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Harvard Believes Chiefs Will Make the Playoffs


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According to this article by Kurt Bullard of the Harvard Sports Analysis Collective, the Kansas City Chiefs have a 66 percent chance of making the playoffs in 2015.


Here's a brief synopsis from that article on how these numbers came to happen.


I converted the aggregated AV for each team into an ELO rating so that I could later use that value to calculate the win probability of each team in each game this season. With the mean ELO rating set at 1500, I set the possible range of ELO values between 1320-1900, since the standard deviation of ELO ratings has traditionally been 90 points.


But ELO ratings don’t paint the whole picture, as teams who finish with worse records the previous year tend to benefit from easier schedules.  I therefore ran a Monte Carlo simulation of each team’s season, calculating win probabilities based on the ELO ratings using the following formula: 1/(10^(Opponent ELO – ELO)/400) 1).  Using Benjamin Morris’ conversion table from wins to playoff odds, I then calculated the odds that a team would make the playoffs for the upcoming year.  I then normalized it so an average of 12 teams would make the playoffs every year.


Now do you understand?


Me either, but any analysis coming from a place like Harvard predicting good things for the Chiefs is alright by me.


Per this article, the Denver Broncos have a 62 percent chance, the Chargers are at 33 and the Raiders come in with an NFL-low 1 percent chance of making the playoffs in 2015.


Hard to argue with the minds at Harvard, which just made some friends in Chiefs Kingdom.


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I converted the aggregated AV for each team into an ELO rating so that I could later use that value to calculate the win probability of each team in each game this season. With the mean ELO rating set at 1500, I set the possible range of ELO values between 1320-1900, since the standard deviation of ELO ratings has traditionally been 90 points.

But ELO ratings don’t paint the whole picture, as teams who finish with worse records the previous year tend to benefit from easier schedules.  I therefore ran a Monte Carlo simulation of each team’s season, calculating win probabilities based on the ELO ratings using the following formula: 1/(10^(Opponent ELO – ELO)/400) 1).  Using Benjamin Morris’ conversion table from wins to playoff odds, I then calculated the odds that a team would make the playoffs for the upcoming year.  I then normalized it so an average of 12 teams would make the playoffs every year.

 

Well Hell.., There ya go.., :lol:

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I converted the aggregated AV for each team into an ELO rating so that I could later use that value to calculate the win probability of each team in each game this season. With the mean ELO rating set at 1500, I set the possible range of ELO values between 1320-1900, since the standard deviation of ELO ratings has traditionally been 90 points.

But ELO ratings don’t paint the whole picture, as teams who finish with worse records the previous year tend to benefit from easier schedules.  I therefore ran a Monte Carlo simulation of each team’s season, calculating win probabilities based on the ELO ratings using the following formula: 1/(10^(Opponent ELO – ELO)/400) 1).  Using Benjamin Morris’ conversion table from wins to playoff odds, I then calculated the odds that a team would make the playoffs for the upcoming year.  I then normalized it so an average of 12 teams would make the playoffs every year.

 

Well Hell.., There ya go.., :lol:

 

Simple formulas hehe

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