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Why Visuals Matter More Than You Think
The beginner’s guide to avoiding visualisation traps — and how to fix them fast
Aug 7
•
MartinOnData
14
2
July 2025
Football Data Wrangling (in plain English)
Why 80 % of data science is about wrangling—and the Python shortcut that makes it painless
Jul 31
•
MartinOnData
14
7
Football Data Collection (in plain English)
The 4 Ways to Collect Football Data—and the Best Starting Point for Beginners
Jul 24
•
MartinOnData
30
2
How Wrong Are Football Pundits?
16 Years · 5,582 Lawro & Sutton Picks — What Would Your Bankroll Look Like if You’d Followed Every Single One?
Jul 17
•
MartinOnData
27
7
You Shall Not Pass
Ranking elite shot-stoppers with xGOT—plus the World Cup & Euro champions who quietly sit among the worst.
Jul 10
•
MartinOnData
20
2
Shooting Royalty
Ranking elite ball-strikers with xGOT: how much they outshoot the average finisher and which big names fall short
Jul 3
•
MartinOnData
20
June 2025
The Myth of the Clinical Striker
Why even Robert Lewandowski does not beat his xG, why that doesn’t make him wasteful, and what 11 seasons of data reveal about true finishing outliers.
Jun 26
•
MartinOnData
31
8
xGChain & xGBuildup 101
What each metric measures, which gap they fill (left by xA and xAG), which players have posted the best build-up numbers this season, and how to pull…
Jun 19
•
MartinOnData
11
6
Expected Assists (xA) 101
What xA measures, why people confuse it with xAG (and why you shouldn't), how to uncover hidden creative talent, and how to pull tons of xA data with a…
Jun 12
•
MartinOnData
13
10
Expected Assisted Goals (xAG) 101
What xAG measures (and what it doesn’t), the key blindspots to watch out for, how it's different from expected assists (xA), and how to pull tons of xAG…
Jun 5
•
MartinOnData
11
1
May 2025
Expected Goals on Target (xGOT) 101
What xGOT measures, how it fixes xG’s blind spots, how analysts rely on it, and a Python shortcut to bulk-download xGOT data
May 29
•
MartinOnData
13
10
Expected Goals (xG) 101
What xG really measures (and what it doesn’t), the key misconception that trips up even seasoned pros, why its loudest critics are mostly wrong, and how…
May 22
•
MartinOnData
32
11
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