MAFL 2010 : Round 6

It's as if someone flicked a switch, which in a fashion someone did.

All six Funds have taken up their option to participate in the weekend's wagering, many of them with an alacrity that can only be exhibited by something inanimate that has no sense of the terror that can be induced by a large wager on a team at $1.01.

Cherishing Inconsistency Where It's Welcome

In an earlier blog we demonstrated the benefits of consistency in football - moderate benefits if the consistency came in the form of generating scoring shots with less variability than teams of otherwise similar ability, and significant benefits if it came in the form of converting more of those opportunities into goals.

Indeed, consistency's a characteristic that sports commentators reserve for their warmest - and often longest - soliloquys, and players and teams, once they've reached an acceptable level of performance, announce as though scripted that they're now "striving for consistency". So, surely, consistency is always a good thing, isn't it?

MAFL 2010 : Round 5 Results

That was a weekend that could easily the unwary into thinking there's something in this statistical modelling stuff.

Six wins from seven bets, with two of the wins coming from seriously unfancied teams, lifted the Heuristic Fund by almost 30% and left it up almost 41% on the season. Investors with the Recommended Portfolio are now, therefore, up over 4% on the season.

Modelling AFL Team Scoring : Part III

This is the third in a series of blogs (here are Part I and Part II) about modelling the scoring of AFL teams and, with the heavy statistical lifting out of the way, in this blog we can look at the practical uses of what we've discovered so far, which is that:

(1) Team scoring can be modelled by the Score Equation

Score = Number of Scoring Shots x Conversion Rate x 6 + Number of Scoring Shots x (1 - Conversion Rate)

(2) A team's number of scoring shots can be modelled by a lognormal distribution with mean determined by the team's strength relative to its opponent and by whether or not the match is a home game for either team, and with a standard deviation of 5.5 scoring shots.

(3) Teams will convert the scoring shots they produce into goals as if drawing from a binomial distribution. The average team will convert 53.64% of its scoring shots into goals.

Modelling AFL Team Scoring : Part II

This is the second in a series of blogs about modelling the scoring of AFL teams.

In the previous blog on this topic I introduced what I called the Score Equation, which represents a way of thinking about a team's score in any game, and is as follows:

Score = Number of Scoring Shots x Conversion Rate x 6 + Number of Scoring Shots x (1 - Conversion Rate)

Then I used empirical data for seasons 2006 to 2009 to show that the bookmakers' starting prices could be used to predict with reasonable accuracy the number of scoring shots that a team will produce in a given game, and that teams, regardless of the number of scoring shots they produce, generally convert about 53.64% of them.

Modelling AFL Team Scoring

Today's blog is the first in a series that will look at statistically modelling the scoring behaviour of teams in the AFL.

If you're profoundly reductionist about it, you can think about a team's footy score as being the product of the number of scoring shots it creates and the proportion of those scoring shots that it converts into goals.

MAFL 2010 : Round 5

Well I did expect the level of wagering activity to ratchet up this weekend compared to last, but I thought Hope would be contributing to at least some of that increase.

That's not the case though. Hope has reviewed the market offerings and decided to return to slumber for at least another week; Shadow has looked at the same market and taken out its metaphorical knife and fork, rediscovering its Round 3-style appetite for the punt.

MAFL 2010 : Round 4 Results

What a pleasant weekend's wagering that was.

On Saturday, Collingwood looked comfortable from the off and eventually annihilated the Hawks by 64 points, and then on Sunday St Kilda teased us long enough to let us feel that we earned our payoff having trailed by a point at quarter time, drawn level by half-time, led by a point at three-quarter time before running out 15-point winners. Two bets, two wins, the Heuristic Fund up another 4.3%, and the Recommended Portfolio now up 1.13% on the season. All of this with the prospect of the Hope Fund commencing trading in the coming round.

MAFL 2010 : Round 4

If last weekend was the SSO in the Opera House this weekend is an acapella duo down the local pub.

We've just two bets and they're both priced at under $1.60. One wager is on the Pies, who face Hawthorn on Saturday, and the other is on the Saints, who take on Fremantle on Sunday.

Goalkicking Accuracy Across The Seasons

Last weekend's goal-kicking was strikingly poor, as I commented in the previous blog, and this led me to wonder about the trends in kicking accuracy across football history.

Just about every sport I can think of has seen significant improvements in the techniques of those playing and this has generally led to improved performance. If that applies to football then we could reasonably expect to see higher levels of accuracy across time.

MAFL 2010 : Round 3 Results

Well that was quite a Sunday.

Investors awoke on Sunday morning with the weekend's profitability hinging on an improbable victory by the Dees against the Crows, which then had to be followed by an almost equally unlikely win by the Dockers against the Cats. In the end, Investors got both results, with a victory by the Dogs providing the proverbial marzipan on the sweet, baked, traditionally tea-accompanying confection.

Coins : The Epilogue

Two previous blogs have been devoted to determining the optimal set of coin denominations that would allow one to produce any amount between 5-cents and 95-cents using, on average, the smallest number of coins. So far, we've solved the 2-coin, 3-coin and 4-coin variants of this problem and I flagged, in the most recent blog on the topic, the difficulty I suspected I'd encounter in trying to find solutions for more coins.

MAFL 2010 : Round 3

This week the Heuristic Fund will again be guided by the selections of the heuristic tipster named Shadow, a situation that will not persist into next week if Shadow's Round 3 tips are responsible for the Fund's third straight weekly loss.

Were Shadow hell-bent on retaining control of the Heuristic Fund - assuming, for the sake of the narrative, that it were sentient at all - it might have chosen to respond to this situation by wagering on a couple of short-priced favourites, hoping to eke out a small profit and in so doing earn the right to manage the Heuristic Fund for at least another 3 weeks.

As it happens, there's only one markedly short-priced favourite this weekend - Sydney at $1.10 facing Richmond - and Shadow has, indeed, thrown bread at the Swans ... but also at six other teams.

MAFL 2010 : Round 2 Results

If you didn't tip the round this weekend you've only yourself to blame. All eight winners were published in the online (and probably the print) version of Melbourne's Herald Sun late on Wednesday night as one of their forecaster's considered selections.

They were Jennifer Hawkins' tips.

It was that kind of round.

Scoring Shots: Not Just Another Statistic

For a while now I've harboured a suspicion that teams that trail at a quarter's end but that have had more scoring shots than their opponent have a better chance of winning than teams that trail by a similar amount but that have had fewer scoring shots than their opponent.

Suspicions that are amenable to trial by data have a Constitutional right to their day in court, so let me take you through the evidence.

We Still Don't Need No 37-cent Piece (And I'm Going Right Off The 10-cent Piece)

A few blogs back we asked and answered the question: if you were to select a set of four coin denominations on the basis that the selected four could combine to make any amount from 5-cents to 95-cents using, on average, the fewest number of them, what would those four denominations be?

There were, it turned out, nine such sets each of which was optimal and required only 2.11 coins, on average, to sum to any amount from 5-cents to 95-cents.

Well since we've solved the problem for 4-coin sets, what about solving it for 2-coin and 3-coin sets?