Super-subs, the sub effect, pinch hitters and more. Players like Jermain Defoe (23 Premier League goals as a sub), Nwanko Kanu (17), Ole-Gunnar Solksjaer (17) and Javier Hernández (14) have done a lot of work to promote this terminology over the past decade(s). But how certain are those concepts? Are their players that consistently score more goals coming on as a sub? And what is the general tendency; do subs, fitter than starters when they come on, score more goals then starters? Let’s see.
I have been writing quite a lot on Premier League substitutions lately and here is an overview of the posts:
- Premier League substitutions: 1. What and When?
- Premier League substitutions: 2. The Decision Rule
- Premier League substitutions: 3. Do subs score more than starters?
- Premier League substitutions: 4. The double-substitution at half time
- Premier League substitutions: 5. Olivier Giroud (draft)
- Premier League substitutions: 6. Jürgen Klopp
ALL DATA COMES FROM DATAFACTORY
Data that is discussed in this blog was described here.
Replicating Myers’ study to substitutions
WHY am i digging this up?
Although there is seemingly very little a manager can do during a game and substitutions seem to be their main way to have an impact on the game, there is very little discussion about them. When getting the data on Premier League subs, as discussed before, I remembered some statements from the book “The Numbers Game” where a study from Myers is mentioned. I wanted to see how much of his conclusions hold true over a larger time period in the Premier League (the dataset from Myers covers only one season).
This blog was written on 26/4/2015, after Round 35 of the Premier League 2015/16.
You know that situation when you leave the pitch when your team is winning 2-1? At the end of the 90 minutes the opponents have turned everything around and won the match 2-3. Stubborn as you are you tell your manager and teammates that you DID win the game, having left the field in a winning situation.
Taking those situations into account we can calculate the effectivity of each player in his team: how many goals does his team score when he is on the pitch compared to when is not present? And what impact does he have on the total goal difference?
All (or at least a lot) statistics for Messi’s first 500 career goals. He scored his 500th at the Camp Nou against Valencia on 17/4/2016.
For the last couple of months I have been (slowly) working on an expected goals model for the Argentine league and I am very happy to finally present a first version here. I will explain the basics of the model here and I will also try to show some of the underlying numbers, something I haven’t seen so much in posts from others.
For the ones that want to skip this blog and just see the results: click here.
Seeing Cristiano Ronaldo score yet another insignificant hat-trick against Espanyol last night I wondered how many of his goals actually matter. And with “matter” I refer to goals that actually have a clear impact on the game and are not just goals in the margin (when already winning 2-0 for example). Within the same effort I could might as well check the same statistic for all players in Europe’s top 4 leagues. So that’s what I did and I also added the goal data from the Champions League and Europa League.
In another blog I am keeping track of my work on a expected goals model. All variables and assumptions are largely based on other people’s models, but here I’ll discuss something I have not yet seen (or missed..): the underlying shot numbers. While working on the analysis for the bigger model I found a lot of interesting statistics on the shot conversion rate (goals/shots) per, for example, game state, number of shot in the game, time in game, and more. Where for the model I will dive deeper into the numbers and use statistical testing these are largely just descriptive tables. But no tests, no significance levels. And yes, each of the paragraphs would need a blog of its own..!
It’s the most wonderful time of the year and the 10 Premier League games on Boxing Day make it even more beautiful! This is the schedule:
You know that situation when you leave the pitch when your team is winning 2-1? At the end of the 90 minutes the rival have turned everything around and won 2-3. Stubborn as you are you tell your manager and teammates that you DID win the game, having left the field in a winning situation.
Taking those situations into account we can calculate the effectivity of each player in his team. I did this for the Argentine Primera División. Starting simple, this is the general table of players: