What is the formula for price changes?

[HintT]

Using this formula, I got Clark having a $59k drop from $498,100 to 439,100.  ???

Also Brett Stanton who's average is now 1 less (101) than his break even (102) would go up in price by $9,470  ???

So is this right? Also the formula is it definitely right ?  ???

Thanks

[walesy]

Holla, yeah, next round is the price movement that will occur if they get their average.

Movement (3 rounds) is the total movement that will occur over three rounds.

If you click on the "extend" button, you'll get the exact details of those 2nd and 3rd rounds.

Alternatively, if you click on the little calculator next to a players name, you can plug in your own numbers and see what you come up with. :)

cheers.

[Sams-Town]

Thanks for that Walesy much appreciated mate

[wish for hope]

when do price changes happen again? in another 3 week or next week ect.

[browny_wce]

they act on a 3 week scoring rolling avg
but they will change again next week by avging r2, r3, r4 etc.

[Samm79]

Anyone cracked the formula for calculating price changes? The excel formula

=(((((last 3 round ave.)/3)*4956)-current price)*3/11)+current price

is close but not accurate. Any ideas?

[Prospector_1]

The 4956 may have changed - work a few examples backwards.

[Samm79]

Thank you prospector, can you confirm whether the rest of the formula is correct?

[Prospector_1]

Recent_Market_Value = F * Average_Points_In_Last_Three_Games

New_Price = 3/4 * Old_Price + 1/4 * Recent_Market_Value

In layman's terms what this formula does is move the player's price one-quarter of the way from where it was towards where it should be based on their recent form. Recent form is only calculated on three weeks' worth of points, and the price is only changed if the player actually scored on the weekend (and has played at least three games).

F is around 5000. Exact value you can get by working backwards.

Formula is probably not exact, but close enough for most purposes.

[Samm79]

Thanks again Prospector!

[wish for hope]

so they will change from now on everyweek if they have already played 3 games?

[Prospector_1]

every week that they play

[Tyrogue]

I ran the forumla for Ablett. According to the formula, his price should have only droppe $2k+, not $16,500.  ???

[Prospector_1]

This article pretty much hits the nail right on the its head, source: http://www.superroach.net/
Quote THE BIG SCORE - SUPERCOACH SCORING SYSTEM FINALLY EXPLAINED!
While complicated, basically the scoring system is not as transparent as we would like it to be. In the Supercoach game there is not a list we can read off to calculate our players scores e.g, 1 kick = 1 point, 1 contested mark = 6 points, because the Supercoach scores are entirely based on your players influence within the game and the context of the possessions. Yes their scores do depend on the amount of possessions they get and there is a scoring system which stipulates how many points each player gets for a different action they have in the game, but it is not black and white and as I previously mentioned, depend heavily on where the possessions were and what part of the game the possession took place.

On top of this and probably the most controversial aspect of the Supercoach scoring system is the 3300 point factor. This means that Champion data will ONLY allocate 3300 points to any one game of AFL football. This means that in a weekend of football, there is only ever 26,400 points available for your Supercoach team to attain, no more no less. I know there will be plenty of discussions and implications for this (see Roachs Forum for SUPERCOACH SCORING SYSTEM discussion) so I have included an explanation from Champion Data themselves to help clarify the situation.

Champion Data Rankings: how come every match adds up to 3,300 points?

Before 2004 we simply allocated a set number of points for each statistic, something like the Dream Team formula but with qualitative stats, such as effective kicks (+4), ineffective kicks (0) and clanger kicks (-6). Those base points had been refined through research by Swinburne University on the most important factors in winning a game of football. Over the years we have continued to test them and made minor tweaks and additions as the game evolves and we collect more information about each match.

From 2004 we decided to take situational information into account. The research shows that you win more matches by making quality decisions near goal, and when the match is in the balance. For each action in the match, the computer uses a multiplier which involves the position on the field and a pressure factor based on the margin and the time left. The pressure factor is basically the effect a player can have on his teams winning chances by doing the right thing at that time  a game-winning goal is given the highest multiplier, while a handball on the wing when his team is already 80 points ahead gets scaled down.

Once all the numbers are in, we normalise them so that the total is 3,300. Each player is given a slice of the pie, in proportion to his total weighted ranking points. This lets us measure a players contribution to a match regardless of its speed or overall quality. For SuperCoach it means that Sydney players are worth considering on a level playing field with Bulldogs, even though there are fewer possessions in their matches. It also means that there is no inflation as the game continues to speed up, and a players 150 today is as dominant of a total match as 150 was five years ago regardless of game styles and trends.

