BALLER

Transfer Decision Report

Antoine Semenyo → Arsenal FC, Dec 24 2025, Premier League (PL) winter transfer window

Match-Level Analysis
7 Key Fixtures

Executive Summary

Current Rank
1st
2pts ahead of Manchester City
Key Fixtures
7
Title-defining matches
Analysis Type
Match-Level
Contextual simulation
Metrics
5 Core
+ Points Difference Added (PDA) extension

This report evaluates whether Antoine Semenyo represents a material improvement to Arsenal's title chances by analyzing his projected performance in seven critical upcoming fixtures. Unlike traditional season-level projections, this analysis operates at match level, accounting for current form of future teammates, specific opponents and their form, tactical contexts, and teammate interactions.

The assessment compares Semenyo's observed performances at Bournemouth against the same opponents with his simulated performances in Arsenal's system match per match, alongside the current output from Gabriel Martinelli and Leandro Trossard in identical fixtures.

Why These Seven Fixtures Matter

These fixtures were selected as the most title-defining moments in Arsenal's remaining season. Each represents a distinct tactical and psychological challenge that will directly influence the final standings.

Aston Villa

Matchday 19 • Current rank: 3rd

Direct title rival

Man United

Matchday 23 • Current rank: 7th

Historic rival, inconsistent form

Tottenham

Matchday 27 • Current rank: 14th

North London Derby - title spoiler

Chelsea

Matchday 28 • Current rank: 4th

London rival, top-4 competitor

Man City

Matchday 33 • Current rank: 2nd

Primary title contender (-2pts)

Newcastle

Matchday 34 • Current rank: 11th

Champions League chasing

Crystal Palace

Matchday 38 • Current rank: 8th

Final day - every point counts

This is not a seasonal average projection. Each match is analyzed independently based on opponent strength, tactical setup, and contextual factors. This match-by-match approach reveals performance volatility and upside that aggregated metrics cannot capture.

Arsenal Lineup Context for Simulations

Opponents Squad Context

Match-by-Match Performance Analysis

vs Aston Villa

Matchday 19Direct title rival

Current Rank
3rd

Semenyo (Bournemouth) (PL 1st leg)

Loss 0-4, RW, 90min
Passes Completed:10-20
Pass Accuracy:80-85%
Touches:34-44
Shots:1-2
xG:>0.30

Arsenal Current LWs (PL 1st leg)

Martinelli
Sub 10min, LW
Passes:0-10
Accuracy:90-100%
Touches:0-11
Shots:0
xG:0.00
Trossard
Sub 41min, LW
Passes:0-10
Accuracy:70-75%
Touches:22-34
Shots:>2
xG:>0.30

Semenyo (Arsenal) - Simulated (PL 2nd leg)

Simulated: Arsenal LW, 90min
Passes Completed:10-20
Pass Accuracy:70-75%
Touches:22-34
Shots:>2
xG:0.11-0.30
HIGH CONFIDENCE

Match-Specific Insights

Against Aston Villa (3rd), Semenyo's simulation shows 10-20 passes at 70-75% accuracy with >2 shots and 0.11-0.30 xG. This represents a marked improvement over Trossard's substitute appearance (41min, 0-10 passes) and Martinelli's minimal involvement (10min). The simulation projects consistent attacking output (>2 shots) as Trossard delivered in this fixture.

Performance Profile Across All Seven Fixtures

These visualizations show the predicted performance ranges (not averages) for Semenyo at Arsenal across all seven key fixtures on a same chart for a comparative view. The bars represent the full range of expected output.

Touches per Match (Range)

Passes Completed per Match (Range)

Passes Completion % per Match (Range)

Shots per Match (Range)

Expected Goals per Match (Range)

Synthesis: Performance Transfer Patterns

Consistency Across Key Fixtures

Semenyo's simulated profile projects full 90-minute involvement across all seven fixtures, contrasting sharply with Arsenal's current rotation pattern. Martinelli averaged just 26 minutes across these matches (excluding DNP), while Trossard's involvement was more substantial but still variable (0-90 minutes). The simulation provides predictable output in critical moments where rotation has created uncertainty.

Attacking Output Stability

Across six of seven fixtures, Semenyo's simulation maintains shot frequency (1-2 or >2 shots) with xG consistently in the 0.01-0.30 range. This compares favorably to Martinelli's limited shot opportunities (0-2 shots across appearances) and matches Trossard's attacking intent when starting. The simulation suggests reliable goal threat even in matches where current options showed minimal offensive contribution.

