Man, I swear I spent the entire weekend just fighting with spreadsheets over this one topic. It all started when my mate, Tony, wouldn’t shut up about how Spanish teams always have better discipline than the Portuguese sides. He was absolutely convinced that even a mid-table La Liga team like Real Betis would be far more clinical and less prone to foul play than Vitória SC, even in a heavy pressure game or a friendly. I told him he was full of it, but when I tried to pull up the concrete evidence to shut him down, I hit a massive wall of garbage information.
I needed to prove him wrong using actual numbers, specifically focusing on goals scored by their primary threats and the sheer volume of red cards handed out in their head-to-head history, especially those matches where the stakes were bizarrely high, like early European qualifying rounds or preseason tournaments. I didn’t want the easy answer; I wanted the granular truth.
The Initial Struggle and The Dive into the Deep End
My first move was the lazy one. I fired up my browser and just started punching in keywords. What a complete waste of time. I waded through five pages of search results, hitting forum posts, dodgy betting sites, and Wikipedia pages that only offered vague final scores. The stats I needed—the minute a goal was scored, the exact player who earned a card, the nature of the foul—were either missing or contradicted by the next site I clicked on. I realized immediately that I couldn’t trust the surface level summaries. I had to build the data myself.
I remembered I had an old, clunky Python setup I used years ago for tracking commodity prices, so I dragged it out. I tried connecting to a few well-known, free sports data APIs, figuring I could just ask them for the match reports. Nope. They all demanded sign-ups, API keys, or straight-up cash. I slammed my laptop shut in frustration after two hours of failed authentication attempts. That was never going to work for a quick weekend project.
Building the Beast: The Manual Aggregation Process
I switched gears entirely. If the machines wouldn’t give me the data, I was going to rip it out myself. I opened up three different highly reputable (but agonizingly hard to navigate) European football history sites—the kind that look like they were designed in 1998 but keep meticulous records. I designated one primary source for match dates and scores, and the other two for cross-referencing the player actions.
I started a massive Google Sheet, organizing columns for: Match Date, Competition, Final Score, Vitória Goal Scorer (and minute), Betis Goal Scorer (and minute), Total Yellows, and crucially, Red Cards (Direct or Accumulative).
The goals data was tough enough. I scoured every match report, focusing on who the top five scorers were for each team in that time period and seeing how many of their goals came against this specific opponent. It was less balanced than Tony thought, which was my first small victory.
But the red card data? That took me into insanity territory.
- I had to differentiate between a straight red card—usually for a moment of madness or a blatant denial of a scoring opportunity.
- Then I tracked down those pesky second yellow cards that lead to a dismissal. This is where the story truly lies. It shows persistent, often petty, fouling, which points to a lack of tactical control.
- I compared the discipline records meticulously. If one site said Player X got a yellow in the 45th minute, but another said 47th, I went digging for a third source or a match summary video to confirm. I spent hours calibrating these minor discrepancies.
I logged everything. My eyes were burning, and my wrist was definitely screaming at me, but I was building an analysis that no quick search engine result could match. I forced myself to complete the data entry for thirteen historic matchups.
The Discovery and The Proof
Once the data was all sitting clean and ready, I ran the numbers. I calculated the average red cards per match for both teams against each other. I charted the top three goal scorers and their conversion rates in these specific high-tension games. I found out two things that completely busted Tony’s theory:
First: While Real Betis did edge out Vitória SC on total goals, the goal difference was entirely down to two highly prolific Betis strikers, who were responsible for nearly 70% of their total goals in the series. Remove those two superstars, and the scoring becomes highly sporadic and unpredictable. It showed reliance, not pure clinical superiority.
Second: The red card data was startling. Vitória SC actually averaged fewer direct red cards, showing they kept their cool better in critical moments. However, Betis held a slight edge in accumulating yellow cards leading to reds, demonstrating a subtle, creeping lack of discipline over the course of the match. Tony thought discipline meant no huge fouls; I proved it meant maintaining control for 90 minutes.
I packaged up the results, exported the spreadsheet, and just sent it to Tony with a simple message: “Read this. You owe me a beer.” The sheer weight of the custom-aggregated data was undeniable. It was a massive effort just to win a stupid argument, but man, collecting that raw truth felt absolutely fantastic.