Analysis of Data
This page examines shooting patterns and performance for both Real Madrid and Paris Saint-Germain, then draws cross-team comparisons. The two clubs offer different analytical lenses: Real Madrid invites questions about volume vs. efficiency, while PSG data reveals how shot distance shapes scoring success.
Top Performers: Shot Volume
This section compares attacking activity using shots per 90 minutes and shots on target per 90 minutes. Mbappé takes the highest number of shots per game, indicating he is the primary attacking outlet for Real Madrid. Vinícius Júnior shoots less frequently but maintains a strong shots-on-target rate, suggesting more selective shooting. Jude Bellingham, despite playing as a midfielder, records comparable shots on target per 90, highlighting his advanced attacking role and late runs into the box.
| Player | Position | Sh/90 | SoT/90 | Total Shots |
|---|---|---|---|---|
| Kylian Mbappé | FW | 5.14 | 2.30 | 105 |
| Rodrygo | MF,FW | 3.33 | 1.39 | 24 |
| Vinícius Júnior | FW,MF | 3.23 | 1.35 | 60 |
| Franco Mastantuono | MF,FW | 2.56 | 0.49 | 21 |
| Jude Bellingham | MF | 2.51 | 1.32 | 36 |
| Arda Güler | MF | 2.40 | 1.00 | 36 |
Shot Accuracy: Who Hits the Target?
This comparison focuses on finishing efficiency rather than volume. Bellingham shows a higher shots-on-target percentage than Vinícius, indicating his chances tend to come from more dangerous positions. Mbappé's efficiency remains high despite his large shot volume, reinforcing his role as a reliable goal scorer. Gonzalo García stands out with 62.5% accuracy from limited appearances — suggesting strong shot selection when called upon.
| Player | Position | SoT% | Goals | Shots on Target | Total Shots |
|---|---|---|---|---|---|
| Gonzalo García | FW | 62.5% | 3 | 5 | 8 |
| Jude Bellingham | MF | 52.8% | 4 | 19 | 36 |
| Kylian Mbappé | FW | 44.8% | 22 | 47 | 105 |
| Vinícius Júnior | FW,MF | 41.7% | 6 | 25 | 60 |
| Arda Güler | MF | 41.7% | 3 | 15 | 36 |
| Rodrygo | MF,FW | 41.7% | 1 | 10 | 24 |
| Federico Valverde | DF,MF | 27.6% | 0 | 8 | 29 |
| Aurélien Tchouaméni | MF | 13.0% | 0 | 3 | 23 |
Real Madrid: Team vs. Opponent
Real Madrid demonstrates overwhelming superiority over opponents in both shot volume and quality: 424 shots vs. 223 (90% more), accuracy of 37.3% vs. 31.4%, and 158 shots on target vs. just 70. This confirms a dominant attacking style that consistently creates high-quality chances while limiting opponents through possession control and defensive pressure.
Research Question: Does Shot Distance Predict Goals?
The PSG analysis investigates a specific tactical question: how does the distance from which a player shoots correlate with their shooting efficiency? The dataset includes each player's average shot distance in yards, alongside their goals, expected goals (xG), and shot accuracy. The pattern is striking.
Close-Range Forwards: Distance vs. Goals
Players who shoot from closer range consistently produce more goals and higher xG values. Gonçalo Ramos averages just 13.4 yards per shot and has scored 4 goals from 33 total shots. Bradley Barcola, averaging 16.5 yards, also contributes significantly to PSG's goals and xG. Both forwards are responsible for a disproportionate share of the team's scoring relative to their shot volume.