• Where does 3,300 come from?
The average match from 2001 to 2003 had about 3,300 points. If we looked at raw base numbers these days, they would have gradually increased just like Dream Team points.

• Not adding up to exactly 3,300?
Rounding can vary this.

• Whats an average score?
3,300 / 44 = 75, so 100+ indicates a good game. 150 means hes done the job of two average players.

• Someone had 50 points at half time and didnt come back on the field. How did he finish with only 40? Or 60?
The normalisation has the effect of concentrating points around the times when the result was decided as one team took control. At half time the computer assumes 1,650 points have been allocated. But if one team has already run away with the match, points from the first half will continue to scale up as a proportion of the pie. Conversely if the match is won very late, points from earlier are scaled down.[/]

[Prospector_1]

Awesome article from the 2008 Prospectus, clears up pretty much anything you need to know about the SC scoring system:

Quote The Official Player Ranking points are a formula designed to measure the quality of a player’s statistics rather than just the quantity. Each year the rankings formula is reviewed by Champion Data’s statisticians and is ‘tweaked’ according to changes in the games. The 2007 season saw an example of this as Champion Data started recording run-down tackles. These were scored high than regular tackles as it involved a player putting in extra effort to apply a tackle after a hard chase.

Explanation of Rankings and the Current Formula:
Champion Data’s Rankings formula is based on the official AFL statistics and is calculated by computer. From 1999-2003, Champion Data together with Swinburne University conducted extensive research (covering 1110 games in total) identifying winning and losing factors in AFL games. Findings from the research tell us that effective kicking along with a side’s ability to win the disputed ball are two of the most important winning factors in the AFL. Our rankings formula is geared towards rewarding these statistics with higher values as well as assigning negative points to stats that are detrimental to a side’s winning chances (ie. clangers and ineffective disposals).

There are 57 individual statistics to which the computer attributes either a positive or negative value. For example, an effective kick is worth four points and an effective handball is worth two points but an ineffective disposal is worth zero points. With research continually conducted on the data gathered by our statisticians, new statistics have been defined and existing values have continually been refined over the years to reflect the changing nature of game plans. Even with the evolution of our great game we know that winning the contested ball and using disposals effectively are still two major keys to victory.

Many statistics are valued higher depending on the state of play in which they occur. Perhaps the most common example of this is an uncontested mark. Over the last few years we have seen a lot more ‘junk’ football being played, with sides kicking the ball sideways and backwards more often than ever before. Therefore grabbing an uncontested mark from a teammate’s kick has become more common than ever and is valued at just one point. Grabbing an uncontested mark from an opposition’s kick requires much greater skill in reading the play however, and is given a value of four points. This principle also applies to a contested mark as they are valued at six points when taken from a teammate’s kick and eight points from an opposition kick.

In 2005, the rankings formula introduced weighting to its values depending on the proximity to goal and the state of play in which the stat occurred. For instance, it is clear that turning the ball over in your own defensive 50 has a much more detrimental effect than turning it over in the forward-line and the rankings values reflect this. The values are designed to reward players that stand up and dominate when the game is up for grabs rather than those that rack them up when the margin is greater and the result of the game is out of reach. Mathematically this state-of-play weighting is based on the derivative of match-winning probability with respect to a score change. The total rankings value for one side in a single match has been normalised to be 3300- so sides with a game plan involving a slower tempo and fewer disposals (think Sydney) are not condemned to a lower score than the side that love to rack up the disposals and create free-flowering games.

Rankings points are not only assigned live during the match but are re-adjusted at the completion of the match with the computer weighting scores depending on the most important time of the match or when the match was won. For example, a player may have a score of 50 points at quarter time with his side leading by 20 points at the first break. If that player’s side loses the match by one point after being outscored by five goals in the last quarter then more weighting will be given to statistics in the last quarter (where the game was ultimately won) rather than the first quarter, which will be geared down at the completion of the match. So that same player might end the day with only 40 points in the first quarter. This system also works in the reverse, so for example if one team out-scores the other by four goals in the first quarter and runs away with the game in the next three quarters, the ranking points from the first quarter will be geared higher at the completion of the match for the winning side.