Man, I woke up this morning and I knew I had a job to do. It wasn’t about work, not the kind that pays the bills anyway. It was about settling a score. You see, I had this discussion with my nephew over the weekend, young smart-alec, fresh out of college, thinks he knows everything about ‘data aggregation.’ We were arguing about the last Deportivo Alavés vs Villarreal CF match, and specifically, about how the midfield transition played out.
I insisted, based on just watching the game, that Alavés was completely suffocated in the middle third, and their usual wide passing plays were nonexistent. He just smirked and said, “Uncle, if you can’t back it up with a completed passing accuracy map for the second half, it’s just noise.” That challenge stuck with me. So, today was the day I went hunting. I needed those numbers. I needed to shove those specific, niche stats right back at him.
My First Steps: Hitting the Big, Useless Sites
I started where everyone starts, right? I banged the names of the teams and ‘stats’ into the search box. Instantly, I got the big global sports providers. That was a waste of ten minutes. They give you the easy stuff. They give you the final score, the goal scorers, and maybe who got a yellow card. I didn’t need that fluff. I needed the guts of the match. I needed to see exactly where those passes went wrong.
I opened three different major international sports pages. Each one just repeated the same basic lines: 1-0 win for Alavés. Great. But where was the possession breakdown by quarter-hour? Where were the touches in the opposition box? Nowhere to be found. They treat football stats like a box score from a baseball game—simple and clean. But this is La Liga; it’s messy, it’s tactical, and I needed the deep dive.
Digging Deeper: Going Straight to the Source
I realized quickly I was barking up the wrong tree. If I want league-specific data, I need to go league-specific. My second move was navigating to the official home of Spanish football. I figured, if anyone has the raw data, it’s the organization running the show. This is where the practice really started to get messy.
I wrestled with their website’s navigation for a solid while. They organize things by ‘match day’ and then ‘fixture,’ and it took me a few clicks to stop looking at the current week and go back two weeks to find the specific game I cared about. Once I finally clicked on the match center, things got marginally better. They did list more detailed data, but it was still presented very clunkily. I had to manually scroll through tables.
What I managed to pull out here was the intermediate stuff:
- Total Shots: Villarreal had more (14 vs 10).
- Shots on Target: Alavés was more clinical (3 vs 2).
- Corners: Villarreal dominated that count (7 vs 2).
See? Those numbers already started proving my point. Villarreal was attacking, but they weren’t penetrating. My nephew’s argument was already weakening, but I still lacked the smoking gun: the detailed passing data in the defensive third.
The Final Hunt: Finding the Granular Details
This is where I had to get smart, realizing that the league website gives you the summary, but the true data nerds are somewhere else. I started searching not for ‘stats’ but for ‘match analysis Deportivo Alavés Villarreal.’ This strategy shift immediately paid off. I found a couple of websites run by people who are obviously obsessed with the positional data—the folks who track every single player movement.
I had to spend time filtering through several different sites. Some are fantastic for xG (Expected Goals), which is good, but I needed passes. I kept clicking, ignoring the flashy graphics, until I landed on one that specialized in positional passing maps. The site was ugly, honestly, just white background and dense tables, but it was exactly what I needed.
I drilled down into the second-half data. I extracted the numbers showing Alavés’s defenders attempting long clearances rather than short, precise passes. I calculated their total pass success rate in their own half. And guess what I found? In the critical 45-75 minute window, Alavés completed less than 65% of their passes originating from their back four. That’s chaos, not control.
It took me nearly two hours of clicking, reading tables, and cross-referencing, but I had the proof. I just sent him a screenshot of that specific table this afternoon. No text, just the raw, ugly numbers.
Why Did I Even Bother?
You might be thinking, why go through all this trouble for a Spanish league match that happened two weeks ago? This whole mission wasn’t really about Alavés or Villarreal. It was about the principle.
I have this slightly embarrassing, long-standing rivalry with my nephew over technology and information access. See, when I was trying to get into this field, finding reliable sports data was next to impossible. I used to have to wait for the local newspaper to print grainy black-and-white tables days after the fact, and they were always full of typos. The internet promised a sea of information, but sometimes, the right information is still buried deep under a mountain of useless headline stuff.
A few years back, I actually got fired from a project management job because I failed to pull some obscure market data quickly enough for a client meeting—data I later found out was only available through a paid, specialized terminal I didn’t have access to. That experience taught me to never take no for an answer when hunting for data. If the information exists, you can find it. It might take three layers of searching and cross-referencing, but it’s there.
So, when my nephew told me my observation was ‘just noise’ because I couldn’t instantly produce the exact numbers from a high-tech platform, I took it personally. This whole search was just me proving that experience and persistence beat having the fanciest college degree, especially when you are just trying to find some very specific football stats.