The latest Ranking on Dashboard metrics data appears below, and now shows that the strongest rank correlations with ladder positions are currently associated with:

• Percentage of Quarters Won (+0.95)

• The MoS Win Production Function (+0.88)

• Q4 Performances (+0.85)

• Own Scoring: Goals (+0.79)

• Scoring Shots Conceded (+0.79)

• Own Scoring: Points (+0.78)

• Q1 Performances (+0.75)

• Opponent Scoring: Points (+0.75)

• Scoring Shots Registered (+0.72)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.36)

• Own Scoring Shot Conversion (+0.40)

• Q2 Performances (+0.49)

The latest Ranking on Dashboard metrics data appears below, and now shows that the strongest rank correlations with ladder positions are currently associated with:

• Percentage of Quarters Won (+0.91)

• The MoS Win Production Function (+0.89)

• Scoring Shots Conceded (+0.78)

• Q4 Performances (+0.72)

• Q3 Performances (+0.71)

• Opponent Scoring: Points (+0.71)

The latest Ranking on Dashboard metrics data appears below, and, again, uses the Match Ratio metric to adjust for the fact that not all teams have yet had their bye.

The strongest rank correlations with those ladder positions are currently associated with:

• The MoS Win Production Function and Percentage of Quarters Won (+0.90)

• Opponent Scoring: Points (+0.78)

• Q1 Performances (+0.85)

• Scoring Shots Conceded (+0.78)

• Q3 Performances (+0.74)

• Goals Conceded (+0.74)

• Q1 Performances (+0.72)

• Scoring Shots Generated (+0.72)

• Q4 Performances (+0.71)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.30)

• Own Scoring Shot Conversion (+0.37)

• Q2 Performances (+0.42)

Winning and losing at the moment is more about scoring shot generation than it is about the average quality of the shots generated.

The latest Ranking on Dashboard metrics data appears below, and, again, uses the Match Ratio metric to adjust for the fact that not all teams have yet had their bye.

The strongest rank correlations with those ladder positions are currently associated with:

• Percentage of Quarters Won (+0.96)

• The MoS Win Production Function (+0.9)

• Q1 Performances (+0.85)

• Scoring Shots Conceded (+0.77)

• Own Scoring: Points (+0.76)

• Q4 Performances (+0.76)

• Own Scoring: Goals (+0.75)

• Opponent Scoring: Points (+0.73)

• Scoring Shots Generated (+0.73)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.3)

• Q2 Performances (+0.47)

The latest Ranking on Dashboard metrics data appears below, and uses the Match Ratio metric to adjust for the fact that four teams had byes this week.

Collingwood and Melbourne have the most impressive set of numbers, with the former ranked no lower than 5th except for Q3 Performances, and the latter ranked no lower than 5th except for Q3 Performances and Opponent Scoring Shot Conversion. Melbourne, in fact, are the only team in the Top 8 not to be ranked 12th or lower for at least one of the metrics.

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• Percentage of Quarters Won (+0.96)

• The MoS Win Production Function (+0.9)

• Scoring Shots Conceded (+0.83)

• Q4 Performances (+0.83)

• Own Scoring: Points (+0.8)

• Scoring Shots Generated (+0.78)

• Own Scoring: Goals (+0.76)

• Opponent Scoring: Points (+0.75)

• Q3 Performances (+0.74)

• Q1 Performances (+0.72)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.18)

• Q2 Performances (+0.44)

It’s notable, I think, that every team currently in the Top 8 is ranked 10th or worse on at least one metric, and six of them are ranked 12th or worse on at least one metric, the exceptions in the latter case being Collingwood and Melbourne.

Notable as well is the fact that the teams in 9th to 15th on the ladder are all ranked in the Top 5 on at least one metric.

