The Messy Start: Why I Needed These Ajax/Frankfurt Numbers
Look, I ain’t some fancy professional analyst with a dedicated server farm. I’m just a guy who likes looking at the receipts after a game is done. And boy, did I need the receipts after that Ajax vs. Eintracht Frankfurt clash a while back. This wasn’t just casual viewing; this was about proving a serious point.
I had this argument with my mate, Dave. Dave’s always talking big about strikers and flashy goalscorers, focusing only on the output. He kept banging on about how the entire game was completely dominated by one forward from Ajax, claiming all the key attacking flow went through him. I watched the match, and I was pretty sure Player Y—the defensive midfielder, the guy who just covers ground—was actually doing all the foundational grunt work and the heavy lifting, even if he wasn’t the one netting goals. Dave laughed and bet me a substantial sum of money that I couldn’t prove him wrong with solid, irrefutable numbers showing that the hidden engine was the most crucial factor. So I had to stop watching like a fan and start digging like a detective.
Digging Up The Dirt: The Manual Scrape
First thing I went and did was ignore any pundit summary or highlight reel. I knew I wouldn’t find the truth there. I wasn’t using any expensive, paid subscription tool either. I just opened up three different free statistics websites, threw them onto my screen side by side, and started comparing notes. It was an absolute mess. It always is when you try to merge different sources.
One site would list something like “total dribbles completed,” another would call it “successful take-ons,” and a third would just vaguely say “beat man.” I had to create a master key to translate everything into a single, usable metric. I threw all this information into a crude spreadsheet I quickly built up on my laptop.
My goal wasn’t to celebrate goals; it was to prove who was actually the key player—the engine, the guy holding the whole thing together—not just the one who got the glory. I decided early on that I needed to track three non-glamour metrics for every player who logged more than 60 minutes:
- Ball Control/Retention: I calculated this by adding up total successful passes in the midfield and opposition half, plus total touches. This told me who was actually influencing possession.
- Defensive Contribution: I focused on tackles won, successful interceptions, and clearances made under pressure.
- Creative Pressure: I searched hard for statistics on high-pressure turnovers forced or key passes that didn’t result in an immediate shot. This proved who was generating the chaos.
I spent maybe four solid hours just manually copying and pasting every relevant number I could find for every player. It felt exactly like I was back in school doing homework, except this homework had a decent financial prize attached to it, and my reputation for being right was on the line. I cross-referenced the numbers twice, because, inevitably, Site A and Site B always had slight disagreements, usually on things like “ground duels won.” I just averaged the discrepancy and decided that the truth was probably somewhere in the middle. I filtered out all the players who only came on for the last ten minutes; their stats skewed the per-minute average too much.
The Big Reveal: Who Really Stepped Up?
Once I filtered the whole ugly dataset down and applied my custom weighting system (giving more points to turnovers forced than to simple passes), the picture cleared right up. Dave was right that his striker generated chances, but the stats showed my defensive player was the indisputable foundation. The data simply did not lie. Here’s what I found when I totaled the crucial metrics:
For Ajax, the true top performers were:
- The Maestro (Player A): He had the highest raw number of successful long passes into the final third. He wasn’t scoring, but he was the one consistently breaking the lines and launching the attacks.
- The Wall (Player B): This central defender was statistically perfect in his position. He won every single aerial duel he contested and had the highest number of defensive headers. His defensive solidity was absolutely key.
For Eintracht Frankfurt, the surprising leaders were:
- The Runner (Player C): This guy barely registered on the score sheet, but the data showed he had an unbelievably high number of high-pressure turnovers forced in the attacking third. He was relentless, running players off the pitch.
- The Distributor (Player D): Often overlooked because he wasn’t flashy, this midfielder had the highest overall pass completion rate of any player on the pitch, even when under heavy duress. He was pure consistency and held the team together.
The numbers showed exactly what I thought: the game wasn’t won by a single moment of magic, but by relentless, measurable effort across the pitch, particularly from the guys who don’t get the headlines. I had the statistical proof I needed.
Why This Stuff Matters To Me (The Personal Story)
People ask why I bother with this level of detail for something as simple as football stats. Why not just take the ready-made summary? Because I learned the absolute hardest way that you always trust the data you collect yourself, even if the collection process is tedious and messy. Everything needs proof that you’ve verified.
Years ago, I was working at this mid-sized software company. We had a massive project failure—the kind that costs millions. Management kept claiming the failure was due to one single, isolated software bug that came from a remote reporting tool. They blamed the coding team and summarily fired two really good people, one of whom was my mentor.
I didn’t buy the narrative. I quietly stayed up for weeks sifting through the deployment logs and raw user activity reports that nobody else wanted to touch. I was just clicking through raw CSV files and text documents, line by line, comparing timestamps and error codes. It was soul-crushingly painful. What I found was a horrifying mess of conflicting reports, intentional obfuscation, and crucial data that had been selectively edited by the project lead to hide their own massive scheduling and resource mistakes.
I took my compiled, messy, hand-checked data—hundreds of lines of verified, cross-referenced numbers—to the head of internal audit. It was enough to get the whole failure investigated properly. My mentor got his job back, and the manager who tried to scapegoat the engineers was immediately walked out the door. That incident taught me that relying on someone else’s polished, summarized report is asking for trouble. You need to roll up your sleeves and touch the raw stuff, even if it means manually copying player stats about Ajax into a cheap spreadsheet just to win a silly bet. The process of verification is everything.
So yeah, Dave paid up. And I know precisely who the key players were in that Frankfurt game, not because some talking head told me, but because I wrestled those ugly, conflicting numbers into submission myself. That’s the only way to be absolutely certain.