As most of you found out this afternoon, I wasn’t able to liveblog the Soccer Analytics panel on the site because of connectivity issues in the main venue. I did take notes of the discussions in the Soccer Analytics panel and I’m reproducing them here.
I warn you that while I tried to capture what the panelists were saying, these are paraphrases and not guaranteed to be 100% accurate. At any rate, here we go:
- Albert Larcada (ESPN)
- Chris Anderson (Soccer by the Numbers)
- Blake Wooster (Prozone)
- Jeff Agoos (MLS)
- what are next steps?
- how can data be used throughout industry?
* what’s next step?
(Chris) where have we been? misnomer to describe this as “revolution” — more an “evolution”
soccer has more history in analytics than people think
Reep’s coding system goes back to 1950 (notation system — all events in pitch), worked with teams in 1950s-1980s
biggest advancement in analytics: cost of data going down, accessibility increasing
gives MCFC Analytics as example
more people writing about it in soccer analytics blogosphere
clubs work hasn’t moved the needle
* why are clubs not keeping pace?
(Blake) cultural challenge exists, persists
regulation driving more interest in due diligence, data usage
generational shift as well
Mike Hughes notational analysis –> Blake, Gavin Fleig
mentions generations —
X: access to technology
Y: making things faster, better
Z: generate insight, making things easier
(Albert) more data available — more data you must visualize
huge on media side — focus on telling stories
(Jeff) more data isn’t always better, ref Silver’s book (The Signal and The Noise)
owners see it as expense or investment
* are analytics more valuable in MLS?
(Jeff) to a point, but there’s cost-benefit equation to consider
(Albert) real-time shot charts, heat maps (Trumedia)
some heat maps actually used on SportsCenter (Messi vs Ronaldo)
(Jeff) challenge is capturing context
(Blake) diff b/t what’s important, and what’s interesting
(Albert) important to remember that SportsCenter audience =/= audience in room
telling the story
(Chris) technology used to communicate story very important
have moved quickly from zero data –> drowning in data
talking about Mourinho’s use of data
(Blake) discussing about Mourinho’s match preparation through data
no-stat all-stars more common in soccer than you think
“most important things are the hardest to measure”
(Albert) is there a player in Europe who is like Shane Battier?
(Blake) IQ — EQ — CQ (contextual intelligence)
(to Jeff) Do you wish you had more access to data ten yrs ago?
(Jeff) absolutely — new players growing up in culture where data is accepted
more tools, visualization critical
* does soccer world lag behind bball on analytics?
(Chris) fair point — “going 0 to 100 in data is scary to lots of clubs”
hard to remember that we’re not dealing with North American sports
– winners don’t feel need to innovate
– relegation battlers too risk averse
– middle runners feel they should finish in top 6 anyway
(Blake) short-termism rampant
manager lifespans extremely short
75% of managers will coach maximum of 75 matches
(Jeff) management decision — captive to short-term concerns
half of league have invested in analysis / BI teams
advance scouting, sports science, academy
(Albert) what is analytics? is it video? data viz? stats/CS?
use of analytics is very gray
(Chris) proving the ROI is very hard
element of trust hugely important
element of randomness is HUGE in soccer
(Blake) we need success stories more than anything else
(Chris) we’re now on Liverpool 2.0 now
big announcement at beginning of LFC 1.0 not productive long-term
(Albert) nature of game not designed for analysis, lots of noise
baseball “is a PhD’s dream” (me: not sure I agree)
(Blake) mentions case of Michu (one who got away) — Type II error
15 goals in Spain, very low transfer fee for Swansea, missed by six scouts
(Jeff) coaches are doing measurements all the time, just in a different way
(Chris) let’s not pile on coaches
dealing with lots of tasks, limited resources
lots of fads in the industry
just b/c we think it’s demonstrably useful doesn’t mean it will be
(Blake) challenge and opportunity
if coach doesn’t get it, it’s our fault for not communicating it
(Chris) we pretend that coaches know how to win football games
not clear that soccer analytics knows what wins games
what is theory of what produces wins in football?
clubs: intuitive non-verbal theory
* what are new metrics that should fans be more familiar with to help game-watching experience?
(Albert) timely stats, fans get info when they want it
(Chris) best player debate not all that interesting
favorite metrics are ones hardest to measure –> defensive metrics
prefers team performance
(Blake) game intelligence
(Albert) certain skillset required
(Chris) difference between prediction and explanation
prediction: interest from bettors, media
explanation: interest from clubs
(Jeff) for MLS, how do we compare ourselves to other leagues
measure everything –> indices of match performance
(Chris) soccer’s unique in terms of “right way” to play
what does it mean to be an attractive league?
(Jeff) attractive vs compelling
* Bundesliga and MLS have bought data and made available to clubs. Premier League hasn’t. Why?
(Blake) used to be resistance in PL, less so now
do same in Qatar, Poland, etc
more cost effective to make central investment