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8 - Kostya Medvedovsky, DARKO and assorted NBA analytics topics

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Manage episode 318615221 series 2567711
Indhold leveret af Canzhi Ye. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Canzhi Ye eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

I was joined by Kostya Medvedovsky, the creator of the basketball projection system DARKO. We went into the weeds about the methodology behind DARKO and answered questions from Twitter about it. We then picked Kostya's brain on a wide range of NBA analytics ideas, mostly focused on topics that involve predicting things. Finally, we answered some more questions from Twitter. You can find Kostya on twitter: @kmedved

[00:00:00] - DARKO

[00:05:05] - exponential decay

[00:08:10] - kalman filters

[00:11:10] - gradient boosted trees go brrrr?

[00:13:40] - data infra

[00:21:30] - seasonality effects

[00:30:45] - rule changes, big external shifts like COVID

[00:37:50] - aging effects

[00:42:40] - measuring defense with box score data

[00:44:50] - Canzhi rants on RAPM, SPM

[00:52:35] - garbage time

[00:57:00] - how to structure data, wax poetic on pbpstats

[01:02:20] - player career and longevity projections

[01:09:30] - another GBT package

[01:10:50] - DFS, betting

[01:19:40] - when DARKO struggles / can learn from betting markets

[01:26:55] - college basketball DARKO

[01:35:00] - NBA preseason

[01:41:30] - coach RAPM lol

[01:43:10] - playoff adjustments

[01:46:25] - playoff adjustments

[01:49:05] - hot hand (fallacy? paper linked below), midwits

[01:55:40] - Sengun

[02:00:50] - team building, quantifying lineup ~synergies~

Things we brought up in the episode:
DARKO: https://darko.app

DRIP: https://theanalyst.com/na/2021/10/nba-stats-and-player-projections/

Hot hand discussion: https://marketing.wharton.upenn.edu/wp-content/uploads/2018/11/Paper-Joshua-Miller.pdf

  continue reading

9 episoder

Artwork
iconDel
 
Manage episode 318615221 series 2567711
Indhold leveret af Canzhi Ye. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Canzhi Ye eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

I was joined by Kostya Medvedovsky, the creator of the basketball projection system DARKO. We went into the weeds about the methodology behind DARKO and answered questions from Twitter about it. We then picked Kostya's brain on a wide range of NBA analytics ideas, mostly focused on topics that involve predicting things. Finally, we answered some more questions from Twitter. You can find Kostya on twitter: @kmedved

[00:00:00] - DARKO

[00:05:05] - exponential decay

[00:08:10] - kalman filters

[00:11:10] - gradient boosted trees go brrrr?

[00:13:40] - data infra

[00:21:30] - seasonality effects

[00:30:45] - rule changes, big external shifts like COVID

[00:37:50] - aging effects

[00:42:40] - measuring defense with box score data

[00:44:50] - Canzhi rants on RAPM, SPM

[00:52:35] - garbage time

[00:57:00] - how to structure data, wax poetic on pbpstats

[01:02:20] - player career and longevity projections

[01:09:30] - another GBT package

[01:10:50] - DFS, betting

[01:19:40] - when DARKO struggles / can learn from betting markets

[01:26:55] - college basketball DARKO

[01:35:00] - NBA preseason

[01:41:30] - coach RAPM lol

[01:43:10] - playoff adjustments

[01:46:25] - playoff adjustments

[01:49:05] - hot hand (fallacy? paper linked below), midwits

[01:55:40] - Sengun

[02:00:50] - team building, quantifying lineup ~synergies~

Things we brought up in the episode:
DARKO: https://darko.app

DRIP: https://theanalyst.com/na/2021/10/nba-stats-and-player-projections/

Hot hand discussion: https://marketing.wharton.upenn.edu/wp-content/uploads/2018/11/Paper-Joshua-Miller.pdf

  continue reading

9 episoder

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