u/Round_Acanthaceae223

I've been seeing a lot of drafts around here and I keep noticing a negative discourse around early Gabriel picks. I completely understand why, but I actually see it as a really viable strategy, especially with the last two picks in 10/12-teamers.

This year feels extremely weird. Most teams have new managers and there's a ton of uncertainty. Looking at Fantrax ADPs, the top 10 is: Haaland, Bruno, Saka, Semenyo, Szobo, Wirtz, Palmer, João Pedro, MGW and Rice. I know Gabriel got very lucky with his attacking returns last year, roughly double his average per match, but even so, compared to that top 10 I'd say he's at worst the fourth-safest player on the list. Haaland is Haaland, Bruno performed really well under Carrick, and João Pedro looks like a lock at striker even though he had a fairly high blank rate last year.

Past those, I think Gabriel is a really steady asset. Even though he's a defender, you're getting far and away the best defender in the game. He plays in the best defense in the league and he's a bit of an attacking threat on top of that. How much is the oportunity cost of pick Gabriel over a Cole Palmer when you can get Gabriel and Mbeumo for example?

IDK, I want to hear your thoughts, because as a late first-round pick, depending on how the draft develops, he could be a really valuable one.

Hey everyone. Background on me: I'm a sports economics professor currently doing a master's in statistics. Football is my main sport, but I've always had a soft spot for baseball and I've always foun the idea of bringing some of baseball's analytical frameworks into football very interesting.

The thing that fascinates me most about baseball analytics is how they've managed to quantify individual player value in a rigorous, reproducible way. Specifically, I'm talking about WAR (Wins Above Replacement).

For those unfamiliar: WAR is a single number that tries to capture how many wins a player contributes to their team compared to a freely available "replacement-level" player. What makes it robust is that it's built from several independent components: batting runs, baserunning, fielding, positional adjustment, and a replacement level baseline, all converted into a common currency of wins. The key insight is that you can decompose a player's total value into distinct, interpretable dimensions.

I want to build something analogous for football. My current thinking is to structure a player's value around three components: an offensive contribution (goal involvement, shot quality, finishing efficiency), a defensive contribution (ball recovery, duels, pressing effectiveness), and a creative/construction one (progressive actions, chance creation, build-up involvement). The weight of each component would vary by position. A striker's value would be dominated by the offensive side, a centre-back's by the defensive one, and midfielders would get a more balanced weighting across all three.

Now here's where I'm stuck: data. I've been going down a rabbit hole trying to find a source that gives me granular per-90 player stats. Things like progressive carries, defensive duels won %, pressures, xG, xA, touches in the box along with minutes played, all in one place and ideally exportable.

FBref used to be the obvious answer, but as most of you probably know, they lost their Opta licence in January 2026 and everything beyond basic stats is gone. I've looked at DataMB, ScoutingStats, Understat, WhoScored, and a few Kaggle datasets, and each one covers part of what I need but not all of it. The consistent problem is missing advanced metrics, or no CSV export on the free tier.

I'm not opposed to paying for something reasonable — something in the €10–30/month range that gives clean, exportable player-level data for the top European leagues would be ideal. Just not in the market for a £3,000/year Wyscout licence.

Two things I'd love your input on. First, data sources, paid or free, that you've actually used and trust for this kind of project. Specifically something with minutes played, advanced per-90 metrics, and CSV export for the Premier League or top 5 leagues. Second, your honest opinion on the project itself. Does a positional WAR framework make sense in football given how interdependent everything is? What would you do differently?

Thanks in advance. Happy to share more of the methodology if there's interest.

Also — not a bot, I promise. Sorry if this reads a bit stiff, English isn't my first language.