Welcome to Tigers: Jason Castagna | PUNT ROAD END | Richmond Tigers Forum
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Welcome to Tigers: Jason Castagna

127/134= 0.9 106/134= 0.79. Rounded up to 0.8 Try that for maths. So that’s why I said nearly 50/50.
Just out of dumb curiosity Willifred, but where does the 134 number come from???? Don't think that any players goal kicking accuracy figures have ever been judged regarding out on the full or kicks that fell short, or were rushed / knocked over the goal line.
Of 233 scoring shots, Georgie's managed to kick 127 goals and 106 behinds, that's not to shabby for a harassing pressure small forward and definitely not 50 / 50 accuracy.
As for your version of maths there .9 + .79 = 1.69 divided by 2 = .845 so your rounding down a long way to .8 not up to .8.
Even if you're counting his goals per game and his behinds per game, you're short changing him on his goals number, it should be .947 goals per game not just a flat .9.

Pull the finger out Willo, even a manky old year ten drop out from the early 70's can push a calculator button better than you :rotfl2 :rotfl2
 
2019 grand final is what I will always remember him for.
Took a great hanger, 6-7 marks, absolute live wire in the forward line. Kicked 0.5 and one out on the full.
 
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Castagna made our forward line very unpredictable, and therefore it was harder for defenders.

That unpredictability is something we really miss, our forward line has been way too predictable and with not enough separation for a few years. George would have been a big help in that regard.

DS
 
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An effort player was George gave his all and it burnt him out physically and mentally.

Infuriating at times and yet so very important in the 3 flags every Tiger fan knows what Chaos Costanza brough to the table.
 
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An effort player was George gave his all and it burnt him out physically and mentally.

Infuriating at times and yet so very important in the 3 flags every Tiger fan knows what Chaos Costanza brough to the table.
Yep. Too obvious he dropped after best mate Butts left.
 
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Castagna made our forward line very unpredictable, and therefore it was harder for defenders.

That unpredictability is something we really miss, our forward line has been way too predictable and with not enough separation for a few years. George would have been a big help in that regard.

DS
Mega predictable all over the ground this year. Injuries might have crippled Ouzo's plans to rejig our game style this year, but *smile* we've been absolutely rigid in how we transition the ball this year.
 
Just out of dumb curiosity Willifred, but where does the 134 number come from???? Don't think that any players goal kicking accuracy figures have ever been judged regarding out on the full or kicks that fell short, or were rushed / knocked over the goal line.
Of 233 scoring shots, Georgie's managed to kick 127 goals and 106 behinds, that's not to shabby for a harassing pressure small forward and definitely not 50 / 50 accuracy.
As for your version of maths there .9 + .79 = 1.69 divided by 2 = .845 so your rounding down a long way to .8 not up to .8.
Even if you're counting his goals per game and his behinds per game, you're short changing him on his goals number, it should be .947 goals per game not just a flat .9.

Pull the finger out Willo, even a manky old year ten drop out from the early 70's can push a calculator button better than you :rotfl2 :rotfl2
134 is the number of games he played.
So it’s the number of goals (127) divided by games played (134) gives the average goals per game 0.9 (rounded 0.947 to the closest whole number) . Same with the points (106) divided by games (134) gives the average points 0.79 (rounded to the closest whole number) 0.8
You always take the number to where it falls <> than .5
If it’s 8.4 it goes to 8 if it’s 8.7 it’s rounded up to 9.
So if it’s 7.9 = 8 if it’s 9.47 it goes to 9. Basic maths. Put the decimal point in.
That’s how I was taught to round up or down to the closest whole number and how to work the average over the games played.


So my version of maths says that on the data George kicked an average of 0.9 goals and 0.8 points. Hence nearly 50/50 average.
I hope that explains it clearly enough. A bit long winded for a simple exercise.

Georgie got the benefit because theres no data on missed, oof or sideways kicks ;) like all others.
 
If he had kicked straight would have been BOG.
Yeah and if Jack had kicked 12 he would have been bog.

Yes he did have a very good game, excellent in fact.
That is apart from his disposal. Which wasn’t unusual for George. But worked and ran all day long.
20 disposals, 11 effective. 6 turn overs, 6 marks, 10 SI, 0 goals, 5 points, 586 mg, 0 tackles, 0 1%ers , 3 bounces.
The usual mixed bag. The good, the bad, the ugly. With a sprinkle of very good thrown in for full measure.
 
