A deep learning framework for football match prediction

Rahman, Md. Ashiqur

doi:10.1007/s42452-019-1821-5

Cited by 24 publications

(10 citation statements)

References 16 publications

(16 reference statements)

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“…[ 19 ] In order to the numerical study of the champion cell based on PSI protein complex, it was employed for the SCAPS‐1D program to simulate the PSI cell using data reported in the literature tabulated in Table 1. [ 12,19,65,66 ]…”

Section: Resultsmentioning

confidence: 99%

“…In this article, the necessary parameters for the simulation related to each layer are all cited from the experimental study, reasonable estimates in some cases (see Supporting Information file), or literature, which are presented in Table 1 . [ 12,19,65,66 ] In each material layer, only one type of the single‐level defect was considered to make the simulation model as simple as possible. Such defects as compensating ones positioned at the intrinsic level.…”

Section: Numerical Modelingmentioning

confidence: 99%

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Numerical Evaluation of Novel Bio‐Photovoltaic Devices Inspired by Photosynthetic Process and High Poly (3,4‐Ethylenedioxythiophene): Poly (styrenesulfonate) Efficacy as Hole Transport Layer

et al. 2022

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Organic‐based photosystem I (PSI) protein complex bio‐solar cells have appeared as strong candidates for very low‐cost and environmentally friendly photovoltaic devices. The main challenge is their low power conversion efficiency (PCE). Such bottleneck stage in efficiency could be improved from the aspects of the absorber layer and carrier transporting layers. The proposed efficient, eco‐friendly, and simple procedure by applying a uniform pulsed electric field to align PSI dipoles leads to improved significant efficiency. Herein, the experimentally found functional data to benchmark cells have been employed to validate the first PSI numerical model using solar cell capacitance simulator‐1D for the first time. Simulation results show a reasonable agreement with those of experimental. The performance response of the second indium tin oxide/PEDOT: PSS/PSI/Au model is evaluated by varying the physical parameters of the hole transport layer (HTL). PCE characteristic achieved a fourfold increment in the crucial conduction band offset region owing to the reasonable barrier formation of electrons in the HTL/absorber interface. The optimum doping concentration is authorized at a certain μp > 10−2 cm2 V−1 S−1 with an HTL thickness in the order of 102 nm estimating an efficient numerical model compared to the HTL‐free cell.

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Section: Resultsmentioning

confidence: 99%

Section: Numerical Modelingmentioning

confidence: 99%

Numerical Evaluation of Novel Bio‐Photovoltaic Devices Inspired by Photosynthetic Process and High Poly (3,4‐Ethylenedioxythiophene): Poly (styrenesulfonate) Efficacy as Hole Transport Layer

et al. 2022

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“…SCAPS-1D solved the system of following simultaneous equations for carriers, namely Poisson's equation, continuity equation, the equation for charge transport, and equations for diffusivity and diffusion length [22,23] Poisson's equation…”

Section: Back-end Governing Equations Of Scaps-1dmentioning

confidence: 99%

A Theoretical Study to Investigate the Impact of Bilayer Interfacial Modification in Perovskite Solar Cell

et al. 2023

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The interfacial defects or imperfections in the multilayer perovskite solar cells (PSCs) are detrimental for efficient and stable devices. To produce highly efficient and stable PSCs, a bilayer between the interfaces of electron‐transport material/perovskite and perovskite/hole‐transport material can be useful for suppressing recombinations at these interfaces. To passivate the interfacial defects at the perovskite/SnO2 and perovskite/Spiro‐OMeTAD for three absorber materials (CsPbI3, FAPbI3, and Cs0.05(FA0.83MA0.17)0.95Pb(I0.83Br0.17)3), a thin layer of WO3 and poly‐bathocuproine interfacial layer is explored using solar cell capacitance simulation in 1D. The optimized device photovoltaic performances significantly improve using bilayers. The power conversion efficiency for the FAPbI3‐based PSCs in bilayer configuration is more than 12% as compared to pristine, whereas open‐circuit voltage is improved by over 13%. The enhancement in device performance is attributed to the reduction of interfacial defects at both the electron transport layer/perovskite and perovskite/hole transport layer interfaces. The proposed interface modification strategy provides a novel approach for fabricating efficient perovskite devices.

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“…It is important to stress that the model used the number of goals as one of the features in building ML models, which helped to achieve a high level of accuracy in predicting the match result. Another DL based study was done in 2020 [26] to predict the outcome of the FIFA World Cup 2018 matches using publicly available datasets "International Football results from 1872 to 2018", "FIFA Soccer Ranking", and "FIFA World Cup 2018 Dataset" and "FIFA Soccer Ranking" dataset. The authors proposed ANN and LSTM based model to predict the outcome of the matches with 63.3% accuracy.…”

Section: Background Studiesmentioning

confidence: 99%

Machine Learning Models Reveal Key Performance Metrics of Football Players to Win Matches in Qatar Stars League

Almulla

Alam

2020

IEEE Access

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As football (soccer) is one of the most popular sports worldwide, winning football matches is becoming an essential aspect of football clubs. In this study, we analyzed football players' performance in a total of 864 football matches of the Qatar Stars League (QSL) between the years 2012 and 2019. For each match, the collective performance of the players in key playing positions was analyzed to understand their effectiveness in winning games. We formulated this study as a classification framework in the machine learning (ML) context to distinguish the winning team from the losing team in a match. This allowed us to check the effectiveness of different performance metrics considered a feature vector for ML models. Different ML models were considered for this classification task, and the logistic regression-based model was considered the best performing model, with more than 80% accuracy. Multiple feature selection methods were leveraged to identify players' performance metrics that could be considered as contributing factors to determine the match result. The proposed ML model identified several features, including (a) shots on target by forwarders (b) distance covered by forwarders and midfielders at very high speed (c) successful passes, that can be considered as effective performance metrics for winning a football match in QSL. Interestingly, we revealed that the defenders' role could not be ignored for match results, and playing fair games improves the chance of winning matches in QSL. We also showed that players' performance metrics from the last five seasons would provide sufficient discriminative power to the proposed ML model to predict the match-winner in the upcoming season. The proposed ML model will support the players, coaching staff, and team management to focus on specific performance metrics that may lead to winning a match in QSL.

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A deep learning framework for football match prediction

Cited by 24 publications

References 16 publications

Numerical Evaluation of Novel Bio‐Photovoltaic Devices Inspired by Photosynthetic Process and High Poly (3,4‐Ethylenedioxythiophene): Poly (styrenesulfonate) Efficacy as Hole Transport Layer

Numerical Evaluation of Novel Bio‐Photovoltaic Devices Inspired by Photosynthetic Process and High Poly (3,4‐Ethylenedioxythiophene): Poly (styrenesulfonate) Efficacy as Hole Transport Layer

A Theoretical Study to Investigate the Impact of Bilayer Interfacial Modification in Perovskite Solar Cell

Machine Learning Models Reveal Key Performance Metrics of Football Players to Win Matches in Qatar Stars League

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