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I've posted this a few times in here already, but it's definitely a flaw. It's just a statistical anomaly, there's no solid reasoning behind it.

Apart from the reasoning that maybe the better team generally finishes higher on the H&A ladder?
 
It's been a long time since I've tested a null hypothesis! I'm not sure I remember how to do that.

What do you want to compare it with? With nominal home ground advantage, which the squiggle uses, it's always clear who gets it. With geographic home ground advantage, not so much. You have situations like:
  • Hawthorn vs Fremantle in Tas
  • Hawthorn vs North in Tas
  • Melbourne vs Port in Darwin
  • St Kilda vs Richmond @ the MCG
  • Geelong vs Port Adelaide @ the MCG
  • Geelong vs North @ the MCG
  • West Coast vs Sydney @ the MCG
Tell me who gets home ground advantage (if anyone) in those situations and I can tell you how it does at tipping.

I was thinking specifically of the situation of Geelong vs Hawthorn (or any other MCG tenant for that matter) playing at the MCG, but I expect there's not enough data to get anywhere near significance.
 
I've posted this a few times in here already, but it's definitely a flaw. It's just a statistical anomaly, there's no solid reasoning behind it.
I'm not sure how much solid reasoning there is behind the idea of geographic home ground advantage, since it's not the 1980s any more with its highly variable suburban grounds. All the grounds are similar, even the ones we think of as huge or tiny:
d5b9qck0q7ix.png

Modern home ground advantage may be more a function of things like travel, crowd support, intangible psychological benefits and facilities.

In finals, there's also how the nominal home team finished higher on the ladder.
 
It's been a long time since I've tested a null hypothesis! I'm not sure I remember how to do that.

What do you want to compare it with? With nominal home ground advantage, which the squiggle uses, it's always clear who gets it. With geographic home ground advantage, not so much. You have situations like:
  • Hawthorn vs Fremantle in Tas
  • Hawthorn vs North in Tas
  • Melbourne vs Port in Darwin
  • St Kilda vs Richmond @ the MCG
  • Geelong vs Port Adelaide @ the MCG
  • Geelong vs North @ the MCG
  • West Coast vs Sydney @ the MCG
Tell me who gets home ground advantage (if anyone) in those situations and I can tell you how it does at tipping.

What if you give each team a "ground experience" score based on how many times and how recently they have played at each ground over the last 2-3 years? Alternatively or in addition you could give each team a score for each ground based on how they have performed in the past at the ground relative to a Squiggle algorithm with no home ground advantage. If you multiply those scores together you would have a pretty good indicator IMO.

I know that you and others value the simplicity of the Squiggle and this is getting a bit complex but that's how I'd attempt to do it quantitatively.
 

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I was thinking specifically of the situation of Geelong vs Hawthorn (or any other MCG tenant for that matter) playing at the MCG, but I expect there's not enough data to get anywhere near significance.
Here is what happens if you keep everything the same but reverse home ground advantage for those games where the nominal home team plays in the away team's state. (Geelong is still considered its own state.) So that's games sold by one team, e.g. Richmond playing Gold Coast in Cairns, and when Geelong had to play a Melbourne-based team at the MCG.

Code:
  1. ISTATE-91:12   : 2615 - 1197  68.599160546%  6.17/9  +/- 25.59pts +/- 36.99pts 579.033bits
  2. ISTATEV3-91:12 : 2594 - 1218  68.048268625%  6.12/9  +/- 25.53pts +/- 37.02pts 568.551bits

Similar results, but regular squiggle gets 21 more tips correct over 20 years, also winning two out of three measures of margin error.

