Co-Founder and Chief Scientist, @ZelusAnalytics. Formerly @ToulouseFC, @SacramentoKings, @SFU, @ASRomaEN, @Harvard
Joined September 2011
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10 Photos and videos
May 26
Salah’s career speaks for itself, but the story is also a reminder of what can happen when clubs combine smart people, good process, and the courage to trust evidence.
A privilege to contribute a small perspective to a much bigger story.
May 20
We’ve got a special three-part series on Mohamed Salah’s record-breaking Liverpool career and his legacy.
Here’s part one with @MarkCarey93 on how the shrewd signing of Salah with a data-led approach sparked changes across football.
nytimes.com/athletic/7252317…
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May 14
After numerous requests for additional time, we’re extending the CASSIS abstract submission deadline by two weeks, to May 31.
Looking forward to seeing your submissions!
Mar 10
Call for Abstracts: The Cascadia Symposium on Statistics in Sports (CASSIS) is now accepting abstracts for oral presentations. Deadline is May 15. More details at cascadiasports.com
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Mar 10
Call for Abstracts: The Cascadia Symposium on Statistics in Sports (CASSIS) is now accepting abstracts for oral presentations. Deadline is May 15. More details at cascadiasports.com
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Jan 5
Save the date: CASSIS ‘26 will be held on September 12th this year. Same venue as always (SFU Harbour Centre in downtown Vancouver).
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Feb 3
For those working on a research project in sports analytics, the conference's call for abstracts will go out next month (with abstracts typically due in late May).
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Luke Bornn retweeted
13 Jun 2025
🎧 Episode #69 of TGG Pod is with @LukeBornn
📊 Analytics pioneer
🏀⚽️Head of Data with @SacramentoKings & @ASRomaEN
🏆 Key in @ToulouseFC promotion Cup win
🕴️Founder @ZelusAnalytics, now @Teamworks Intelligence
🥇 1st person to return on TGG Pod!
🔗podcasts.apple.com/gb/podcas…
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4 May 2025
I rarely speak publicly on technical topics these days, so I really enjoyed recording an episode on Alex Andorra's Bayes podcast recently. For those with a more technical bent in the stats/analytics community, hopefully there are some useful nuggets here. open.spotify.com/episode/0tH…
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25 Nov 2022
While watching this 0-0 draw, thought I'd try visualizing some personal golf data. The intersection of golfers and sports analysts couldn't fill a foursome, but perhaps a couple of you are interested. First up, a round at Bandon Dunes from earlier in the summer. 1/5
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25 Nov 2022
A simple one looking at strokes gained against distance, split by shot type. Pretty remarkable how costly penalties and shots into recovery situations are. Turns out the only thing I'm half-competent at is recovery punch-outs. 4/5
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25 Nov 2022
And lastly, the same but focused on driver. Time for a new driver... 5/5
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8 Sep 2022
People usually point to collection bias (events never "exactly on the line") and rounding, but there's more. Tagging locations on a 105x68 pitch is really hard: 2-4m errors are normal. But lines provide a reference point, so tagged locations become much more accurate around them.
8 Sep 2022
I was looking at the Premier League event data and noticed that lines are almost visible to naked eye. I think I have seen someone mentioning this before, but it should be a data entry issue, right? No reason for players to avoid lines. Can't find the reference for it.
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10 Mar 2019
Sports scientists -- Here's evidence that the scientific literature may be grossly over-estimating the value of acute:chronic workload ratios in predicting injuries:
Talk: youtube.com/watch?v=TIRINmtZ…
Paper: lukebornn.com/papers/bornn_s…
Code: github.com/lukebornn/acute_c…
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21 Feb 2019
Decided in the fall that this will be my last year authoring papers at Sloan. As such, this thread is a great (and complete) resource for the 18 papers we’ve authored there since 2014. SSAC has been really good to me and my students — v thankful for doors opened and friends made!
20 Feb 2018
My lab has had 11 Sloan papers over the last 5 years:
'14: EPV
'15: Counterpoints, Move or Die
'16: Pressing Game, Court Realty
'17: Possession Sketches, Scorekeeper Bias
'18: Open Spaces, NFL Injury, NBA Replay, Deep Learning Trajectories
here's a summary thread of them all:
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20 Feb 2018
And lastly, credit for these projects belongs with the students who lead them: @dcervone0, @alexdamour, @afranks53, @_amiller_, @IavorBojinov, @MattvanBommel, @JaviOnData, @OSPpatrick, Nate, Yatao, Nazanin. Also, to @Harvard, @SFU, @SacramentoKings for supporting the research.
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21 Feb 2019
2019f: Chuckers (w/ @nsandholtz, @jwmortensen). We introduce the idea of spatial allocative efficiency in basketball lineups using spatial hierarchical rank models, allowing us to understand how lineups lose efficiency through who shoots where. lukebornn.com/papers/sandhol…
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21 Feb 2019
2019g: Highlight/Lowlight (w/ @Ev_Keane, @phildesaulniers, Mehrsan Javan). We automatically construct highlight and lowlight reels through explainable temporal game models, incorporating levers for producers to fine-tune for multiple purposes. lukebornn.com/papers/keane_s…
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