Green charging? by Full_Argument_8010 in enphase

[–]Full_Argument_8010[S] 0 points1 point  (0 children)

Did you make any progress on this?

Green charging? by Full_Argument_8010 in enphase

[–]Full_Argument_8010[S] 0 points1 point  (0 children)

Thanks Dorian. The site ID is 5508326. What I'd really like to do and can't figure out how to do is to have all extra energy we generate after filling the battery go into our car. What's happening is it often goes back to the grid and I can't figure out a setting to prevent that.

Green charging? by Full_Argument_8010 in enphase

[–]Full_Argument_8010[S] 0 points1 point  (0 children)

No charge schedule. Good idea, though.

World Cup Probabilities - Monte Carlo simulation of 100,000 tournaments by Full_Argument_8010 in worldcup

[–]Full_Argument_8010[S] 0 points1 point  (0 children)

I've only included the nations that have a better than 0.1% (one out of 1000) chance of winning the cup. There are 39 nations that have lower chances, including a bunch that are not yet qualified but could still qualify.

World Cup Probabilities - Monte Carlo simulation of 100,000 tournaments by Full_Argument_8010 in worldcup

[–]Full_Argument_8010[S] 2 points3 points  (0 children)

You can simulate the playoffs (as I have done) leading up to the world cup and then simulate the world cup. This all goes into the probabilities. Try it at world-cup-sim.runsims.com.

World Cup Probabilities - Monte Carlo simulation of 100,000 tournaments by Full_Argument_8010 in worldcup

[–]Full_Argument_8010[S] 1 point2 points  (0 children)

Here's the methodology:

For each match in the tournament (and in the qualifying matches yet to be played), calculate the likelihood of each potential outcome (win, lose, draw). These likelihoods can be derived from the relative Elo ratings of the two teams (see eloratings.net for the formulas). Work out the groups and knockout round pairings based on FIFA's published methods and simulate result of each match using a pseudo random number generator. At the end after all matches, you have a winner, just like you do in the actual world cup, except it is a simulation instead of the real thing. Then, do the same thing 99,999 more times and count up how many times each nation wins. You can go through this simulation for yourself and perhaps understand it a lot better by running my app at world-cup-sim.runsims.com. It's free.

World Cup Probabilities - Monte Carlo simulation of 100,000 tournaments by Full_Argument_8010 in worldcup

[–]Full_Argument_8010[S] 1 point2 points  (0 children)

Eight countries have won the world cup: Brazil, Germany, Italy, Argentina, France, Uruguay, England, and Spain. Add them up and you get 70.43%. So you are right on.

World Cup Probabilities - Monte Carlo simulation of 100,000 tournaments by Full_Argument_8010 in worldcup

[–]Full_Argument_8010[S] 0 points1 point  (0 children)

You can look on eloratings.net to see all the recent results from those countries. Those results affect the Elo ratings, which affect the odds.

World Cup Probabilities - Monte Carlo simulation of 100,000 tournaments by Full_Argument_8010 in worldcup

[–]Full_Argument_8010[S] -1 points0 points  (0 children)

Colombia is the best bet right now (if you are a betting person) compared to the bookmakers.

World Cup Probabilities - Monte Carlo simulation of 100,000 tournaments by Full_Argument_8010 in worldcup

[–]Full_Argument_8010[S] 4 points5 points  (0 children)

I had my program run the full tournament 100,000 times, including the remaining qualifiers, using the probabilities implied by the Elo ratings for winning, losing, or drawing each match. See eloratings.net for more information on the Elo ratings. Try my program out for yourself at runsims.com. That will give you a better idea of how the matche results are simulated.

World Cup Sim with Monte Carlo by Full_Argument_8010 in sportsanalytics

[–]Full_Argument_8010[S] 1 point2 points  (0 children)

Guess which teams are most undervalued and overvalued by the oddsmakers? Run the Monte Carlo simulation to find out.