Does the “all-in” strategy actually work? CPP reader Edgar Medina (@Ironclad) ran some computer simulations with the probabilities in the table from week 9, and tested the money picks (the blue, yellow, and green shaded picks). He tests the Giants (green money pick) at various confidence levels, all the upset picks, and various other scenarios using the two leagues he’s part of. Here’s his write up of the work he did. Thank you Edgar!
Kickoff time is here! It’s too late to change our picks, but we can study what might have been. The retrospective simulations shown here are for a 32-player league, which I think is on the small side of how people play. … >>read more>>
For Confidence Pool Picks, I use the implied win probability that Moneylines give us to create the “base picks” each week. The idea is to assign higher win probabilities higher confidence values. But is Moneyline even accurate?
I wanted to put this to the test. I analyzed data from the 2013 season, and compared what Moneyline values predicted to what actually happened. To review, the Moneyline values are in the form of +150 or -300. Positive values mean you bet the value, in this case $150, to win $100. Negative values mean you bet $100 to win the value, in this case $300.… >>read more>>
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Picking in a confidence pool league or Yahoo Pick Em League with confidence points involves two things: accuracy and contrarian-ness. Accuracy is picking the right team to win and putting the right confidence level to it. However, it’s virtually impossible to pick all the teams right. If it were easy, we wouldn’t need to care for the second part of the equation: contrarian-ness. To be a contrarian is to be someone who goes the opposite way; someone who zigs when others zag. If you pick the same as everyone in the league, you’ll probably end up in the middle of the pack… out of the money.… >>read more>>