Intro to Power Ratings, Part 4: Pythagorean Win Expectation and Log 5 Win Probability

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  • เผยแพร่เมื่อ 2 ธ.ค. 2024

ความคิดเห็น • 15

  • @Highlandcorp
    @Highlandcorp 4 ปีที่แล้ว +6

    Please keep these kinds of videos coming! There is no one else on TH-cam that do the good work you do, really appreciate it!

  • @nickranieri
    @nickranieri 4 ปีที่แล้ว +1

    Thanks again for sharing an approach to developing prediction models. I find them very informative. And beyond the model, being exposed to VBA macro programming. Keep them coming and until sports are back, we have lots of time to develop the perfect models.

  • @selecthospitalityinc.9109
    @selecthospitalityinc.9109 4 ปีที่แล้ว

    Great job on the videos....learning more about Macros is great. I took your 4th video, plugged in all the NBA and MLB scores and the models are looking pretty good. Looking forward to adding more stats to the Pytho model to refine it even more. Great work, keep it up!

  • @thoughtsfromthecheapseats4641
    @thoughtsfromthecheapseats4641 4 ปีที่แล้ว

    love the channel. we subscribed. we would love to pick your brain about how you grew so quickly covering this topic. thanks for your help man.

  • @cactuscapper5567
    @cactuscapper5567 4 ปีที่แล้ว +1

    I appreciate this series, thank you

  • @docholliday4128
    @docholliday4128 11 หลายเดือนก่อน +1

    How is it possible for the Proj. Score to say that one team will win, but Pyth shows me that the other team has a higher percentage for win?

  • @OlkaAlex94
    @OlkaAlex94 2 ปีที่แล้ว

    Could I just plug projected scores into pyth formula to determine win probability ?

  • @dachgoliga8520
    @dachgoliga8520 2 ปีที่แล้ว

    Could you do something like what are the posibilities for each team to win their division?

  • @roberthunt8204
    @roberthunt8204 4 ปีที่แล้ว

    Great video.

  • @NCKLM
    @NCKLM 4 ปีที่แล้ว

    What is your education background in? How would someone get started in building the acumen of your statistics knowledge?

  • @bkkerevan2654
    @bkkerevan2654 4 ปีที่แล้ว +1

    Great video, thoroughly enjoying this series during lockdown. I've applied this to a football league (soccer if you're American) and look forward to testing it out.
    However, in soccer, the draw percentage is much higher than in the NFL (although I am not familiar with the average range of results). Broadly speaking around 25% of matches in a season end in a draw so how would you incorporate this into the PYTH and LOG5 calculations?
    Cheers

    • @williamleiss4
      @williamleiss4  4 ปีที่แล้ว +1

      I think you are better off doing an ELO calculation for draws.

  • @joelsweet2302
    @joelsweet2302 4 ปีที่แล้ว +1

    Why is there a home advantage and an away disadvantage?

    • @joelsweet2302
      @joelsweet2302 4 ปีที่แล้ว

      Can someone please explain this? If there is a home advantage, why must there be an away disadvantage? Doesn't that double it up unnecessarily? Thank you :D

  • @nexus-qb3bu
    @nexus-qb3bu 4 ปีที่แล้ว +1

    You seem to edit alot and throw out "one-liner" comments. Let's see your knowledge for verbal fluency on these games.