Saturday, 21 January 2012
Wednesday, 18 January 2012
Web is blacked out today to protest SOPA and PIPA
Many sites are blacked out today to protest SOPA and PIPA. You can learn about why SOPA and PIPA are such a bad idea and how to tell your representatives you are against it at the EFF.
Help stop bad legislation from censoring the internet, and plain old breaking the internet.
Help stop bad legislation from censoring the internet, and plain old breaking the internet.
Wednesday, 11 January 2012
Superbowl 46 Playoff Roster predicted winners after Wild Card week
Mostly the expected happened during NFL Wild Card week, HOU beat CIN, NO beat DET (but was interesting at the start), and NYG crushingly beat ATL. Less expected was DEN beat PIT in an extremely exciting game. This sets the outcomes for the RKB Fantasy Playoff roster predictions a little more firmly, though four of the teams haven't played yet.
Like previous years, we can still model the performance of the list of 52 roster using the current points scored and plugging in the average points/game from the season multiplied by the number of games the simulations says a given team will play. Add it up and compare to the other rosters to see which rosters make it to 1st or 2nd place, which is in the money. There are obvious problems with the model, since it uses averages and there can be a wide variation in the performance of a given player in a given game. But it points the way toward a prediction of the outcome.
Firstly, below is a plot of the outcomes of rosters in 1st and second place from 10,000 simulations of the rest of the games of the playoffs.
The sizes of the entire pies above represent the relative probability of the various matchups in the Superbowl. For the purposes of this model prediction the winner doesn't matter as much as the number of times a team plays. Each pie is then broken down into slices for each of the 1st and 2nd place result combinations. Light green pies are when I end in first place, dark green are when I end in 1st and 2nd place, and the lighter yellowish green are when a roster of mine ends in 2nd place. The orange and blue colors represent other rosters of interest, for my sister and brother-in-law respectively.
It is in my best interest that NE and GB meet in the Superbowl, and my roster somehow overcome the all GB and all NE rosters of some of my competitors, I think this is due to spreading the players across teams, and the hopefully luck addition of Arian Foster to the lineup. I can also be successful if NE plays SF and HOU plays GB, while NO vs. NE or BAL vs. GB might yield a first and SF vs, any three yield 2nd place finishes. Under no circumstances do I want to see NYG or DEN make it to the Superbowl.
I know who I need to root for this weekend, how about you?
Like previous years, we can still model the performance of the list of 52 roster using the current points scored and plugging in the average points/game from the season multiplied by the number of games the simulations says a given team will play. Add it up and compare to the other rosters to see which rosters make it to 1st or 2nd place, which is in the money. There are obvious problems with the model, since it uses averages and there can be a wide variation in the performance of a given player in a given game. But it points the way toward a prediction of the outcome.
Firstly, below is a plot of the outcomes of rosters in 1st and second place from 10,000 simulations of the rest of the games of the playoffs.
Each column represents the frequency of that given result. The numbers are the number of the roster. Green rosters have me in the money. The darker green rosters are results in which I actually come in 1st and second place! As it stands I have a 54% chance of being in the money (1st or 2nd), a 47% chance of being in 1st, a 20% chance of being in 2nd, and 13% chance of being in 1st and 2nd. Most of these centered around NE or GB making it to the Superbowl, with a little help from Arian Foster of HOU along the way.
We can take the bars above and break up the results by the final Superbowl team matchups. Thus we can determine which combos result in wins for me and which do not.
The sizes of the entire pies above represent the relative probability of the various matchups in the Superbowl. For the purposes of this model prediction the winner doesn't matter as much as the number of times a team plays. Each pie is then broken down into slices for each of the 1st and 2nd place result combinations. Light green pies are when I end in first place, dark green are when I end in 1st and 2nd place, and the lighter yellowish green are when a roster of mine ends in 2nd place. The orange and blue colors represent other rosters of interest, for my sister and brother-in-law respectively.
It is in my best interest that NE and GB meet in the Superbowl, and my roster somehow overcome the all GB and all NE rosters of some of my competitors, I think this is due to spreading the players across teams, and the hopefully luck addition of Arian Foster to the lineup. I can also be successful if NE plays SF and HOU plays GB, while NO vs. NE or BAL vs. GB might yield a first and SF vs, any three yield 2nd place finishes. Under no circumstances do I want to see NYG or DEN make it to the Superbowl.
I know who I need to root for this weekend, how about you?
Tuesday, 3 January 2012
Superbowl 46 simulations and predictions
It's time for playoff fantasy football again. Like previous years, using the data from this season I have simulated the playoff games and generated probabilities of the matchups for the Superbowl and the winners. It should come as no surprise that the most probable matchup, about 20% of the 100,000 simulations has Green Bay playing New England. The plot below shows the relative probability by size of bubble with the NFC team winning in blue and the AFC team winning in red.
Other NFC teams with a reasonable chance to be in the Superbowl are SF and NO. On the AFC side it is Baltimore, with perhaps Pittsburgh and Houston as also-rans.
The reason to do the simulation is to see how many games each team plays so that I can choose players who score many points per game and have many chances to do it. Below is a chart of the expected number of games played for each team. The best outcomes are when a team without a bye makes it to the Superbowl because then they play four games, in bright green. More likely is playing three games, in light green. Obviously I will avoid players on teams that only play one game, in red.
Next step is to pick players.
The reason to do the simulation is to see how many games each team plays so that I can choose players who score many points per game and have many chances to do it. Below is a chart of the expected number of games played for each team. The best outcomes are when a team without a bye makes it to the Superbowl because then they play four games, in bright green. More likely is playing three games, in light green. Obviously I will avoid players on teams that only play one game, in red.
Next step is to pick players.
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