Do you mean "after 2016" as in from 1 January 2017 onward, or do you mean from the 2016–17 season onward? I don’t have live match data here, so I can’t recompute the counts myself unless you either (a) provide the match list/dataset or (b) allow me to fetch data (I can’t browse from this environment).
If you want to filter the original dataset yourself, here are clear ways to get the post‑2016 head‑to‑head counts (La Liga vs Premier League):
1) Definition: keep only matches where one team is from La Liga and the opponent is from the Premier League, and where match date > 2016-12-31 (or >= start of 2016–17 season if that’s what you meant).
2) Excel / Google Sheets
- Ensure you have columns: Date, HomeLeague, AwayLeague, HomeGoals, AwayGoals.
- Add a filter: Date > 2016-12-31.
- Filter rows where (HomeLeague = "LaLiga" AND AwayLeague = "PremierLeague") OR (HomeLeague = "PremierLeague" AND AwayLeague = "LaLiga").
- Add a column Result with formula (example in Excel):
=IF(HomeGoals>AwayGoals, HomeLeague, IF(HomeGoals<AwayGoals, AwayLeague, "Draw"))
- Use COUNTIF or a PivotTable to count how many rows = "LaLiga", how many = "PremierLeague", and how many = "Draw".
3) SQL (example assuming table matches with date, home_league, away_league, home_goals, away_goals)
SELECT
SUM(CASE WHEN home_goals>away_goals AND home_league='LaLiga' THEN 1
WHEN away_goals>home_goals AND away_league='LaLiga' THEN 1 ELSE 0 END) AS la_liga_wins,
SUM(CASE WHEN home_goals>away_goals AND home_league='PremierLeague' THEN 1
WHEN away_goals>home_goals AND away_league='PremierLeague' THEN 1 ELSE 0 END) AS premier_wins,
SUM(CASE WHEN home_goals=away_goals THEN 1 ELSE 0 END) AS draws
FROM matches
WHERE date > '2016-12-31'
AND ((home_league='LaLiga' AND away_league='PremierLeague') OR (home_league='PremierLeague' AND away_league='LaLiga'));
4) Python / pandas
import pandas as pd
df = pd.read_csv('matches.csv', parse_dates=['date'])
df = df[df['date'] > '2016-12-31']
mask = ((df['home_league']=='LaLiga') & (df['away_league']=='PremierLeague')) | \
((df['home_league']=='PremierLeague') & (df['away_league']=='LaLiga'))
df = df[mask]
def winner(r):
if r.home_goals > r.away_goals:
return r.home_league
elif r.home_goals < r.away_goals:
return r.away_league
else:
return 'Draw'
results = df.apply(winner, axis=1)
counts = results.value_counts()
print('LaLiga wins:', counts.get('LaLiga', 0))
print('Premier League wins:', counts.get('PremierLeague', 0))
print('Draws:', counts.get('Draw', 0))
If you share the match data (CSV or key columns) or confirm which exact start date/season you want, I’ll compute the post‑2016 counts for you.