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Nah 127 to 106 is 60:50 not 50:50
Sounds like data manipulation to suit what you want
 
So I brought JC back not to talk about kicking or chaos, but the football skill to impact a marking contest often outnumbered. George was elite.

We know how important this is.
The numbers are stark. We have a goal conversion 20%. We could improve this, focus on connection and better kicks. The best are 30%.
So for all our effort we gain 10%.

But moneyball is the 70%.
7 of every 10 inside 50s go back out and a possible oppo score.
At the very least we have to stop this 70% becoming scores. Maybe get a shot at goal.
Thats the Ridley Scrimshaw marks.

We talk about goals. 20 to 30‰ of forward time.
But the bigger question is 70‰.
It doesnt appear to be Cumbo. Who can it be?
 
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So I brought JC back not to talk about kicking or chaos, but the football skill to impact a marking contest often outnumbered. George was elite.

George also had one of the best tackling techniques I have seen at AFL level. Especially front on tackling, which a lot of players in the AFL struggle with. It is why Dusty is so effective with the stiff arm fend off.

In open play with an opponent looking to run at him, George had no AFL peer in being able to stick tackles. The AFLs answer to Trevor Gilmeister.
 
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So my version of maths says that on the data George kicked an average of 0.9 goals and 0.8 points. Hence nearly 50/50 average.
I hope that explains it clearly enough. A bit long winded for a simple exercise.
But your version of maths is unfortunately highly inaccurate in these days of Computers n decimal points that can go back forever. You're short changing Georgie of some very important career goals.
 
Yes. Too many focussed on his flaws rather than the incredible role he performed for the team. Heartbeat player. Letting Butts go was also a mistake.

They would both be making a difference now.

Butts literally couldn't get a game in the seniors and wanted a trade to a club where he'd get more game time.
 
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But your version of maths is unfortunately highly inaccurate in these days of Computers n decimal points that can go back forever. You're short changing Georgie of some very important career goals.
Well we’ll mark him up an extra 3 goals then or even 5 ;) even though on total he didn’t.
 
Nah 127 to 106 is 60:50 not 50:50
Sounds like data manipulation to suit what you want
Maybe like others learn to read my post.
I stated on average. That means goals and points divided by games played. That’s how you work out the average. I haven’t manipulated anything.
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Jason Castagna​

Last played for Richmond Tigers in 2022
Games: 134 Born: July 12, 1996 Origin: Northern Knights
Playing Height: 182cm Playing Weight: 82kg Position: Forward
Drafted: Round 2, Pick #29 2014 Rookie Draft by Richmond Tigers
Even FootyWire agrees with me. Refer to the bottom line of the chart below here it says “Career” columns 8 and 9 for goals and behinds. Satisfied?

Career Season Averages​
YearTeamGMKHDMGBTHOFFFAGAI50CLCGR50BL
2022​
16*​
6.2​
5.1​
11.3​
3.7​
0.8​
0.6​
2.1​
0​
0.4​
0.5​
0.4​
1.8​
0.1​
2.4​
0.4​
2021​
21*​
5.7​
6.0​
11.7​
4.0​
0.8​
0.6​
1.9​
0​
0.6​
0.1​
0.3​
1.5​
0.3​
1.3​
0.2​
2020​
21​
6.8​
4.6​
11.3​
3.4​
0.8​
0.6​
2.2​
0​
0.4​
0.4​
0.3​
2.2​
0.1​
1.7​
0.5​
2019​
24​
8.3​
6.4​
14.7​
4.1​
1.1​
1.2​
3.1​
0​
0.5​
0.6​
0.5​
2.9​
0.5​
2.2​
0.3​
0.10​
2018​
22​
5.8​
4.5​
10.3​
3.0​
1.2​
1.1​
2.9​
0.1​
0.8​
0.7​
0.6​
2.2​
0.4​
1.9​
0.1​
2017​
25​
6.0​
4.8​
10.8​
3.0​
1.0​
0.8​
3.0​
0​
0.8​
0.6​
0.4​
2.1​
0.5​
2.2​
0.2​
2016​
5​
8.0​
6.8​
14.8​
4.0​
0.4​
0​
1.6​
0​
0.4​
0.6​
0​
2.6​
1.4​
2.4​
1.6​
Career
134*​
6.6
5.3
11.9
3.5
0.9
0.8
2.6
0
0.6
0.5
0.4
2.2
0.4
2.0
0.3
 
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