Founder @graphingthegame. Previously Performance Analyst for @USAFieldHockey, @UNCFieldHockey, @PacificTigers and @HockeyWales.
Joined November 2010
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Chris Fry retweeted
If Kyle had to bet his life on predicting whether he chooses a red ball or a blue ball from a jar, and he was informed there are 51 red balls and 49 blue, which color should he predict?
Kyle Shanahan says a 51% analytics recommendation won’t convince him to go for it because he gets one shot, not an hour at a blackjack table
“I don’t want to hear about it if it’s 51% of the time we should go for it.”
“As I always say, I’m not sitting here playing Blackjack for an hour with no one else at the table, and eventually I’ll get 51% of it. Like, I have this one try, and I have a feel for it. I’ve been doing it too long.”
“But what I want to know from him, when it’s not a feel, when it, no, this is 98%. We don’t even need to talk about it. So we don’t need to talk about it. Tell me when it’s that, and I’ll just do it.”
Chris Fry retweeted
This is a good example of how physical data can be often misused in football.
This post has 1.1m views and tentatively insinuates that because Manchester United don’t sprint much out of possession, that’s a bad thing.
Under Michael Carrick, United generally defend in a mid-block.
They will naturally accumulate less OOP sprint distance than a Bournemouth side whose defensive model involves pressing much more aggressively.
Look at the bottom-left quadrant. Many of those teams use structures designed to control space rather than constantly press at high intensity. It’s about running at the right moments.
Physical output is generally a consequence of how you play. Or at least, how you want to play.
Additionally, after the longest World Cup in history, it's another long season ahead for clubs and players in European competitions, and who go deep in domestic cups.
Managing the season physically will be key.
Compared to coaches poll, my Elo model values Miami higher, and Wake Forest lower.
NFHCA 2026 Division I Preseason Coaches Poll is here! See full rankings: nfhca.org/polls/division-i/
Probably more artful than insightful, but with NFL season starting soon I wanted to visualize ball starts like offensive drives
Chris Fry retweeted
If anything is abundantly clear, it’s that Argentina didn’t deserve to be in the final and that they progressed as far as they did because they were the beneficiaries of repeated instances of match fixing & FIFA corruption
Chris Fry retweeted
Hello Elo. Our approach to quantifying team strength:
graphingthegame.com/blog/hel… #NCAAFH #SportsAnalytics
I agree, but coaches/players/general audience seem to like them. AI dashboards are also hideous (seen bars not match values, wrong flags/logos, just generally look poor).
I see the disease of radar plots afflicting the nascent cricket analytics field, which has taken to blindly aping ideas from football.
Radar plots are useless and misleading for most information (except periodic/geometric). Say no to radars, read this:
pymc-labs.com/blog-posts/rad…
Chris Fry retweeted
In 2 of the last 3 years, our clients have led the nation in NCAA D1 corner conversion 🎯
Chris Fry retweeted
UTILIDADE PÚBLICA: para quem gosta de dados, estatísticas, e números, ou apenas gosta de Futebol, a FIFA está disponibilizando dados físicos e técnicos de todos os jogos da Copa do Mundo.
link: fifatrainingcentre.com/en/fi…
Chris Fry retweeted
Recently completed a project helping Colgate migrate their coding and reporting windows to MyVideoAnalyser ahead of the fall season.
Beyond replicating existing workflows, we improved coding efficiency and upgraded visualizations.
Workflow > software.
Chris Fry retweeted
Adopting Claude speak in my regular life, episode 1:
Partner: Did you do the dishes tonight?
Me: Yes they're done.
Partner: Why are they still dirty?
Me: You're right to push back. I didn't actually do them.
Many congratulations to @allison_k13 - first trip as analyst, and first medal secured. Now to go get that gold!
