Using the great data and awesome articles provided by Peter at aflratings.com.au, we have put together a table that is easily sorted to show who averaged the most/least points both for and against.
Some interesting things to note is how dominant the Hawks were. Averaging over 1700 points is a massive effort. It was also a 52.7 improvement on last year and the next best team, West Coast, were 100 points per game behind. The Eagles and the Dockers were the only two teams to average over 1600 points per game.
Five times the Hawks and Dockers scored over 1800 points. North Melbourne, Melbourne, Carlton and Gold Coast didn’t manage to crack that figure during the season.
The Suns scored less than 1500 in 19 games. Carlton and Geelong were next worse with 15 and 10 times.
The most important thing to look at for most fantasy coaches is who restricts scoring or gives up a lot of points.
Richmond were the buzz team this year as the hardest team to score on. They averaged just 1448 points against for the season. Couple this with no teams scoring over 1800 and 17 times they held teams to less than 1500, there is a good reason why we wouldn’t make a captain against them.
Hawthorn, Port Adelaide and Sydney were also very restrictive. North Melbourne and West Coast also stopped quite a few teams combining for 1500.
On the flipside, points flowed freely against Gold Coast. Despite not letting teams score over 1500 on 10 occasions, the Eagles gave up the second most points on average this season. The Bulldogs, Blues and Pies gave up over 1600 points per match.
Sort the data below using the cells at the top of the table. Click on the team initials in order to read more about each team.
CLUB | PTS FOR AVE | GAMES >1800 FOR | GAMES <1500 FOR | PTS AGA AVE | GAMES >1800 AGA | GAMES <1500 AGA |
---|---|---|---|---|---|---|
ADE | 1564.3 | 2 | 8 | 1559.9 | 3 | 8 |
BL | 1497.1 | 1 | 7 | 1576.2 | 1 | 7 |
CAR | 1429.8 | 0 | 15 | 1602.0 | 2 | 7 |
COLL | 1583.6 | 1 | 8 | 1601.0 | 4 | 6 |
ESS | 1583.6 | 3 | 6 | 1569.3 | 2 | 8 |
FRE | 1601.5 | 5 | 8 | 1558.5 | 2 | 7 |
GEE | 1572.8 | 3 | 10 | 1568.6 | 1 | 7 |
GC | 1406.7 | 0 | 19 | 1685.0 | 4 | 1 |
GWS | 1561.2 | 1 | 9 | 1562.0 | 1 | 7 |
HAW | 1705.3 | 5 | 1 | 1495.9 | 1 | 11 |
MELB | 1469.2 | 0 | 7 | 1588.0 | 3 | 6 |
NM | 1542.7 | 0 | 8 | 1588.0 | 0 | 12 |
PA | 1584.2 | 1 | 4 | 1500.4 | 0 | 10 |
RICH | 1556.2 | 1 | 9 | 1448.0 | 0 | 17 |
STK | 1568.3 | 1 | 6 | 1578.6 | 3 | 6 |
SYD | 1559.3 | 3 | 2 | 1509.0 | 0 | 12 |
WC | 1605.5 | 3 | 5 | 1641.5 | 2 | 10 |
WB | 1571.0 | 1 | 7 | 1615.5 | 2 | 5 |
We will have more in depth fixture analysis over the pre-season and easy to access data during the season to help you make decisions for your fantasy teams. This will be especially important for those playing daily fantasy with Moneyball.
Thanks once again to Peter for his excellent research.
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