I’m sure most of you think I’m pretty twisted; i.e. a modeling fanatic who rarely ventures out in the light of day.... <blink, blink>
…this thread will convince you…
If you are a newbie to sports modeling, these are Wreck’s Commandments to live by when you build a model:
(imagine James Earl Jones reading this to you)
1. Thou shalt (TS): Pick one sport to model. Actually one variant of a sport like NBA sides. Pick a sport you like and want to research because you will be spending a lot of time on it if you are to do even moderately well. Until you can do one sport variant well, you should not do others, as you’ll simply spread yourself out too thinly and accomplish little.
2. (TS): Examine the data available to pick which type of modeling to use. In the NFL, with Gamebooks, you can build Monte Carlo Simulations (Sims) to do both Expected Value (EV) modeling and simulations. NBA is too difficult to model play-by-play so most mortals do EV, as the data to do play-by-play doesn’t exist online.
3. (TS): Divide your data set into two sections, one to build your model from, the second to test against. This helps in preventing overfitting, but is no guarantee. I have a woeful story about this in regards to the NFL and the old USFL.
4. (TS): Spend time and money, if you have to, getting quality data. Most of the data in on-line dbs are full of errors. Sharing data with other modelers works well, but most modelers are like herding cats, and won’t trade their precious data. Not only that, but a great portion of them think they are God’s gift to the modeling world so why should they help anyone else out? …come to think of it, my sh*t doesn’t stink either…
5. (TS): Paper trade your system until you get it working, and use a very small bankroll (BR) in your first season when you fist make wagers. If you exhaust your BR, don’t refill it, work on the model to prepare for next season.
6. (TS): Keep strict records of how your model is doing against the line (ATS) and straight up (SU). Annotate any changes in modeling against your win% both ATS and SU.
7. (TS): Not use Kelly Criterion to bet your first year. You might want to seriously consider NOT using Kelly in other years too. But if you do, plan on spending some quality time on Bayesian Priors. BTW if you use it, plan on Kelly kicking your ass…a lot…
8. (TS): Plan on spending a lot of time rebuilding your model during the season, especially when your model breaks down, i.e. can’t hold a winning percentage over at least 30 games.
9. (TS): Plan on your model breaking down, because it will. When it does, stop everything (yes folks, this does mean: no betting) and examine everything. Look at your data set first because: garbage in with get you sewage out.
10. (BTW): This list doesn’t cover good betting practices (don’t chase, don’t bet more than you can lose, yadda, yadda). Plenty of advice on this elsewhere.
When you conquer a single sport variant, PM me with a copy of your code, and go back to step 1 for the next variant.
Have fun boys and girls…
…and girls, PM me anyway, cause any chick who can code has got to be another alien like me…
…this thread will convince you…
If you are a newbie to sports modeling, these are Wreck’s Commandments to live by when you build a model:
(imagine James Earl Jones reading this to you)
1. Thou shalt (TS): Pick one sport to model. Actually one variant of a sport like NBA sides. Pick a sport you like and want to research because you will be spending a lot of time on it if you are to do even moderately well. Until you can do one sport variant well, you should not do others, as you’ll simply spread yourself out too thinly and accomplish little.
2. (TS): Examine the data available to pick which type of modeling to use. In the NFL, with Gamebooks, you can build Monte Carlo Simulations (Sims) to do both Expected Value (EV) modeling and simulations. NBA is too difficult to model play-by-play so most mortals do EV, as the data to do play-by-play doesn’t exist online.
3. (TS): Divide your data set into two sections, one to build your model from, the second to test against. This helps in preventing overfitting, but is no guarantee. I have a woeful story about this in regards to the NFL and the old USFL.
4. (TS): Spend time and money, if you have to, getting quality data. Most of the data in on-line dbs are full of errors. Sharing data with other modelers works well, but most modelers are like herding cats, and won’t trade their precious data. Not only that, but a great portion of them think they are God’s gift to the modeling world so why should they help anyone else out? …come to think of it, my sh*t doesn’t stink either…
5. (TS): Paper trade your system until you get it working, and use a very small bankroll (BR) in your first season when you fist make wagers. If you exhaust your BR, don’t refill it, work on the model to prepare for next season.
6. (TS): Keep strict records of how your model is doing against the line (ATS) and straight up (SU). Annotate any changes in modeling against your win% both ATS and SU.
7. (TS): Not use Kelly Criterion to bet your first year. You might want to seriously consider NOT using Kelly in other years too. But if you do, plan on spending some quality time on Bayesian Priors. BTW if you use it, plan on Kelly kicking your ass…a lot…
8. (TS): Plan on spending a lot of time rebuilding your model during the season, especially when your model breaks down, i.e. can’t hold a winning percentage over at least 30 games.
9. (TS): Plan on your model breaking down, because it will. When it does, stop everything (yes folks, this does mean: no betting) and examine everything. Look at your data set first because: garbage in with get you sewage out.
10. (BTW): This list doesn’t cover good betting practices (don’t chase, don’t bet more than you can lose, yadda, yadda). Plenty of advice on this elsewhere.
When you conquer a single sport variant, PM me with a copy of your code, and go back to step 1 for the next variant.
Have fun boys and girls…
…and girls, PM me anyway, cause any chick who can code has got to be another alien like me…
