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Run-in analysis

SoccerSTATS.com - updated on: 15 Jun 2020


Objective

The run-in analysis table aims at helping visualize:

  • how difficult each team's played matches might have been
  • how difficult upcoming matches could look like.

You may also want to read more contextual information regarding that table on the following page: Evaluating matches difficulty-level


Description

The table lists team ranked by points and shows, for each team:

  • Games played
  • Points
  • Points Per Game
  • Average PPG of played opponents
  • Average PPG of remaining opponents
  • Difference between both average PPG values
  • Average PPG of next 4 opponents

Below is a view of some of the first columns of the run-in analysis table, including average Points Per Game values for each team's opponents.




Calculations

Points Per Game (PPG)

That value is calculated based on the number of points for each team, divided by the number of matches played by the team.

Average PPG of played opponents

Average value calculated based on the away PPG values of each opponent played by the team at home, and on home PPG values of each opponent played by the team in away matches.

Average PPG of remaining opponents

As with the played opponents, the average value is calculated based on the away PPG values of each future opponent to be played by the team at home, and on home PPG values of each future opponent to be played by the team in away matches.

Difference between both average PPG values

That value is calculated for each team, based on the difference between the "Average PPG of played opponents" value and the "Average PPG of remaining opponents" value. The Difference column will show a value that can be positive, neutral or negative. A positive Difference value means that the team's upcoming matches are featuring oppositions that have a lower combined PPG than that of the oppositions already played.

Average PPG of next 4 opponents

Average value calculated based on PPG value regarding the next 4 opponents to be played by each team. Again, those calculations take into account the away PPG values of each future opponent to be played by the team at home, and the home PPG values of each future opponent to be played by the team in away matches.




Example

Let's assume that a team has 4 matches left to play in the regular season:

  • Match #1 to be played at home against Opponent A
  • Match #2 to be played away against Opponent B
  • Match #3 to be played at home against Opponent C
  • Match #4 to be played away against Opponent D

The value calculated for the remaining opponents' PPG in that example will be the average of the away PPG of Opponent A, the home PPG of Opponent B, the away PPG of Opponent C, and the home PPG of Opponent D.

The detailed view of each opponents Points Per Game values can be displayed by hovering the mouse cursor above each average opponent PPG value, as you can see in the example of the German league on the Bundesliga run-in analysis page.




Avoiding pitfalls

Such an approach may look quite straightforward on paper however it also comes with its caveats and weaknesses. For example, the closest we are to the beginning of the season, the less data we have to calculate the Points Per Game recorded for each opponent.

Assuming the current title holders have started their season with two draws against strong teams, that approach would label such team as a mere 1.0 PPG opponent. This could make the relative performances of the teams having won a point against them look weaker than they actually could be.

This is why paying attention to opponents PPG to evaluate a team's performance makes more sense as more matches have been played in the season.

Another pitfall would be to deem a team's PPG consistent whether calculated based on home games or away games. That may sound obvious - although there are a few teams that tend to play in the same way at home or away while obtaining similar types of results - but at the end of the season we often find that the majority of the teams typically end up picking up more points on average in home matches than in away matches.

To obtain a more realistic average PPG value, the calculations in the run-in analysis table are based on the home PPG of opponents that the team has faced away, and the away PPG of the opponents played at home.



 ENGLAND  Premier League
 Liverpool 38 99
 Manchester City 38 81
 Manchester Utd 38 66
 Chelsea 38 66
 Leicester City 38 62
Premier League stats

 ITALY  Serie A
 Juventus 38 83
 Inter Milan 38 82
 Atalanta 38 78
 Lazio 38 78
 AS Roma 38 70
Serie A stats

 SPAIN  Primera Division
 Real Madrid 38 87
 FC Barcelona 38 82
 Atletico Madrid 38 70
 FC Sevilla 38 70
 Villarreal 38 60
Primera Division stats

 FRANCE  Ligue 1
 Nimes 0 0
 Bordeaux 0 0
 Angers 0 0
 Brest 0 0
 Dijon 0 0
Ligue 1 stats

 GERMANY  Bundesliga
 Bayern Munich 34 82
 Dortmund 34 69
 RB Leipzig 34 66
 Monchengladbach 34 65
 Leverkusen 34 63
Bundesliga stats

 NETHERLANDS  Eredivisie
 Ajax Amsterdam 25 56
 AZ Alkmaar 25 56
 Feyenoord 25 50
 PSV Eindhoven 26 49
 Willem II 26 44
Eredivisie stats








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