Background: Computer Science school teacher... previous life... Army Officer... Simulation expert and presenter. Degree is in Electrical Engineering with Computer Engineering Track.
Step 1: Collect data. Has to remain pure. I have had people ask me to exchange data and I quickly asked is it pure or did up manipulate it. Data is only valuable in its infancy state. And it has to be current. You can manipulate it at your hearts content after the fact. Pure data believe it or not is a commodity.
Step 2: Use mathematics to include standard deviations ... z scores and try to determine the variables that at least determine a reasonable score outcome. There are so many variables that impact the score that it is unreasonable to think you will predict the exact outcome but you may be able to get close.
Step 3: Develop an algorithm to test against past data. This presents a problem because many don't actually have past data that is pure to test against. I do. If you have virgin past data and can develop an algorithm that worked in the past... try it moving forward.
Step 4: Did you algorithm actually work? Was it close to the predictions or way off? Do you need to make adjustments or is it right but unlucky or is it completely worthless?
I have spent well over ten years.... just getting to the put that I collect data correcting and do the math correctly. I am now creating algorithms that worked in the past and seeing if they can predict the future.
As a modeler you are always going to tweak as new data comes in.
College Football Results:
Keep in mind these results are just based on the week they occurred if the same algorithms didn't work the previous 3 years they are worthless.
Week 10 10-8
Week 11 11-5
Week 12 4-6
Week 13 9-5
You have any questions... send me a message. I'll try to accommodate as much as I can .
My NFL program has done really well until last week went 1-6. NBA is doing well but last night 4-5. I have losses but everything trending well.
Dave
P.S. The irony... is I have been told it can't be done. I actually think I might have already done it for college football... I am onto NFL... but more NBA and NCAAB,
Step 1: Collect data. Has to remain pure. I have had people ask me to exchange data and I quickly asked is it pure or did up manipulate it. Data is only valuable in its infancy state. And it has to be current. You can manipulate it at your hearts content after the fact. Pure data believe it or not is a commodity.
Step 2: Use mathematics to include standard deviations ... z scores and try to determine the variables that at least determine a reasonable score outcome. There are so many variables that impact the score that it is unreasonable to think you will predict the exact outcome but you may be able to get close.
Step 3: Develop an algorithm to test against past data. This presents a problem because many don't actually have past data that is pure to test against. I do. If you have virgin past data and can develop an algorithm that worked in the past... try it moving forward.
Step 4: Did you algorithm actually work? Was it close to the predictions or way off? Do you need to make adjustments or is it right but unlucky or is it completely worthless?
I have spent well over ten years.... just getting to the put that I collect data correcting and do the math correctly. I am now creating algorithms that worked in the past and seeing if they can predict the future.
As a modeler you are always going to tweak as new data comes in.
College Football Results:
Keep in mind these results are just based on the week they occurred if the same algorithms didn't work the previous 3 years they are worthless.
Week 10 10-8
Week 11 11-5
Week 12 4-6
Week 13 9-5
You have any questions... send me a message. I'll try to accommodate as much as I can .
My NFL program has done really well until last week went 1-6. NBA is doing well but last night 4-5. I have losses but everything trending well.
Dave
P.S. The irony... is I have been told it can't be done. I actually think I might have already done it for college football... I am onto NFL... but more NBA and NCAAB,
