles and in marking contests. 


9th August 2011 Category: Statistical Analysis

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The division between "good" and "bad" clubs in 2011 has been highlighted this week with the form of league leaders, Collingwood and Geelong. The Cats have been ruthless over the past couple of weeks. Collingwood, too, have been impressive, but as the Pies prepare their team for the run into the finals, the form of veterans, Alan Didak and Nick Maxwell, is cause for concern.

Didak has been out of form all season, performing well below expectation and well below his own lofty standards. Truth be told if Alan Didak wasn’t Alan Didak he’d have surrendered his spot to one of Alex Fasolo, Dane Beams or Luke Rounds months ago. If Didak’s current form-line continues, Mick Malthouse will have a tough decision to make come finals time.

Maxwell’s statistical drop hasn’t been as dramatic, but his role in the team this season has diminished considerably – due in large part to the addition of Chris Tarrant and the development of Ben Reid. Maxwell’s role is now more about leadership than actual contribution.

 

Alan Didak 2009-2011:

  Games Kicks H'balls Disp. Marks Goals Tackles Rating
2011 13 11.4 6.2 17.6 2.8 0.7 2.8 5.99
2010 24 14.6 10.0 24.6 4.2 1.7 2.7 7.48
2009 20 17.9 7.6 25.5 5.0 1.0 1.8 -
 

Nick Maxwell 2009-2011:

  Games Kicks H'balls Disp. Marks Goals Tackles Rating
2011 15 7.9 5.1 13.0 3.9 0.0 2.6 5.93
2010 22 8.4 7.0 15.4 5.5 0.0 2.7 6.51
2009 23 8.9 9.0 17.9 6.4 0.1 2.6 -


3rd August 2011 Category: Statistical Analysis

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Last week, Geelong fans were doubting the return of big man Cam Mooney. A week on and Mooney looks well placed to find a spot in the Cats finals team after kicking 5 goals against Melbourne at the weekend. The fact that playing Melbourne on Saturday was the equivalent of playing the Corio under 14’s is largely irrelevant. Mooney’s got his swagger back.

It’s not the first time this season Melbourne has helped turn a season. Back in round 9, Melbourne faced off against St Kilda. The Saints at the time were on a 3 game losing streak and had won just 1 of their first 7 games. St Kilda beat Melbourne, and the victory sparked a run of 7 wins from their next 9.

The player that got his swagger back that day… Brendon Goodard, with a season high 37 touches and 9 Marks.

Goddard had endured a tough start to the season, his form from 2010 had all but disappeared and talk of a move to one of the league’s new franchises had dissipated as his stock dropped.

In the seven games leading up to the game against Melbourne, Goddard averaged 20.2 disposals a game, well down on the 28.8 disposals a game he averaged in 2010.

Throughout the 25 games Goddard played last season not once did he get less than 20 touches. By round 9 this season Goddard had already had 3 games where he failed to reach the 20 touches mark.

Since playing Melbourne, though, Goddard has recaptured form. In the last three weeks alone, Goddard has averaged over 32 possessions a game.

 

Goddard's 2011 Per Game Averages:

 
Games Kicks H'balls Disposals Marks I50's
Round 9 - 19 10 15.8 11.5 27.3 7.8 3.7
Round 1 - 8 7 10 10.2 20.2 3.6 2.4
 

Disposals - Round by Round - 2011:


R1 v GEEL R2 v RICH R3 v ESS R5 v BRIS R6 v ADEL R7 v CARL R8 v HAW R9 v MELB R10 v FRE R11 v COLL R12 v WB R13 v GEEL R15 v NM R16 v PA R17 v WCE R18 v ADEL R19 v GC AVG.
Disp. 22 15 28 26 21 16 14  37  10* 24 26 24 28 27 30 30 37 24.4
*Goddard suffered a game ending injury late in the first quarter against Fremantle.

28th July 2011 Category: Statistical Analysis

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Yesterday’s article focused on the inconsistency of the Bulldogs midfield. Today's post looks at the rest of the competition. 

