Using the mean or median has no effect on the variance and does not change the probability of your predicted result. To have a serious model you have to have a calculation that decreases the variance to a point where the probability is significant enough to have confidence in the result. there is just nothing you can do mathematically with that data in its current state to give you any possible way of predicting future outcomes with any significant probability. Whether that is weighting for defenses, weighting for starting lineups, etc. So you have to figure out a model to change the 80, 100, 120 points in to something more correlated. For example, a team that scores 80, 100, and 120 points has the same mean and median as a team that scores 98, 100, 102 points, yet the variance isn't even close. You calculate the variance within your dataset to project the probability of future data points. If you could, you wouldn't need statistics. any thoughts on this?You don't project future variance. I imagine modelling with means and variance is superior to using just medians.and medians is superior to only meansīut how do you project variance? is past variance predictive of future variance? my guess for basketball is pace, 3 point attempts, and TOs are three 3 variables that determine variance.
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