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S3C6 - Visualizing Top Football Teams in History

Visualizing Top Football Teams in History
Visualizing Top Football Teams in HistoryLevel: MediumAs the 2024 European Football Championship (UEFA) unfolds, let's dive into football historywith a data challenge. Today you are asked to create a data app that allows users to check, forany timeframe, what the top three teams with the most football victories were. Who are the topthree teams of all time? And who were the top three teams in the 1980s? PreparationGet goal difference, years, and home/away outcomes pivot from wide to long & Aggregate Instead of having home & away teams/scores on different columns, we put them into 1 columnAnd SUM up the total wins, loses, draws for each {team, tournament, year} tuples Clean Set missing values to 0 Data App ApproachTo answer the question, I needed to know what & where does a win mean? E.g. is it absolutewins or winning percentages? Do friendlies or Confederation Cups count? How about teamsthat win all of their very few matches? Why not use it all? Start with dates, filter by wins and tournaments, then let the user decide ifthey want to get the top 3 teams by absolute wins or winning percentage. Apart from just returning the top 3 teams, we should provide more context for each team. 1. How many wins, losses, and draws? 2. How many tournaments did they take part in? 3. What's their best win and worst loss? 4. What's the breakdown of their WLD?And, how did the other teams do? How 1. Build 2 datasets: A) Aggregated dataset of wins, losses, draws for each team and tournament for specified duration B) Add on features to original dataset: home, away outcomes; goal difference2. Use dataset A to get the top 3 winners, and rest of the pack info3. Use dataset B to get best & worst match details for each of the 3 winners 4. Display results in dashboard Node 1Node 6Node 7Node 8Node 10Node 11Node 12Node 13Node 14Node 16Node 17Node 18Node 19Node 20 CSV Reader Rule Engine Rule Engine Column Filter Column Renamer Column Renamer Concatenate String to Date&Time Extract Date&TimeFields Pivot Math Formula Column Filter Column Renamer Missing Value data app Visualizing Top Football Teams in HistoryLevel: MediumAs the 2024 European Football Championship (UEFA) unfolds, let's dive into football historywith a data challenge. Today you are asked to create a data app that allows users to check, forany timeframe, what the top three teams with the most football victories were. Who are the topthree teams of all time? And who were the top three teams in the 1980s? PreparationGet goal difference, years, and home/away outcomes pivot from wide to long & Aggregate Instead of having home & away teams/scores on different columns, we put them into 1 columnAnd SUM up the total wins, loses, draws for each {team, tournament, year} tuples Clean Set missing values to 0 Data App ApproachTo answer the question, I needed to know what & where does a win mean? E.g. is it absolutewins or winning percentages? Do friendlies or Confederation Cups count? How about teamsthat win all of their very few matches? Why not use it all? Start with dates, filter by wins and tournaments, then let the user decide ifthey want to get the top 3 teams by absolute wins or winning percentage. Apart from just returning the top 3 teams, we should provide more context for each team. 1. How many wins, losses, and draws? 2. How many tournaments did they take part in? 3. What's their best win and worst loss? 4. What's the breakdown of their WLD?And, how did the other teams do? How 1. Build 2 datasets: A) Aggregated dataset of wins, losses, draws for each team and tournament for specified duration B) Add on features to original dataset: home, away outcomes; goal difference2. Use dataset A to get the top 3 winners, and rest of the pack info3. Use dataset B to get best & worst match details for each of the 3 winners 4. Display results in dashboard Node 1Node 6Node 7Node 8Node 10Node 11Node 12Node 13Node 14Node 16Node 17Node 18Node 19Node 20 CSV Reader Rule Engine Rule Engine Column Filter Column Renamer Column Renamer Concatenate String to Date&Time Extract Date&TimeFields Pivot Math Formula Column Filter Column Renamer Missing Value data app

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Created by: Dreamcore
Created at: 2024-06-22
On NodePit since: 2024-06-25
Last update: 2024-09-16
Created with KNIME version: v5.2.5
Tags: just knime itstock trendsJKISeason3-6

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