My Math Forum  

Go Back   My Math Forum > High School Math Forum > Probability and Statistics

Probability and Statistics Basic Probability and Statistics Math Forum

LinkBack Thread Tools Display Modes
January 6th, 2015, 01:35 AM   #1
Joined: Jan 2015
From: hong kong

Posts: 3
Thanks: 0

Measuring predictions, statistically

Sorry if this question might appear to be a bit vague.

I am trying to measure the performance of my model, by comparing the actual shots on target attained by a football team against a predicted amount of shots that my model estimates.

I have been reading up on various methods that might help me, but can't quite figure out where to turn.
Should I be using some sort of log likelihood (logistical regression) method?
Or do I need to find the MSE (mean squared error)?

Any help would be greatly appreciated
Attached Images
File Type: jpg maths.jpg (51.6 KB, 8 views)
StooCats is offline  
January 5th, 2017, 06:43 PM   #2
Senior Member
Joined: Oct 2013
From: New York, USA

Posts: 477
Thanks: 71

The "Team Performance vs Expected" could have the absolute value of the difference between the two columns, but that might not be useful. I think models need to be compared to each other rather than evaluating one model by itself. Your model has a correlation (r) = 0.4050020254. A positive correlation means the your model predicts in the correct direction.
EvanJ is offline  

  My Math Forum > High School Math Forum > Probability and Statistics

measuring, predictions, statistically

Thread Tools
Display Modes

Similar Threads
Thread Thread Starter Forum Replies Last Post
Linear Graph Future Predictions hein123 Linear Algebra 0 June 7th, 2014 01:57 AM
Measuring Reflections icor1031 Algebra 8 April 3rd, 2014 04:08 PM
Bayesian predictions ybot Advanced Statistics 4 July 7th, 2013 04:14 AM
How to determine the accuracy of predictions? TheAndruu Algebra 7 May 13th, 2010 04:39 PM
Making a measuring stick for an oiltank wahlstrom Algebra 8 December 28th, 2007 12:45 PM

Copyright © 2017 My Math Forum. All rights reserved.