The relevant games:

Code:
Processing 1997...
Reversed HGA of 12: R 4 1997: Geelong (85) vs Essendon (78) at M.C.G.
Reversed HGA of 12: R14 1997: Geelong (80) vs Collingwood (72) at M.C.G.
Reversed HGA of 12: R23 1997: Geelong (61) vs North Melbourne (79) at M.C.G.
Processing 1998...
Reversed HGA of 12: R11 1998: Geelong (80) vs Carlton (63) at M.C.G.
Reversed HGA of 12: R22 1998: Geelong (127) vs Essendon (117) at M.C.G.
Processing 1999...
Reversed HGA of 12: R 1 1999: Geelong (141) vs North Melbourne (135) at M.C.G.
Reversed HGA of 12: R19 1999: North Melbourne (111) vs Sydney (101) at S.C.G.
Reversed HGA of 12: R20 1999: Geelong (113) vs Carlton (104) at M.C.G.
Reversed HGA of 12: R24 1999: West Coast (70) vs Carlton (124) at M.C.G.
Processing 2000...
Reversed HGA of 12: R 5 2000: North Melbourne (128) vs Sydney (120) at S.C.G.
Reversed HGA of 12: R 8 2000: Geelong (77) vs Richmond (147) at Docklands
Reversed HGA of 12: R10 2000: Western Bulldogs (137) vs Sydney (79) at S.C.G.
Reversed HGA of 12: R11 2000: Geelong (87) vs Essendon (145) at Docklands
Reversed HGA of 12: R13 2000: Geelong (126) vs Western Bulldogs (119) at Docklands
Reversed HGA of 12: R19 2000: Geelong (85) vs North Melbourne (124) at Docklands
Reversed HGA of 12: R23 2000: Geelong (83) vs Hawthorn (92) at Docklands
Processing 2001...
Reversed HGA of 12: R 3 2001: North Melbourne (71) vs Sydney (151) at S.C.G.
Reversed HGA of 12: R 7 2001: Geelong (68) vs Carlton (108) at M.C.G.
Reversed HGA of 12: R 8 2001: Western Bulldogs (122) vs Sydney (101) at S.C.G.
Reversed HGA of 12: R11 2001: Geelong (93) vs Hawthorn (90) at Docklands
Reversed HGA of 12: R12 2001: Melbourne (99) vs Brisbane Lions (148) at Gabba
Reversed HGA of 12: R14 2001: Geelong (111) vs Collingwood (93) at Docklands
Reversed HGA of 12: R18 2001: Geelong (100) vs Melbourne (103) at M.C.G.
Processing 2002...
Reversed HGA of 12: R 1 2002: Geelong (76) vs Essendon (126) at M.C.G.
Reversed HGA of 12: R 8 2002: Western Bulldogs (159) vs Sydney (90) at S.C.G.
Reversed HGA of 12: R11 2002: Geelong (100) vs Carlton (96) at Docklands
Reversed HGA of 12: R14 2002: Melbourne (131) vs Brisbane Lions (110) at Gabba
Reversed HGA of 12: R19 2002: North Melbourne (97) vs Sydney (144) at S.C.G.
Reversed HGA of 12: R22 2002: Geelong (57) vs Hawthorn (75) at Docklands
Reversed HGA of 12: R24 2002: Adelaide (130) vs Melbourne (118) at M.C.G.
Processing 2003...
Reversed HGA of 12: R 9 2003: Geelong (109) vs Hawthorn (75) at Docklands
Reversed HGA of 12: R 9 2003: North Melbourne (84) vs Sydney (59) at Manuka Oval
Reversed HGA of 12: R10 2003: Melbourne (63) vs Brisbane Lions (123) at Gabba
Reversed HGA of 12: R11 2003: Geelong (115) vs Carlton (75) at Docklands
Reversed HGA of 12: R12 2003: Western Bulldogs (63) vs Sydney (127) at S.C.G.
Reversed HGA of 12: R18 2003: Geelong (73) vs Collingwood (97) at Docklands
Reversed HGA of 12: R26 2003: Brisbane Lions (134) vs Collingwood (84) at M.C.G.
Processing 2004...
Reversed HGA of 12: R 4 2004: Geelong (127) vs Richmond (78) at Docklands
Reversed HGA of 12: R 4 2004: North Melbourne (70) vs Sydney (121) at Manuka Oval
Reversed HGA of 12: R 9 2004: Geelong (120) vs Essendon (97) at Docklands
