Aaron Brown's NFL Sports Betting System.

Discussion in 'Trading' started by TheBigShort, Jun 23, 2019.

  1. AaCBrown

    AaCBrown

    S + N = 20%, this is what you observe. You can't measure S and N, you can only guess about them, hopefully with better than random accuracy.

    I this case you have conflicting information. The fact that this quarter's implied move is greater than last quarter's implied move inclines you to guess it is an over-reaction and the actual expected move is between 10% and 20%. But the fact that it is less than last quarter's actual move inclines you to bet that the actual move will be between 20% and 25%. Both of these predictions are things you might expect to be borne out when averaging over hundreds of events, not something reliable every time.

    This is ultimately an empirical question to be investigated from past data. There could be reasons you have the opposite effect, many moves tend to be under-reactions. The only value of thinking about shrinkage is the knowledge that it works in many similar situations, so it's less likely to be a random pattern thrown up by data mining (that is, if it turns out to exist in the data) than some pattern without broader support.
     
    #21     Nov 30, 2019
    jtrader33 and Aged Learner like this.
  2. AaCBrown

    AaCBrown

    I don't think in terms of R^2 for this application. I'm trying to get a 55% win rate, meaning I need a 0.01 R^2 between my prediction and the outcome. In most textbook problems, an R^2 of 0.01 would not be considered useful. But it can make you rich if it's real. High R^2's usually describe relations that are obvious without statistics--and often if you want to understand those relations you need domain knowledge rather than statistical expertise.

    In an efficient sports betting market, there would be no autocorrelation. Sure, good teams keep winning, but if the market correctly evaluates how good teams are, the spread should be set such that good teams and bad teams beat it 50% of the time (in fact, underdogs win slightly but consistently more than 50% of games, but this autocorrelation is the sort that models exploit to win, not autocorrelation that destroys the models).

    My model actually bets on negative autocorrelation in spreads. If the spread moves to favor Team A, it moves too far on average, and you should bet against Team A.
     
    #22     Nov 30, 2019
    jtrader33 likes this.
  3. TheBigShort

    TheBigShort

    Aaron, can we go over this a bit more?In your example Ed George found out it was better to shrink to the average of each position. What if we find that your dominant hand explains some variance in batting average. How would I go about shrinking to both: position and dominant hand?

    How might you go about finding a predictor variable on a data set that has many levels. For example, in an Earnings data set where our DV is |Move| we have many levels/groups such as Stock, Industry, Sector, Mktcap etc.. We might find a relationship between |Move| and Mktcap only once we group by sector. The amount of combinations start to get very large. This is a serious problem I have when it comes to modelling.

    Above I posted a link to cross validated where @whubber showed a negative relationship between 2 variable once we grouped and used the centroid of each group.
     
    #23     Dec 4, 2019
  4. AaCBrown

    AaCBrown

    Your first question is easy. You could build a model of the form:

    second half of the season batting average =
    A * (first half of the season batting average for the player) +
    B * (first half of the season batting average for all players at the same position) +
    C * (first half of the season batting average for all players of the same handedness) +
    error

    Normally in shrinkage, A + B + C = 1, but you do not have to enforce this. You also don't have to use a linear model, for example, you might want to shrink batters close to the average more or less than batters far from the average; or you might want to shrink batters with more at bats less than batters with more at bats.

    I don't think it's wise to look for shrinkage everywhere, with respect to every variable and combination of variables. I would look for it only where (a) you had a lot of data from different markets and time periods suggesting there was some broad, fundamental effect, or (b) you had some economic or behavioral reason to expect over-reaction.
     
    #24     Dec 4, 2019
    drm7 likes this.
  5. TheBigShort

    TheBigShort

    Aaron, its great to see you have turned ET notifications on :p. It looks like people are really enjoying your posts. Keep them coming!
    Screen Shot 2019-12-05 at 12.59.46 AM.png

    Another concept you mentioned in the paper is "Feeding The Hungry". Do you think this concept would apply to an earnings event? Eg. The long vol earnings bettors/hedgers have lost money over the last 4 LULU events, so they will most likely not be willing to bid up the option prices this quarter. I have actually tested this because of your paper, but I did not find a signal.

    Unlike sports, The Hungry might remain hungry like in the index vol space (ivol usually overstates hvol). Which is unlikely to change. I would love to hear your opinion on that.

    p.s. Where do you do your data analysis? I could not figure it out from your posts on NP and Qoura.
     
    Last edited: Dec 5, 2019
    #25     Dec 5, 2019
  6. TheBigShort

    TheBigShort

    Data Analysis Using Regression and Multilevel/Hierarchical Models

    I am 100 pages in and I absolutely love it! The math is simple, the examples are fantastic. For anyone who is interested in learning about shrinkage/partial pooling, this is the best beginners guide!
     
    #26     Dec 12, 2019
  7. MrKobalt

    MrKobalt

    I would like to try it as well.
     
    #27     Mar 24, 2020
  8. Who has Aaron Hernandez in their FF roster?
     
    #28     Mar 24, 2020
  9. newwurldmn

    newwurldmn

    duzos kid's friend.... for his NBA fantasy team.
     
    #29     Mar 24, 2020
    PoopyDeek likes this.
  10. Freedance

    Freedance

    This information should be helpful to anyone placing bets. No matter how much I tried to figure out the odds, winnings, and other things, it was always tricky.
     
    #30     Jun 11, 2021