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• The MoS Win Production Function (+0.95)

• Percentage of Quarters Won (+0.93)

• Scoring Shots Conceded (+0.9)

• Opponent Scoring: Points (+0.8)

• Scoring Shots Generated (+0.8)

• Own Scoring: Goals (+0.77)

• Q4 Performances (+0.76)

• Opponent Scoring: Goals (+0.75)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.15)

• Own Scoring Shot Conversion (+0.49)

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• Percentage of Quarters Won (+0.96)

• The MoS Win Production Function (+0.94)

• Scoring Shots Conceded (+0.93)

• Opponent Scoring: Points (+0.84)

• Opponent Scoring: Goals (+0.71)

• Own Scoring: Goals (+0.76)

• Own Scoring per Game (+0.73)

• Q2 Performances (+0.72)

• Own Scoring: Points (+0.71)

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• Percentage of Quarters Won (+0.94)

• Scoring Shots Conceded (+0.91)

• The MoS Win Production Function (+0.91)

• Opponent Scoring: Points (+0.79)

• Own Scoring: Points (+0.73)

• Own Scoring: Goals (+0.73)

• Q4 Performances (+0.73)

• Own Scoring per Game (+0.71)

• Opponent Scoring: Goals (+0.71)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.1)

• Q1 Performances (+0.51)

At this stage, Port Adelaide looks perhaps the most out of place as a Top 8 team, based solely on their scoring metrics, and Essendon looks perhaps the most out of place as a team outside the Top 8.

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• The MoS Win Production Function (+0.91)

• Scoring Shots Conceded (+0.89)

• Percentage of Quarters Won (+0.79)

• Opponent Scoring: Points (+0.74)

• Own Scoring: Goals (+0.77)

• Own Scoring: Points (+0.75)

• Q4 Performances (+0.74)

• Opponent Scoring: Goals (+0.73)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.1)

• Q1 Performances (+0.41)

At this stage, Port Adelaide looks perhaps the most out of place as a Top 8 team, based solely on their scoring metrics, and Sydney looks perhaps the most out of place as a team outside the Top 8.

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• The MoS Win Production Function (+0.89)

• Percentage of Quarters Won (+0.88)

• Q4 Performances (+0.81)

• Scoring Shots Conceded (+0.8)

• Opponent Scoring: Points (+0.74)

• Own Scoring: Goals (+0.72)

• Own Scoring: Points (+0.71)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (-0.04)

• Q1 Performances (+0.35)

Remarkably the ladder’s Top 8 teams includes the four worst teams on Opponent Scoring Shot Conversion.

Overall, the teams whose scoring statistics look least congruous with their ladder positions are Geelong, who the Win Production Function places 2nd, and who are in the Top 4 on a slew of other measures, and Richmond, who the Win Production Function places 11th.

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• The MoS Win Production Function (+0.85)

• Percentage of Quarters Won (+0.84)

• Opponent Scoring: Points (+0.76)

• Scoring Shots Conceded (+0.75)

• Q4 Performances (+0.73)

• Own Scoring: Points (+0.70)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.11)

• Q1 Performances (+0.31)

Carlton also remain Top 4 on the ladder despite bring ranked 10th on Scoring Shots, 11th on Scoring Shots Conceded, 12th on Q3 and Q4 Performances, 13th on Point and Goal Scoring, and 14th on Scoring Shot Conversion and Q1 Performances. It’s really Q2s and defence that has seen them climb to where they are.

The latest Ranking on Dashboard metrics data appears below, and shows that the strongest rank correlations with ladder position are associated with:

• The MoS Win Production Function (+0.84)

• Percentage of Quarters Won (+0.84)

• Own Scoring: Goals (+0.73) and Behinds (+0.71)

• Scoring Shots Conceded (+0.69) and Points Conceded (+0.68)

• Q3 Performances (+0.66)

The weakest rank correlations with ladder position are associated with:

• Opponent Scoring Shot Conversion (+0.21)

• Q1 Performances (+0.44)

The latest Ranking on Dashboard metrics data appears below, and shows that, at this point in the season, defence has been more important than offence.

We have:

• The rank correlation between Ladder Position and Conceded Scoring Shots per Game is +0.78, while that between Ladder Position and Recorded Scoring Shots per Game is just +0.32

• The rank correlation between Ladder Position and Conceded Points per Game is +0.78, while that between Ladder Position and Recorded Points per Game is just +0.59

The MoS Win Production Function continues to provide a good fit with Ladder Position. The rank correlation between the two now stands at +0.93.

