My predictions for next week-end (it will be a very full week for me at work, and I'm better to do it now): WAS 0 SEA 2 NC 1 UTA 0 ORL 1 NJ 2 (yes, I am trying the gamble: I am too much behind not to try. That's, by the way, the usual mistake casino-losers make ) CHI 3 POR 1
For a little fun during the break, here's a table that shows how we've done as a collective over the course of the season so far -- we're roughly half way through the regular season. Our total number of predictions is 626. That includes a phantom predictor who goes with 1-1 for every game, since that's a prediction someone easily could make -- it would place them quite high in the rankings so far. There are carry overs in some numbers in moving across the table. For example, the # of correct exact score predictions also shows up in each of the other categories.
I was MIA because of final exams and then launching two summer classes on a new online teaching platform (change from Blackboard to Canvas). So, buried, but now emerging.
Welcome while emerging, BalanceUT. Continuing with success at predicting correct game scores, here's a table that shows how each predictor has done, taking into account games in which there were no predictions. In this table, I've included the phantom predictor who simply goes with 1-1 for every game:
Well, I thought the robot was putting us to shame, but the "phantom" 1-1 predictor embarasses us even more!!! Are we really so bad that most of us would have done way better by just writing down 1-1, 1-1, 1-1, 1-1 each week and call it a day?
Yes, I hesitated to show how the phantom 1-1 predictor was doing because I didn't want to depress some predictors. But remember, that's just how the phantom is doing at predicting exact scores, which isn't too surprising since teams score 1 goal about 37% of the time, which suggests there will be a good number of 1-1 games. Here are the robot's predictions for this week: Washington 1 v Seattle 2 North Carolina 1 v Utah 0 Orlando 3 v Sky Blue 1 (very rare for the robot to predict 3 goals for a team, but that's how poor Sky Blue has been in away games over the last half of 2017 and the first half of 2018) Red Stars 1 v Thorns 1
It should, but then again, it's a heartless computer that determines your score . For more detail on Sky Blue, over the last half of 2017 and the first half of 2018, in away games, their average score has been Sky Blue 1.00 v Opponent 3.00 (it's unusual to have the scores come out right on the numbers). The average NWSL points of its away opponents over that time period is 32.86. Orlando's NWSL points over that period are 34, which makes for a good match. Thus the robot's 3-1 prediction. If you get it right notwithstanding, you're either a genius (most likely) or very lucky (less likely).
Hopefully Chicago will only have one player on the the "OUT" list. (Unfortunately we already know Stephanie Mcaffrey will be out). Casey Short, Vanessa Dibernardo and who knows, maybe even Morgan Brian may be ready. Bad news for Portland.......
It would be exciting if Gilmoy could even give a personal prediction to us for this match-day, as a special one-of.
June 16 predictions: Washington 0, Seattle 2 North Carolina 1, Utah 1 Orlando 3, NJ 1 Chicago 2, Portland 2