Applied ETL operations to NBA datasets by using R
Created a shiny app of Top 5 Leagues' players
Line graph of selected players through selected seasons with the option of metric to plot
Used FBref.com data
Shotmap of selected players with body part and shot type granularity by using understat data
Pass map of selected players

Intro to Advanced Metrics of Soccer by Top 5 Leagues 2021-22 Season

The Motive and Dataset

Understand the game of soccer by additional metrics in addition to existing ones which are Expected Goal, Expected Assist, Shot Creating Action and Goal Creating Action and their values in terms of per 90 mins.
To analyze the performance of both teams and players of Top 5 Leagues in 2021-22 season in terms of xG, xA, SCA, GCA
FBref.com data of Top 5 Leagues in 2021-2022 season is extracted by using worldfootballR package in R in both team and player level

Measures the quality of a chance by calculating the likelihood that it will be scored
xG per 90 min(xG_p90) and Goal per 90(G_p90) min seems positively correlated
Bayern Munich has the highest xG_p90 and G_p90. Liverpool and Manchester City have similar values in both metrics.
Those 3 teams have way higher values compared to other teams
Top players based on xG_p90 from each leagues are Robert Lewandowski and Erling Haaland transferred to Barcelona and Manchester City after that performances.

Expected assist measures the likelihood that a given pass will become a goal assist.
It is calculated regardless of whether the receiver takes a shot or not. It considers different parameters such as
- Type of pass (e.g., cross, non-cross, header, through ball etc)
- Pattern of play (e.g., open play, corner, free kick, throw-in etc)
- Location of where the pass is received
- Location of where pass is made from
- Distance of the pass
xA per 90 min(xA_p90) and Assits per 90 min(A_p90) are positively correlated
Thomas Müller has the highest value of both xA_p90 and A_p90
Seeing De Bruyne, Trent Alexander, and Salah in the top of Premier League is not suprising . They might be most creative players in the Premier League

Shot Creating Actions help to understand which player (or a team) is involved mostly in a team(or a league)
Can even be considered as a metric indicates creativeness of a player or a team
Offensive actions directly lead to a shot such as passes, dribbles and drawing fouls constitute Shot Creating Actions
Manchester City was the most creative team in the Premier League while Norwich City and Burnley were the least creative teams
In addition to the clubs’ performance the most creative player of Premier League is De Bruyne based on SCA_p90 values. Payet, Messi, Neymar, and Vinicius Junior unsurprisingly are at the top
In GCA instead of measuring the involvement per shot, the involvement per shots that lead to a goal are measured
Bayern Munich, Liverpool, and PSG are at the top as in the other metrics

To analyze the teams and players in terms of passing performances
- In match level
- Throughout the whole tournament
To obtain and interpret the passing graph of the best passer player
Free World Cup data of Statsbomb is fetched including all 64 games in the competition by using StatsBombR package with RStudio

Spain has the highest success rate among all teams while Iran has the lowest value with 90% and 60% respectively
Among the players who has at least 100 pass attempts, Mousa Dembélé for Belgium has the highest pass success rate with 96%.
Igor Akınfeev has the lowest pass success rate among the players with at least 100 pass attempts with 42%
Ante Rebic for Crotia has the lowest pass success rate among players with at least 100 pass attempts after goalkeepers are excluded wşth 51%
In terms of math level data, Thiago Alcantara for Spain has the highest success rate against Morocco in which he had only 1 unsuccessfull pass attempts out of 88

Advaced Metrics of Soccer

Shiny App of Top 5 Leagues

Evolution of 3-Pointers in NBA

Passing in WorldCup 18