As a way of measuring the inconsistency of a clubs top players, we’ve identified the top 5 possession winners at each club, then calculated their average disposals - in games won - compared with their average disposals - in games lost. 

The theory is that the closer the two averages are, the more consistent the player is. And the closer to zero the collective average of the 5 players, the more consistent a teams stars are. 

Notes:

  • In order to get a fair sample, only players that have played in at least 13 games including at least 5 wins and 5 losses have been included. This eliminates Collingwood, Geelong, Adelaide, Brisbane, Gold Coast and Port Adelaide.
  • For the record, Collingwood and Geelong's figures were: Pies: -5.85% and Cats: +2.89%.
  • The table supports the popular belief that North Melbourne and Sydney are honest, consistent teams. And the Demons and the Bulldogs are inconsistent.
  • Fremantle had an inconsistent start to the season, but one of the other reasons for their high position is that 3 of their top 8 possession winners this season have missed 5 or more games.
 
 
 
Top 5 Avg. Disposal Winners
Avg. % Diff.
Consistent
Inconsistent
Melbourne Moloney, Jones, Trengove, Sylvia, Gysberts -15.73% Jones (+0.9%) Moloney (-35.7%)
Bulldogs Boyd, Griffen, Cross, Cooney, Higgins -15.57% Boyd (+0.3%) Cross (-25.7%)
Fremantle Fyfe, Pavlich, Broughton, Hill, Ibbotson -15.50% Hill (-10.7%) Ibbotson (-23.9%)
West Coast Priddis, Embley, Rosa, Shuey, Cox -10.17% Priddis (+4.1%) Embley (-21.0%)
Richmond Deledio, Cotchin, Martin, Grigg, Houli -9.89% Grigg (+0.5%) Houli (-18.9%)
St Kilda Dal Santo, Montagna, Goddard, Gram, Fisher -9.02% Fisher (+6.7%) Montagna (-30.3%)
Carlton Murphy, Judd, Scotland, Gibbs, Carrazzo -7.21% Gibbs (-0.8%) Carrazzo (-22.1%)
Essendon Stanton, Heppell, Zaharakis, Hocking, Howlett -6.66% Heppell (0.0%) Hocking (-35.8%)
Hawthorn Mitchell, Suckling, Hodge, Shiels, Birchall -5.75% Mitchell (+11.2%) Birchall (-33.3%)
Sydney O'Keefe, Bolton, Kennedy, McVeigh, Hannebery -2.77% McVeigh (+1.4%) Bolton (-20.6%)
North Melb.  Swallow, Wells, Rawlings, Harvey, Adams 0.90% Swallow (-3.1%) Rawlings (-16.1%)

Using Melbourne as an example, here is how the figures are calculated. Melbourne supporters should find some comfort in the fact that the average age of their top 5 is 23, and their total number of games played is 397. The Bulldogs top 5 have an average age of 26, and have played a total 744 games.
 
  Avg. Disp. (Wins) Avg. Disp. (Losses) % Difference
Brent Moloney 29.4 18.9 -35.71%
Nathan Jones 23.6 23.8 +0.85%
Jack Trengove 21.1 19.2 -9.00%
Colin Sylvia 20.9 19.9 -4.78%
Jordan Gysberts 23 16.1 -30.01%
Average % Difference: -15.73%

27th July 2011 Category: Statistical Analysis

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Two weeks ago it looked like the Bulldogs were back on track. Since then they’ve lost two winnable games, lost hope of playing finals and got news that key forward Barry Hall won’t be with the club in 2012. 

The win over Carlton in round 16 was their best for the season, and one of the best team performances in 2011. When the Dogs are hot, they’re almost untouchable, but - like their pseudo star midfielders - they can swing dramatically cold too.

The Bulldogs inconsistency is a reflection of their inconsistent stars.

