Ron Yurko and Kostas Pelechrinis host the 'Open Source Sports' podcast to serve as a public reading group for discussing the latest research in sports analytics. Each episode focuses on a single paper featuring authors as guests, with discussions about the statistical methodology, relevance and future directions of the research. <br/><br/><a href="https://statthinksportsanalytics.substack.com?utm_medium=podcast">statthinksportsanalytics.substack.com</a>
Open Source Sports
Claim This Podcastby Ron Yurko
4.8(13 reviews)
12 episodes
Updated Daily
Accepts GuestsHas SponsorsLocation 🇺🇸
Podcast Overview
Ron Yurko and Kostas Pelechrinis host the 'Open Source Sports' podcast to serve as a public reading group for discussing the latest research in sports analytics. Each episode focuses on a single paper featuring authors as guests, with discussions about the statistical methodology, relevance and future directions of the research. <br/><br/><a href="https://statthinksportsanalytics.substack.com?utm_medium=podcast">statthinksportsanalytics.substack.com</a>
Language
🇺🇲
Publishing Since
5/6/2020
1 verified contact email on file for Open Source Sports
Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.
Recent Episodes
August 23, 2022
A Statistical Model of Serve Return Impact Patterns in Professional Tennis with Stephanie Kovalchik
<p>In this episode we talk to <a href="https://twitter.com/StatsOnTheT">Stephanie Kovalchik</a> about her paper <a href="https://arxiv.org/abs/2202.00583">'A Statistical Model of Serve Return Impact Patterns in Professional Tennis'</a> (co-authored with Jim Albert). Stephanie is a Staff Data Scientist at <a href="https://zelusanalytics.com/">Zelus Analytics</a>, where she works on advanced performance valuation for multiple pro sports. Before joining Zelus, Stephanie led data science innovation for the Game Insight Group of <a href="https://www.tennis.com.au/">Tennis Australia</a>, building first-of-a-kind metrics and real-time applications with tracking data. Stephanie is the founder of the <a href="http://on-the-t.com/">tennis analytics blog "On the T"</a> and tweets <a href="https://twitter.com/StatsOnTheT">@StatsOnTheT</a>. </p><br/><p>For additional references mentioned in the show:</p><br/><ul><br/> <li><a href="https://www.atptour.com/en/stats/second-screen/archive/2022/404/MS001">ATP Tour Second Screen</a></li><br/> <li>Stephanie's article in Harvard Data Science Review: <a href="https://hdsr.mitpress.mit.edu/pub/uy0zl4i1/release/4">Why Tennis Is Still Not Ready to Play Moneyball</a></li><br/> <li>Grand Slam R package: <a href="https://github.com/skoval/courtvisionr">courtvisionr</a></li><br/> <li>Stephanie's GitHub with various resources for accessing tennis data: <a href="https://github.com/skoval">https://github.com/skoval</a></li><br/> <li>Stan tutorials: <a href="https://mc-stan.org/users/documentation/tutorials">https://mc-stan.org/users/documentation/tutorials</a></li><br/> <li>Register now for the Carnegie Mellon Sports Analytics Conference: <a href="https://www.stat.cmu.edu/cmsac/conference/2022/">https://www.stat.cmu.edu/cmsac/conference/2022/</a></li><br/> <li>Check out the <a href="https://www.kaggle.com/competitions/big-data-derby-2022/overview">Big Data Derby</a> now on Kaggle</li><br/></ul> <br/><br/>This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit <a href="https://statthinksportsanalytics.substack.com?utm_medium=podcast&utm_campaign=CTA_1">statthinksportsanalytics.substack.com</a>
June 23, 2022
True Shot Charts with Justin Ehrlich and Shane Sanders
<p>We discuss <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4138586">True Shot Charts</a> with Syracuse University Professors <a href="https://falk.syr.edu/people/ehrlich-justin/">Justin Ehrlich</a> and <a href="https://falk.syr.edu/people/sandersshane/">Shane Sanders</a>. For references mentioned in the show:</p><br/><ul><br/> <li><a href="https://www.bigdataball.com/">BigDataBall</a></li><br/> <li><a href="https://www.statmuse.com/nba">StatMuse</a></li><br/> <li><a href="https://www.positiveresidual.com/">Positive Residual</a> - <a href="https://www.positiveresidual.com/shiny/true-shooting-charts/">True Shooting Charts</a></li><br/></ul> <br/><br/>This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit <a href="https://statthinksportsanalytics.substack.com?utm_medium=podcast&utm_campaign=CTA_1">statthinksportsanalytics.substack.com</a>
May 18, 2022
An Examination of Sport Climbing with Quang Nguyen
<p>We discuss <a href="https://jds-online.org/journal/JDS/article/1273/info">An Examination of Olympic Sport Climbing Competition Format and Scoring System</a> with <a href="https://qntkhvn.netlify.app/">Quang Nguyen</a> (<a href="https://twitter.com/qntkhvn">@qntkhvn</a>). This paper won the <a href="https://www.stat.cmu.edu/cmsac/conference/2021/">Carnegie Mellon Sports Analytics Conference Reproducible Research Competition in November 2021</a><a href="http://stat.cmu.edu/cmsac/conference/2020/" rel="ugc noopener noreferrer" target="_blank">.</a> </p><br/><p>Quang Nguyen completed his Master of Science in Applied Statistics at <a href="https://www.luc.edu/datascience/">Loyola University Chicago</a> in 2021. He recently spent the Spring 2022 semester working as an instructor in the Dept of Mathematics and Statistics at Loyola. Quang previously completed his undergraduate degree in Mathematics and Data Science at Wittenberg University in Springfield, Ohio. Quang's current interests include statistics in sports, data science, statistics and data science education, and reproducibility. He is a die-hard supporter of Manchester United F.C. of the English Premier League. And last but not least, Quang is excited to join the <a href="https://www.cmu.edu/dietrich/statistics-datascience/index.html">Dept of Statistics and Data Science at CMU</a> as a first-year PhD student this coming Fall 2022.</p><br/><p>For additional references mentioned in the show:</p><br/><ul><br/> <li>Quang's blog posts: <a href="https://qntkhvn.netlify.app/blog.html">https://qntkhvn.netlify.app/blog.html</a></li><br/> <li>Code for paper: <a href="https://github.com/qntkhvn/climbing">https://github.com/qntkhvn/climbing</a></li><br/> <li>I<a href="https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1379438">nducing Any Feasible Level of Correlation to Bivariate Data With Any Marginals</a></li><br/> <li>R copula package: <a href="https://cran.r-project.org/web/packages/copula/index.html">https://cran.r-project.org/web/packages/copula/index.html</a> and book: <a href="http://copula.r-forge.r-project.org/book/">http://copula.r-forge.r-project.org/book/</a></li><br/> <li><a href="https://statds.org/events/ucsas2022/index.html">UConn Sports Analytics Symposium (UCSAS) </a></li><br/> <li>CRAN Task View for Sports Analytics: <a href="https://cran.r-project.org/web/views/SportsAnalytics.html">https://cran.r-project.org/web/views/SportsAnalytics.html</a></li><br/></ul> <br/><br/>This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit <a href="https://statthinksportsanalytics.substack.com?utm_medium=podcast&utm_campaign=CTA_1">statthinksportsanalytics.substack.com</a>
12 total episodes available
Deep-dive analytics for Open Source Sports
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is Open Source Sports?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Yes, this podcast regularly features guests.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.