https://www.youtube.com/watch?v=clCpyVHApqY

https://www.youtube.com/watch?v=DhJxYeDUbLQ

Throughout the talk, please utilize the chat to ask questions. The moderators will forward the questions to the speaker. Please remain on mute until the Q&A session.

how it helps in player selection?

Who is more receptive to listening to data: GMs for player selections or coaches for lineups/defensive shifts?

I am a big fan of football and cricket and I love to watch these games live. I was just wondering, how do you implement AI to find the best pitchers? Like do you find who pitches the fastest ball, or who most frequently gets the batter out?

How is player defensive rating different than UZR? How do the Rays apply these metrics to minor leaguers that are in other organizations (i.e. Randy Arozarena)?

How long did it take to create this classification model? Was it complicated at first?

I'm a huge baseball fan, and I know the Rays FO has a huge reputation for being one of the smartest. Two things that stand out to me is that you guys will find the best players, then milk them as long as possible then drop him right when he has the most value, or that when y'all ask for a trade for a player their entire analytics teams revisit their analysis process about that player. My question is, how do you guys balance data you get from models you create and the eye test?

First, I wanted to say I enjoyed your presentation a great deal, Will. My question is whether or not there have attempts to harness the available cameras to collect data and perform ML analysis on aspects of the baseball experience off the field (team dugouts, fan mood and reaction to players and events, etc.)?

Do the Rays use in game technology like iPads to breakdown a play with each player or only ones that are receptive to the technology? How did the lack of in-game technology affect last years team when the replay rooms weren’t in use due to COVID restrictions?

How big of a factor do the results that your analytics team produces impact decisions made by FO, coaches, and players?

How is the stat cast data, metrics, and machine learning used in the draft process and the scouting of high school and college players?

You could take opinion from the baseball players whether they work hard in their games and frame their opinion into the model, right?

less technical question, but how do you get a job in sports analytics without connections? especially since you did a postdoc in mechanical eng, did you have any challenges with that?