In 2011, 5 of the Bulldogs top 6 possession winning midfielders have averaged dramatically lower disposal numbers when the team loses. Teams typically have fewer possessions in losing games, so naturally the stats of some players are going to fall, but the drop normally wouldn't affect so many of a teams top ball winners. 

Notes:

  • The Bulldogs next 3 highest ball winners, Robert Murphy, Ryan Hargrave and Tom Liberatore also average lower disposal numbers in losses.
  • Daniel Giansiracusa is the only other player (apart from Boyd) in the top 10 possession winners at the club that averages equal or greater disposals in losses. 18.0 (wins) vs 18.1 (loses).
  • Ben Hudson (+1.2) and Liam Picken (+3.4) have the best positive swings when comparing possessions in wins with possessions in losses.
  • The Bulldogs are renowned as a skillful, technical team that thrives in possession of the ball, if their best players aren't getting their hands on the ball they struggle to compete.


Avg. Disp. (Wins) Avg. Disp. (Losses) % Difference
Matthew Boyd 30.3 30.4 +0.33%
Ryan Griffen 26.1 23.6 -10.59%
Daniel Cross 27.6 20.5 -34.63%
Adam Cooney 24.3 19.2 -26.56%
Shaun Higgins 24.5 19.2 -27.60%
Callan Ward 23 19.5 -17.95%


19th July 2011 Category: Statistical Analysis

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Tom Scully's proposed move to Greater Western Sydney has led to questions about Scully’s standing in the AFL. Will he be an elite player? What compensation should Melbourne receive? What kind of contract does he deserve? 

The table below compares Scully's first two seasons in AFL with the first two seasons of some of the AFL's top midfielders. In particular it focuses on players that made an immediate impact in the league. The numbers put Scully in elite company. 

A few things to note when looking at the table:
  • The players are ranked by average disposals per game.
  • All of the top 6 started their careers in 2007 or later, which indicates that recently it has become easier for first and second year players to put up big numbers.
  • Dale Thomas and Gary Ablett played predominantly in the forward line in their first two seasons.
  • The hype around Scully should be tempered slightly due to the fact that Rhys Palmer and Daniel Rich put up similar numbers in their first two seasons.
  • Rhys Palmer is the only player on the list whose average disposals per game dropped from season one (22.7) to season two (20.8).
  • On average the players listed increased their average disposals per game from season one to season two by 24.8%. Palmer's average decreased by 8.4%.

Averages per game for first two seasons in AFL:

Player Debut Games Disp. Kicks Marks HB Tack. Goals Clea. CP   DE%     SA  
Joel Selwood 2007 45 22.5 11.0 4.8 11.5  4.2 0.3 3.4 9.1 76.4 1.9
Tom Scully 2010 27 22.4 9.1 3.1 13.3 4.6 0.2 3.7 9.0 70.3 1.7
Rhys Palmer 2008 25 21.8 11.3 4.3 10.5  4.1 0.6 3.2 8.9 68.1 1.0
Daniel Rich 2009 46 18.8 10.7 2.9 8.1 5.0 0.5 3.6 8.6 64.4 1.5
Marc Murphy 2006 35 18.1 11.8 4.9 6.3 3.9 0.6 2.6 7.3 70.6 1.9
Chris Judd 2002 45 17.0 11.0 2.4 6.0 4.5 1.2 3.9  11.5  64.0 1.5
Daniel Kerr 2001 42 16.7 8.4 2.0 8.4 5.1 0.6 2.7 12.5 66.8 1.4
Scott Pendlebury 2006 32 16.2 9.0 5.3 7.2 4.0 0.7 1.4 6.5 80.0 0.9
Dale Thomas 2006 41 15.0 9.7 5.8 5.3 3.3 0.7 0.8 5.9 74.0 1.1
Sam Mitchell 2002 30 14.8 7.7 2.3 7.2 5.4 0.2 4.0 8.5 69.7 0.9
Gary Ablett 2002 34 11.7 5.9 1.9 5.8 4.1 1.0 1.9 8.1 66.2 1.7


 
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