Reversed HGA of 12: R10 2004: Western Bulldogs (67) vs Sydney (93) at S.C.G.
Reversed HGA of 12: R10 2004: Melbourne (83) vs Brisbane Lions (123) at Gabba
Reversed HGA of 12: R17 2004: Geelong (131) vs Carlton (74) at Docklands
Reversed HGA of 12: R24 2004: Geelong (74) vs Essendon (64) at M.C.G.
Processing 2005...
Reversed HGA of 12: R 2 2005: North Melbourne (82) vs Sydney (59) at Manuka Oval
Reversed HGA of 12: R 4 2005: Geelong (131) vs Essendon (75) at Docklands
Reversed HGA of 12: R 7 2005: Geelong (119) vs St Kilda (101) at Docklands
Reversed HGA of 12: R 9 2005: Western Bulldogs (76) vs Sydney (89) at S.C.G.
Reversed HGA of 12: R14 2005: Melbourne (92) vs Brisbane Lions (166) at Gabba
Reversed HGA of 12: R14 2005: Geelong (113) vs Hawthorn (58) at Docklands
Reversed HGA of 12: R23 2005: Geelong (116) vs Melbourne (61) at M.C.G.
Processing 2006...
Reversed HGA of 12: R 7 2006: Hawthorn (66) vs Brisbane Lions (106) at Carrara
Reversed HGA of 12: R 8 2006: Western Bulldogs (90) vs Sydney (116) at S.C.G.
Reversed HGA of 12: R10 2006: North Melbourne (98) vs Sydney (105) at Manuka Oval
Reversed HGA of 12: R11 2006: Geelong (130) vs Essendon (88) at Docklands
Reversed HGA of 12: R14 2006: Melbourne (98) vs Brisbane Lions (90) at Gabba
Reversed HGA of 12: R16 2006: Geelong (90) vs Western Bulldogs (89) at Docklands
Reversed HGA of 12: R19 2006: Geelong (80) vs St Kilda (103) at Docklands
Processing 2007...
Reversed HGA of 12: R 2 2007: Geelong (162) vs Carlton (84) at Docklands
Reversed HGA of 12: R 4 2007: North Melbourne (87) vs Brisbane Lions (63) at Carrara
Reversed HGA of 12: R 9 2007: Western Bulldogs (57) vs Sydney (100) at Manuka Oval
Reversed HGA of 12: R15 2007: Geelong (80) vs Collingwood (64) at M.C.G.
Reversed HGA of 12: R15 2007: Melbourne (82) vs Brisbane Lions (126) at Gabba
Reversed HGA of 12: R16 2007: Geelong (138) vs Western Bulldogs (63) at Docklands
Reversed HGA of 12: R18 2007: Melbourne (64) vs Sydney (112) at Manuka Oval
Reversed HGA of 12: R23 2007: Geelong (156) vs North Melbourne (50) at M.C.G.
Reversed HGA of 12: R25 2007: Geelong (92) vs Collingwood (87) at M.C.G.
Processing 2008...
Reversed HGA of 12: R 2 2008: Geelong (150) vs Essendon (51) at Docklands
Reversed HGA of 12: R10 2008: Geelong (133) vs Carlton (77) at Docklands
Reversed HGA of 12: R13 2008: Melbourne (74) vs Sydney (114) at Manuka Oval
Reversed HGA of 12: R18 2008: Geelong (134) vs Richmond (71) at Docklands
Reversed HGA of 12: R18 2008: North Melbourne (92) vs Brisbane Lions (84) at Carrara
Reversed HGA of 12: R18 2008: Western Bulldogs (113) vs Sydney (97) at Manuka Oval
Reversed HGA of 12: R23 2008: Geelong (119) vs St Kilda (61) at M.C.G.
Reversed HGA of 12: R25 2008: Geelong (83) vs Western Bulldogs (54) at M.C.G.
Reversed HGA of 12: R26 2008: Geelong (89) vs Hawthorn (115) at M.C.G.
Processing 2009...
Reversed HGA of 12: R 3 2009: Geelong (122) vs Collingwood (95) at M.C.G.
Reversed HGA of 12: R 9 2009: Geelong (116) vs Western Bulldogs (114) at Docklands
Reversed HGA of 12: R10 2009: Western Bulldogs (117) vs Sydney (77) at Manuka Oval
Reversed HGA of 12: R17 2009: Geelong (99) vs Hawthorn (98) at M.C.G.