Passing Accuracy Trade-offs

The model projects passing accuracy in the 60-80% range for most fixtures—lower than Martinelli's high completion rates in limited minutes (often 80-100%) but comparable to Trossard's 0-85% range when playing extended periods. Against elite opponents (Man City), the simulation drops to minimal passing output (0-10 passes), acknowledging tactical constraints that limit wide forward involvement.

Context-Dependent Variance

The simulation does not project uniform enhancement: against Crystal Palace, Trossard's actual 90-minute performance (20-30 passes, >2 shots, 0.11-0.30 xG) exceeded Semenyo's simulation (10-20 passes, 1-2 shots). Against Man City, both Martinelli and Trossard showed higher involvement than the conservative simulation (0-10 passes, 0.00 xG). This variance demonstrates opponent-specific modeling rather than blanket optimism.

Extension: Points Difference Added (PDA)

Decision Summary

Based on match-level contextual simulation across seven title-defining fixtures, Antoine Semenyo presents a mixed but strategically valuable option compared to Arsenal's current left wing rotation:

  • Availability Certainty: Projected full 90-minute involvement across all seven matches eliminates rotation risk. Current options show high variance (Martinelli: 0-60min, Trossard: 0-90min), creating tactical unpredictability in crucial fixtures.
  • Attacking Reliability: Simulation maintains shot frequency (1-2 or >2) and xG output (0.01-0.30) in six of seven fixtures. This consistency contrasts with Martinelli's limited offensive contribution (frequently 0 shots in substitute appearances) and provides baseline goal threat Arsenal currently lacks in several key matches.
  • Contextual Limitations: Against elite opponents (Man City) and in specific scenarios (Crystal Palace), the simulation projects lower output than Trossard's actual performances when starting. The model does not guarantee superiority in every fixture—rather, it offers stable output where current options show high variance or minimal involvement.
  • Tactical Fit Considerations: Projected passing accuracy (60-80%) sits below Martinelli's high completion rates in limited minutes but aligns with Trossard's output over extended play. The simulation suggests Semenyo would operate as a direct attacking outlet rather than a high-volume build-up contributor, particularly evident in the conservative Man City projection (0-10 passes, minimal xG).

The transfer case rests primarily on availability and baseline attacking output rather than superior peak performance. In fixtures where Arsenal rotated or deployed current options in limited roles (Aston Villa, Man United, Chelsea), Semenyo's simulation projects materially higher involvement. In fixtures where Trossard started and performed well (Crystal Palace, Newcastle), the simulation acknowledges comparable or inferior output. This nuanced assessment—accounting for rotation patterns, opponent quality, and role uncertainty—provides decision confidence that seasonal aggregates cannot offer.

About This Analysis

Methodology

This report uses a foundational contextual performance transfer model that represents players through their surrounding context—teammates, opponents, tactical roles, and action interactions. Performance is discretized into multi-metric labels, enabling structured transfer learning across teams and competitions.

Data Sources

Observed performances: Premier League matchday data through MD 17 (December 2024). Simulated performances: Arsenal lineup context aggregated from 17 matches, opponent profiles from current season form. PDA: placeholder values demonstrating integration pathway.

Model Architecture

The model operates at match level, not season level, and predicts coherent multi-metric performance profiles rather than independent continuous values. This enables reasoning about tactical fit, role adaptation, and context-dependent output variance.

Intended Use

This analysis demonstrates a level of contextual simulation that moves beyond seasonal projections to evaluate match-specific impact in critical fixtures. Rather than aggregate metrics across competitions, this approach isolates the seven most consequential matches in Arsenal's title race and simulates performance within those exact tactical and competitive contexts.

This report is a technical demonstration of contextual performance transfer modeling applied to a real-world transfer decision. All simulations are based on the described model architecture and real performance data through December 2025. PDA values are illustrative pending full data integration.

Interested in similar analysis for other transfer targets? The Semenyo case represents one scenario among thousands of possible transfer evaluations. This same match-level contextual framework can be applied to any player-to-team transfer question.

For custom transfer analysis requests, contact: adjileyeb@yahoo.com

Match-Level Contextual Performance Transfer Analysis • December 2025