Much has transpired in the world of soccer statistics over the past four years since I first published: Possession with Purpose – An Introduction and some Explanations.
- Three years ago I published my Possession with Purpose – Revised Introduction.
- In 2014 the concept was presented at the World Conference on Science and Soccer 2014.
- Last year the concept was published in Europe and just this year another part of Possession with Purpose was presented at the World Conference on Science and Soccer 2017 (Predictability).
- Now it’s time for a new update that hopefully brings more clarity and simplicity?
CLICK this link for my NEW simplified power point presentation update of Possession with Purpose the Total Soccer Index
- The .pdf version should make it easier to print and use as reference material.
Within you’ll find:
- Definition of TSI
- Purpose of TSI
- Premise of TSI
- Parts of TSI
- Leagues / competitions analyzed
- Application of TSI and its parts
- The data for leagues / competitions analyzed
- Observations & conclusions by league / competition as well as reviewing TSI across leagues / competitions
My thanks to all for your support and kind words throughout the years.
For those who want to know:
The most comprehensive victory in the last four years of MLS has been Seattle Sounders beating FC Dallas last year 5 – nil. Here’s some statistics from that game for your consideration:
Possession 62% 38%
Accuracy 87% 80%
Penetration 17% 13%
Creation 13% 7%
Precision 67% 0%
Finishing 63% 0%
- The sum of the parts has greater correlation to points earned than the parts independent of each other.
- Confirming for me that team performance, not individual performance measurements, more accurately translate why a team gets a positive result.
- In other words, the much vaunted Expected Goals only talks to the shot taken itself, it completely ignores the environment surrounding the shot taken. The correlation of Expected Goals to Points Earned has never come close to attaining the amount of correlation TSI has to points earned – or expected points to be earned in the league table.
- Besides, as Dr. Hector Ruiz pointed out to those of us attending the World Conference on Science and Soccer 2014; a true predictability tool for goals scored excludes goals scored and uses the factors leading up to the shot taken to predict a goal scored. That recognition, in and of itself, debunks Expected Goals as a reliable goal predictability tool.
- Team A within one league operates (and sees greater or less correlation to points earned) differently than Team B, C, D, etc…
- Confirming for me that individual statistics, used to create those team statistics (as part of TSI) do not have the same weight / value for all teams.
- Meaning clearances or crosses (used as a measurement in fantasy soccer) for one player, on one team, DO NOT have the same weight/value of clearances or crosses for a different player on a different team.
- Same can be said for passes or shots taken.
- As such, what I’m submitting is that a calculations like Expected Goals and Expected Passes are inherently flawed (to some level) because they assumes the weight / value of all shots or passes from one location to another location are equal.
- With the exception of the Women’s World Cup fewer shots taken, per penetration, sees teams earn more points.
- Less means more…
- Teams with more possession and greater passing accuracy are beginning to earn more points in MLS 2017 than in previous years.
- More means more…
- This trend seems to indicate technical skill levels of players in MLS are improving.
- The lower the overall correlation of the Total Soccer Index to points earned the greater the parity within the league or competition; this also intuits those are less predictable.