Reversed HGA of 12: R17 2009: Melbourne (50) vs Sydney (68) at Manuka Oval
Reversed HGA of 12: R23 2009: Geelong (96) vs Western Bulldogs (82) at M.C.G.
Reversed HGA of 12: R25 2009: Geelong (120) vs Collingwood (47) at M.C.G.
Processing 2010...
Reversed HGA of 12: R 1 2010: Geelong (125) vs Essendon (94) at M.C.G.
Reversed HGA of 12: R 8 2010: Western Bulldogs (101) vs Sydney (63) at Manuka Oval
Reversed HGA of 12: R15 2010: Geelong (85) vs Hawthorn (83) at M.C.G.
Reversed HGA of 12: R19 2010: Geelong (85) vs Collingwood (107) at M.C.G.
Reversed HGA of 12: R21 2010: Geelong (121) vs Carlton (79) at Docklands
Reversed HGA of 12: R23 2010: Geelong (79) vs St Kilda (83) at M.C.G.
Processing 2011...
Reversed HGA of 12: R 1 2011: Geelong (48) vs St Kilda (47) at M.C.G.
Reversed HGA of 12: R 7 2011: Western Bulldogs (65) vs Sydney (73) at Manuka Oval
Reversed HGA of 12: R 8 2011: Geelong (65) vs Collingwood (62) at M.C.G.
Reversed HGA of 12: R12 2011: Geelong (88) vs Hawthorn (83) at M.C.G.
Reversed HGA of 12: R17 2011: Richmond (70) vs Gold Coast (85) at Cazaly's Stadium
Reversed HGA of 12: R18 2011: Geelong (113) vs Richmond (51) at Docklands
Reversed HGA of 12: R25 2011: Geelong (98) vs Hawthorn (67) at M.C.G.
Processing 2012...
Reversed HGA of 12: R 2 2012: Geelong (92) vs Hawthorn (90) at M.C.G.
Reversed HGA of 12: R16 2012: Richmond (88) vs Gold Coast (90) at Cazaly's Stadium
Reversed HGA of 12: R16 2012: Geelong (79) vs Collingwood (110) at M.C.G.
Reversed HGA of 12: R17 2012: Geelong (134) vs Essendon (67) at Docklands
Reversed HGA of 12: R21 2012: Geelong (123) vs St Kilda (81) at Docklands
Processing 2013...
Reversed HGA of 12: R 2 2013: Geelong (112) vs North Melbourne (108) at Docklands
Reversed HGA of 12: R 3 2013: Geelong (119) vs Carlton (103) at Docklands
Reversed HGA of 12: R 7 2013: Geelong (113) vs Essendon (85) at Docklands
Reversed HGA of 12: R15 2013: Geelong (82) vs Hawthorn (72) at M.C.G.
Reversed HGA of 12: R16 2013: Richmond (53) vs Gold Coast (44) at Cazaly's Stadium
Processing 2014...
Reversed HGA of 12: R 5 2014: Geelong (106) vs Hawthorn (87) at M.C.G.
Reversed HGA of 12: R 7 2014: Geelong (81) vs Richmond (76) at M.C.G.
Reversed HGA of 12: R12 2014: Geelong (107) vs Carlton (102) at Docklands
Reversed HGA of 12: R15 2014: Geelong (89) vs Essendon (80) at Docklands
Reversed HGA of 12: R17 2014: Western Bulldogs (94) vs Gold Coast (66) at Cazaly's Stadium
Reversed HGA of 12: R25 2014: Geelong (92) vs North Melbourne (98) at M.C.G.
Processing 2015...
Reversed HGA of 12: R 8 2015: Geelong (140) vs Carlton (63) at Docklands
Reversed HGA of 12: R15 2015: Western Bulldogs (95) vs Gold Coast (73) at Cazaly's Stadium
Reversed HGA of 12: R20 2015: Geelong (85) vs Hawthorn (121) at M.C.G.
Reversed HGA of 12: R22 2015: Geelong (62) vs Collingwood (110) at M.C.G.
Processing 2016...
Reversed HGA of 12: R 1 2016: Geelong (116) vs Hawthorn (86) at M.C.G.
Reversed HGA of 12: R12 2016: Geelong (105) vs North Melbourne (74) at Docklands
Reversed HGA of 12: R17 2016: Western Bulldogs (107) vs Gold Coast (59) at Cazaly's Stadium
Reversed HGA of 12: R20 2016: Geelong (100) vs Essendon (34) at Docklands
 