It’s still far too early to be making much of the Ranking on Dashboard metrics data, which appears below, but it is interesting to note that:

• Three of the teams in the Top 8 of the Competition Ladder are in the bottom 8 on scoring

• Ladder position is positively rank-correlated with every metric on the Dashboard, but especially with the rankings on MoS Win Production, Quarters won, and points concession

It’s early days, so we’ll not be attempting to draw any insights from the data this week.

The final Ranking on Dashboard Metrics data for season 2022 appears below, and shows that the metrics most associated with success this season were:

• Percentage of Quarters Won

• MoS Expected Wins using the Win Production Function

• Opponent Scoring Shots per Game

• Points Conceded per Game

• Goals Conceded per Game

• Performance in Q1s and Q3s

• Own Scoring Shots per Game

The metrics least associated with success were:

• Own Scoring Shot Conversion

• Opponent Scoring Shot Conversion

• Performance in Q2s

Sydney finish as the team with the highest worst ranking on any metric (9th) and Collingwood and Western Bulldogs, amongst the Top 8 teams, as the teams with the lowest best ranking on any metric (5th).

The Ranking on Dashboard Metrics data appears below and shows that the two metrics most highly-correlated with ladder position are MoS Win Production Function Expected Wins, and Quarters Won.

Those metrics align particularly well for the teams that are currently in Finals positions, with the exceptions of Collingwood, whose scoring statistics rank them only 10th, despite their 5th-placed position and, to a lesser extent, Carlton, who rank only 10th on Quarters won. On that metric in particular, the Western Bulldogs might well be expected to have a place in the Top 8 on the ladder.

On that Win Production Function metric, every team has won plus or minus 2 games relative to expectation except Collingwood (+3.9 wins), and Port Adelaide (-2.9 wins).

The Ranking on Dashboard Metrics data appears below and still shows that there is still no team that can claim to be in the Top 10 on every metric.

That’s true even for the teams currently in the Top 8 on the competition ladder where we have:

• Geelong: 15th on Opponent Scoring Shot Conversion and on Own Scoring Shot Conversion

• Collingwood: 16th on Opponent Scoring Shot Conversion, 11th on Goals Conceded, and 12th on Q2 Performances

• Melbourne: 16th on Own Scoring Shot Conversion

• Sydney: 12th on Own Scoring Shot Conversion 10th on Q1 Performances, and 11th on Q2 Performances

• Brisbane Lions: 10th on Q2 Performances

• Fremantle: 13th on Own Scoring Shots per Game, 13th on Own Scoring Shot Conversion, 11th on Goals Scored per Game, 12th on and on Points Scored per Game, 14th on Q2 Performances, and 10th on Q3 and Q4 Performances.

• Carlton: 11th on Own Scoring Shot Conversion, 13th on Q3 Performances, and 12th on Q4 Performances

• Richmond: 12th on Scoring Shots Conceded per Game, and 10th on Points Conceded per Game

Scoring Shot Conversion - Own and Opponents’ - continues to be largely irrelevant this season.

The Ranking on Dashboard Metrics data appears below and still shows that there is no team that can claim to be in the Top 10 on every metric.

That’s true even for the teams currently in the Top 8 on the competition ladder where we have:

• Geelong: 14th on Opponent Scoring Shot Conversion and 17th on Own Scoring Shot Conversion

• Melbourne: 16th on Own Scoring Shot Conversion

• Collingwood: 16th on Opponent Scoring Shot Conversion, and 11th on Win Production Function Expected Wins

• Sydney: 11th on Q1 Performances, and 12th on Q2 Performances

• Brisbane Lions: 11th on Q2 Performances

• Fremantle: 12th on Own Scoring Shot Conversion, 13th on Goals and on Points Scored per Game, and 14th on Own Scoring Shots per Game and Q2 Performances

• Carlton: 11th on Own Scoring Shot Conversion, 12th on Q3 Performances, and 14th on Q4 Performances

• St Kilda: 12th on Goals and on Points Scored per Game, 12th on Q1 Performances, and 13th on Own Scoring Shots per Game and Own Scoring Shot Conversion