| Player | Position | Avg. Dist (yds) | Goals | Shots | xG | SoT% |
|---|---|---|---|---|---|---|
| Gonçalo Ramos | FW | 13.4 | 4 | 33 | 0.25 | 54.5% |
| Bradley Barcola | FW | 16.5 | 4 | 40 | 0.38 | 52.5% |
| Kvicha Kvaratskhelia | FW | 16.7 | 5 | 42 | 0.30 | 35.7% |
| Ousmane Dembélé | FW | 16.0 | 5 | 19 | 0.38 | 42.1% |
| Désiré Doué | FW | 16.5 | 3 | 19 | 0.38 | 42.1% |
| Marco Asensio | MF,FW | 17.3 | 1 | 22 | 0.21 | 36.4% |
| Lee Kang-in | MF,FW | 21.3 | 1 | 27 | 0.13 | 29.6% |
| João Neves | MF | 20.7 | 5 | 17 | 0.27 | 41.2% |
| Achraf Hakimi | DF,MF | 22.0 | 1 | 10 | 0.15 | 40.0% |
| Fabian Ruiz Peña | MF | 22.1 | 1 | 13 | 0.15 | 38.5% |
| Warren Zaïre-Emery | MF | 20.1 | 1 | 11 | 0.65 | 36.4% |
| Vitinha | MF | 27.0 | 1 | 27 | 0.04 | 11.1% |
| Quentin Merlin | MF | 24.8 | 0 | 6 | 0.08 | 33.3% |
The Midfield Distance Problem
Midfielders face a structural disadvantage: their tactical role keeps them further from goal. Vitinha averages 27 yards per shot — the highest in the squad — and has generated only 1 goal from 27 shots with a very low xG of 0.04 per shot. This confirms that midfield players like Vitinha contribute fewer goals not because of poor skill, but because their role keeps them in low-probability shooting positions.
João Neves: The Over-Performer
A notable exception is João Neves, who has scored 5 goals from just 17 shots despite averaging 20.7 yards per shot. His goals-to-shots ratio significantly exceeds his expected goals (xG = 0.27 per shot), suggesting superior shot selection — he chooses when to shoot more wisely than teammates, and converts opportunities more efficiently than his position would typically predict.
Defenders: Minimal Contribution by Design
Defensive players like Achraf Hakimi (avg. 22 yards, 1 goal from 10 shots) contribute minimally to PSG's scoring, which is entirely expected. Their role keeps them furthest from goal, and the data confirms this. Shot-distance data could be used to tailor training: players who naturally operate farther from goal could focus on getting the right timing and opportunities, rather than volume shooting.
Cross-Team Comparison: Real Madrid vs. PSG
Both clubs represent elite European football, but their attacking profiles differ in interesting ways. Real Madrid relies on high shot volume and dominant possession, while PSG's data reveals a clearer distance-efficiency relationship.
| Metric | Real Madrid (La Liga) | PSG (Ligue 1) |
|---|---|---|
| Total Shots | 424 | 332 |
| Goals Scored | 47 | 41 |
| Shots on Target | 158 | 131 |
| Shot Accuracy (SoT%) | 37.3% | 39.5% |
| Shots per Game | 19.27 | 17.47 |
| Opponent Shots per Game | 10.14 | 7.32 |
| Goals per Shot | 11.1% | 12.3% |
| Leading Shot-Taker | Mbappé (105 Sh) | Kvaratskhelia (42 Sh) |
| Highest SoT% | Bellingham (52.8%) | Gonçalo Ramos (54.5%) |
Key Comparisons
PSG is more efficient per shot: Despite taking fewer shots, PSG converts at a slightly higher rate (12.3% goals per shot vs. Real Madrid's 11.1%). This aligns with PSG's emphasis on shot proximity — closer shots yield better conversion.
Real Madrid dominates in volume: With nearly 20 shots per game, Real Madrid floods opponents with attacking pressure. Their volume approach still produces a high goals total despite slightly lower per-shot efficiency.
Positional patterns hold across both clubs: In both squads, forwards generate the most shots and goals, midfielders show moderate involvement, and defenders contribute minimally. The distance-efficiency relationship seen at PSG would likely apply to Real Madrid as well, though the Real Madrid dataset does not include shot distance data.
Both clubs dominate their opponents: Each team outshoots opponents by a wide margin, reflecting the quality gap between these elite clubs and the rest of their respective domestic leagues.