What if you give each team a "ground experience" score based on how many times and how recently they have played at each ground over the last 2-3 years? Alternatively or in addition you could give each team a score for each ground based on how they have performed in the past at the ground relative to a Squiggle algorithm with no home ground advantage. If you multiply those scores together you would have a pretty good indicator IMO.

I know that you and others value the simplicity of the Squiggle and this is getting a bit complex but that's how I'd attempt to do it quantitatively.
The problem with venue-based algorithms is that most teams play most grounds very infrequently. There are only one or two data points per year for most teams at Subiaco, for example. So you have to either rely on a tiny sample or assume that years-old data is still relevant to today's performance.

That might work if venue made a huge difference to results, but that doesn't seem to be the case, so it's hard to identify in a small dataset.
 
The problem with venue-based algorithms is that most teams play most grounds very infrequently. There are only one or two data points per year for most teams at Subiaco, for example. So you have to either rely on a tiny sample or assume that years-old data is still relevant to today's performance.

That might work if venue made a huge difference to results, but that doesn't seem to be the case, so it's hard to identify in a small dataset.
This is why I suggested multiplying it by the "ground experience" score.

So for example for West Coast vs. Hawthorn at Domain:

West Coast have +15 ground score and 1.0 experience score = +15
Hawthorn have -5 ground score and 0.3 experience score = -1.5

West Coast vs. Hawthorn at MCG:

West Coast have -10 ground score and 0.5 experience score = -5
Hawthorn have +10 ground score and 1.0 experience score = +10
 
Here is what happens if you keep everything the same but reverse home ground advantage for those games where the nominal home team plays in the away team's state. (Geelong is still considered its own state.) So that's games sold by one team, e.g. Richmond playing Gold Coast in Cairns, and when Geelong had to play a Melbourne-based team at the MCG.

Code:
  1. ISTATE-91:12   : 2615 - 1197  68.599160546%  6.17/9  +/- 25.59pts +/- 36.99pts 579.033bits
  2. ISTATEV3-91:12 : 2594 - 1218  68.048268625%  6.12/9  +/- 25.53pts +/- 37.02pts 568.551bits

Similar results, but regular squiggle gets 21 more tips correct over 20 years, also winning two out of three measures of margin error.

Final Siren, you are the best person on the Internet.

That's 21 tips out of about 120 games - that sounds pretty significant, but I'll need to consult with my statistics expert (aka my wife) to work it out. (She's recommending a chi-squared test).
 
Final Siren, you are the best person on the Internet.

That's 21 tips out of about 120 games - that sounds pretty significant, but I'll need to consult with my statistics expert (aka my wife) to work it out. (She's recommending a chi-squared test).

I think its 21 tips over the last 20 years mate - so only 1 per season. It won't be a statistically significant difference I'd wager.
 
I think its 21 tips over the last 20 years mate - so only 1 per season. It won't be a statistically significant difference I'd wager.

You're looking at it the wrong way. The number of years is irrelevant.

The point is that if one algorithm tips 80 correct out of 120 games the other algorithm tips 60 correct. That's a big enough difference to me to suggest that it's more than chance.

If you saw that kind of 20pt difference after the first 5 rounds of your office tipping comp, would you put it down to luck?
 

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This is why I suggested multiplying it by the "ground experience" score.

So for example for West Coast vs. Hawthorn at Domain:

West Coast have +15 ground score and 1.0 experience score = +15
Hawthorn have -5 ground score and 0.3 experience score = -1.5

West Coast vs. Hawthorn at MCG:

West Coast have -10 ground score and 0.5 experience score = -5
Hawthorn have +10 ground score and 1.0 experience score = +10

i think that's getting a bit far removed from what the 'squiggle' is intended to be... that is, as few inputs as possible, and as little subjectivity as possible.
 
You're looking at it the wrong way. The number of years is irrelevant.

The point is that if one algorithm tips 80 correct out of 120 games the other algorithm tips 60 correct. That's a big enough difference to me to suggest that it's more than chance.

