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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,291 papers · 148 categories

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48 results for football betting

Study proposes new methods to convert betting odds into accurate probabilities for sports forecasting.

problem Convert betting odds to accurate outcome probabilities for sports forecasting and market efficiency analysis.
method Proposes two methods: Odds-Only-Equal-Profitability-Confidence (OO-EPC) and Favourite-Longshot-Bias-Adjusted Generalised Linear Model (FL-GLM).
result Proposed methods outperform existing methods in empirical tests and real-world applications.

We study the relationship between social media output and National Football League (NFL) games, using a dataset containing messages from Twitter and NFL game statistics. