Following the submission deadline for the second stage of the 2026 Opta Forum research competition, four projects have been nominated for showcasing on stage, with a further three recommended for poster presentations.
Each proposal submitted was judged based on four key criteria: innovation, methodology, relevance and application. Now the seven standout projects will be showcased to an invited audience of industry delegates at the British Museum in London.
A new initiative for this year’s Opta Forum is the introduction of a dedicated media storytelling category, relating to how data can be applied intelligently to enhance media storytelling.
The full line-up of research presentations and posters for the 2026 Opta Forum, listed in no specific order, is as follows:
Stage Presentations
Media Storytelling Category: Hassan Rafique, Dylan D’Amelio and Evan Pegorsch – The power of interactive visuals: comparing player pass performance using Opta Vision
Hassan, Dylan, and Evan have developed two interactive data visualisations built on Opta Vision data, Passing Intelligence and Passflow, which are designed to deliver an engaging interactive experience to supplement an editorial feature comparing the passing performance of different players in a league. The visualisations are powered by several new metrics they have developed, including Opportunity Cost, Expected Value, and Risk Intelligence.
Hassan is an Assistant Professor in the Department of Sport Analytics at the Falk College of Sport, Syracuse University, where Dylan and Evan are currently studying Sports Analytics and Economics. Both Dylan and Evan are currently working as data analyst interns for the Syracuse Men’s Soccer team and Oldham Athletic A.F.C.
Performance Category, Analysis: Jaime Oriol – Breaking the Press from the Back: Linking Off-Ball Runs to Passing Decision Quality Under High Pressing
Jaime’s project has seen the development of a framework that connects two layers of analysis that are currently studied in isolation: the quality of off-ball runs in generating passing options under pressure, and the quality of the passer’s decision relative to those available options. The aim of this framework is to provide actionable insights for coaching staff, recruitment, and opposition analysis into both movement design and decision-making evaluation.
Jaime is currently studying a double degree in Business Analytics and Computer Science at Universidad Francisco de Vitoria in Madrid. He is the founder of the Football Decoded blog and currently works as a Data Science intern at Minsait.
Performance Category, Recruitment: Yureed Elahi – Run Exploitation Profiling – Measuring How Passers Respond to Off-Ball Movement
Yureed has developed a framework to evaluate passers based on how they respond to off-ball runs from teammates, measuring whether they select the highest-value options or default to safer passes. By linking off-ball run data with pass events and expected threat values, his research captures decision-making quality under defensive pressure. The result is a per-player profile that highlights the quality of passing decisions.
Yureed works for Data Science Dojo and has previous industry experience as an intern with FC Dinamo Tbilisi.
Performance Category, Abstract: Billy Mulley – Identifying Elite Low-Block Disruptors: A Recruitment Framework Using Low Block Decision Value (LBDV)
Billy’s project utilises a new metric, Low Block Decision Value (LBDV), to identify players who consistently demonstrate the bravery and execution required to break low defensive blocks.
By quantifying decision-making and progression under pressure, the framework highlights individuals whose choices translate into measurable competitive advantage. Designed with recruitment in mind, the metric enables clubs to target players capable of unlocking compact defensive structures.
Billy is currently pursuing an MSc in Data Analysis at Sports Data Campus and works in football as an academy video scout at Tottenham Hotspur, having previously held a first-team scout position at Millwall FC.
Poster Exhibitors
Roi Gil – Beyond Event Data: Building Structural Playing Style Models with Opta Vision
Roi’s poster will showcase a probabilistic Tactical Identity Framework he has developed that uses phase-aware metrics to model team playing styles more accurately than traditional event- or tracking-based approaches.
By leveraging structured tactical outputs, such as Phases of Play and Attacking and Defensive Style Qualifiers, his research builds measurable team-level identity profiles rather than relying on indirect stylistic proxies. Roi is undertaking a full-time PhD in Applied Data in Football Science with Cardiff Metropolitan University.
Eduardo Marques – Under Pressure, Out of Context: Glass-Box Decision Profiles for Recruitment Risk Assessment with Opta Vision
Eduardo has developed a recruitment-ready, interpretable analytical framework that evaluates how outfield players, particularly midfielders, choose between available passing options, how robust those decisions remain under pressure, and how well their decision patterns align with a team’s tactical identity.
The approach separates genuine decision quality from context-inflated execution by evaluating decisions against the alternatives available at the moment of action. The framework generates operational outputs for scouting departments, including tiered recruitment shortlists, transfer risk flags, and one-page player profiles with video-auditable decision trails.
Eduardo is an independent AI and data science consultant with a PhD in Machine Learning. He previously held leadership roles building large-scale data and ML teams and is currently completing a Masters in Big Data Applied to Football Scouting at Sports Data Campus.
Remi Awosanya – Quantifying Press-Resistance: A Multi-Dimensional Framework for Identifying and Evaluating Tactical Solutions to High-Intensity Pressing Using Opta Vision Data
Remi has developed a standardised framework for measuring press resistance that includes defining “Pressing Envelopes” to identify high-pressure situations, categorising tactical “Bypass Mechanisms” and evaluating their effectiveness. The findings have applications in coaching, recruitment and match strategy, helping teams exploit or defend against high-press scenarios.
Remi works as a data analyst for a non-profit and previously completed a 12-month internship in the Data and Analysis department at Sunderland.
Stats Perform would like to thank everyone who submitted a proposal and congratulate the seven participants who will be presenting or exhibiting at the 2026 Opta Forum.