If you saw that kind of 20pt difference after the first 5 rounds of your office tipping comp, would you put it down to luck?

i think the poster before you is actually correct. it seems like the difference is 'regular squiggle' 2615 correct tips over 20 years; against 'tweaked squiggle' 2594 correct tips. or 68.6% vs 68.06% over 20 years, rounded up.
 
I second this.

Can I make a suggestion to everyone here? Please buy one of his books. For 2 reasons:

(1) Lexicon by Max Barry (aka Final Siren) is a cracking read - one of the best books I have read in years.

(2) By selling more books his publisher will advance/give him more money to write his next book. So he can be doing Squiggle stuff while he is telling his publisher that he is working on the novel :)
 
i think the poster before you is actually correct. it seems like the difference is 'regular squiggle' 2615 correct tips over 20 years; against 'tweaked squiggle' 2594 correct tips. or 68.6% vs 68.06% over 20 years, rounded up.
Yes, this is right! You can't simply take those reversed-home-game matches in isolation. Most of the time, both models tip the same way, but since they expect different margins, they react to the result a little differently, and that affects future tips.

So it quickly becomes very complicated and hard to follow. But if you want to go through the nitty-gritty, here is 2016 as an example.

There were four games this year where the team with nominal home game advantage played in the away team's state:

Code:
Processing 2016...
Reversed HGA of 12: R1 2016: Geelong (116) vs Hawthorn (86) at M.C.G.
Reversed HGA of 12: R12 2016: Geelong (105) vs North Melbourne (74) at Docklands
Reversed HGA of 12: R17 2016: Western Bulldogs (107) vs Gold Coast (59) at Cazaly's Stadium
Reversed HGA of 12: R20 2016: Geelong (100) vs Essendon (34) at Docklands

Only one of those games, R12 Cats vs Roos, involved teams rated closely enough that the home ground advantage changed the tip. For this game, regular squiggle got it right, because it gave the Cats home ground advantage even though it was at Docklands, whereas the model with "true" home game advantage gave it to the Roos, and got the tip wrong.

However, there were also three other games this year where the models tipped differently, because they involved teams that were rated differently due to results in previous games:

In Round 5, Geelong (107) defeated Port Adelaide (59) at Adelaide Oval. The regular squiggle got this wrong, but the "true" model had more highly rated the Cats' win over the Hawks in Round 1 (which was a Geelong home game at the MCG), so tipped them here.

In Round 12, Melbourne (104) defeated Collingwood (58) at the MCG. This was a very close tip where subtle ratings differences from previous matches tipped the balance: regular squiggle tipped Collingwood by 0.1 points (wrong) while the "true" HGA model tipped Melbourne by 0.5pts.

In Round 18, Gold Coast (105) defeated Fremantle (81) at Carrara. Regular squiggle got this right, while "true" HGA tipped Fremantle, mainly because of the Dogs vs Suns game the week before, where the regular squiggle gave the Suns more credit because it was a nominal away game.

So after all that, both versions have the same number of correct tips this year. Regular squiggle has slightly lower margin error.
 
Last edited:

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Yes, this is right! You can't simply take those reversed-home-game matches in isolation. Most of the time, both models tip the same way, but since they expect different margins, they react to the result a little differently, and that affects future tips.

Thanks for explaining that, FS. I stand corrected. Would still be interested to see if the difference is due to more than chance, but it will be harder to test.
 
Can I make a suggestion to everyone here? Please buy one of his books. For 2 reasons:

(1) Lexicon by Max Barry (aka Final Siren) is a cracking read - one of the best books I have read in years.

(2) By selling more books his publisher will advance/give him more money to write his next book. So he can be doing Squiggle stuff while he is telling his publisher that he is working on the novel :)

Looks very interesting - I'll pick that up before my next holiday.

Personally, I can't wait for "The Tangled Web We Weave: Great moments in squiggleology".
 
An excellent addition to Squiggles is adding a wooden spoon to the chart for each team thst ginished last in the lsst 20 years. Adds some excitement for those teams at the bottom of the ladder.
HNnslJT.jpg

Edit: Oops, GWS 2012 were off the chart. Added them in.
 
Last edited:

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