BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:America/New_York X-WR-TIMEZONE:America/New_York BEGIN:VEVENT UID:908@fds.yale.edu DTSTART;TZID=America/New_York:20260204T113000 DTEND;TZID=America/New_York:20260204T130000 DTSTAMP:20260116T153908Z URL:https://fds.yale.edu/events/fds-colloquium-brian-burke-espn/ SUMMARY:FDS Colloquium: Brian Burke (ESPN)\, "A Solution to the Performer-C ontext Paradox" DESCRIPTION:\nAbstract: A common method of assessing performance in sports or other domains is to rely on residual analysis. Under this framework\, a task performed within a given situational context is assigned an expected probability of success\, and the performer is credited or debited by the residual. For example\, if an athlete accomplishes a feat that has an expe cted 0.75 probability of success\, he would be credited with the balance o f 1 - 0.75 = 0.25. If he fails\, he would be debited with 0.75. Many indiv idual performance metrics in sports adopt this approach to account for var iation in situational difficulty. \n\n\n\nHowever\, this framework overlo oks a critical complication: the athlete himself often influences the very context he finds himself in. A top performer might change a 0.75 feat int o a 0.85 feat\, reducing the credit available for a success. This is the&n bsp\;Performer-Context Paradox\, which systematically penalizes elite perf ormers for creating more favorable environments. The more positively a per former shapes his context\, the less credit he can receive under residual- based evaluation. \;\n\n\n\nESPN’s Receiver Tracking Metrics for NFL pass catchers solve this problem in two innovative ways. First\, our appr oach segments performance\, so each phase of the task is independently ass essed. Second\, it explicitly measures the impact an athlete has on his co ntext before the residual is calculated. Together\, these steps allow perf ormer contributions to be disentangled from contextual effects\, yielding a more faithful assessment of individual performance.\n\n\n\nBio: Brian Bu rke\, founder of the popular website AdvancedFootballAnalytics and one of the leading voices in NFL Analytics\, joined ESPN as a senior analytics sp ecialist in June 2015. As a member of the Stats &\; Information Group ’s (SIG) Analytics Team\, Burke is expanding upon his previous work to e nsure ESPN has the best-in-class football analytics. His years of experien ce are also helping ESPN develop analytic tools in other sports.\n\n\n\nBu rke founded \;advancedfootballanalytics.com \;in 2007. \;The s ite includes tools such as in-game win probability graphics\, 4th-down cal culator\, win probability calculator\, NFL Draft Prediction model\, and mo re. In addition to being the site’s primary writer\, Burke has contribut ed to \;The \;New York Times\, \;The Washington Post\, \;S late \;and other outlets. \;A regular speaker at the MIT Sloan Spo rts Analytics Conference\, he also previously worked as an analytics consu ltant for multiple NFL teams and supplied statistics and analytics insight s to NBC Sports and \;ESPN The Magazine.\n\n\n\nBefore entering the wo rld of sports analytics\, Burke had a distinguished career as an officer a nd aviator with the United States Navy. \;Much of those 15 years were spent as an F/A-18 carrier pilot. \;He flew numerous combat missions a nd was awarded the Air Medal\, the Navy Commendation Medal\, and numerous other personal and unit commendations.\n\n\n\nOriginally from Baltimore\, Md.\, Burke graduated from the U.S. Naval Academy \;with the Class of 1993. He attended the Naval Postgraduate School and returned to Annapolis as an instructor. After serving in the Navy\, Burke worked for a defense c ontractor\, serving as a strategy and tactics expert and then as a busines s unit director before launching Advanced Football Analytics. He recently completed a masters degree in Operations Research from George Mason Univer sity.\n\n\n\nWhen not analyzing \;football and other sports\, Burke co mpetes in triathlons. He resides with his family in Reston\, \;Virgini a\, just outside Washington\, D.C.\n CATEGORIES:FDS Events,Colloquium LOCATION:Yale Institute for Foundations of Data Science & Webcast\, 219 Pro spect Street\, 13th Floor\, New Haven\, CT\, 06511\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=219 Prospect Street\, 13th Floor\, New Haven\, CT\, 06511\, United States;X-APPLE-RADIUS=100;X-TITLE= Yale Institute for Foundations of Data Science & Webcast:geo:0,0 END:VEVENT BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST END:STANDARD END:VTIMEZONE END:VCALENDAR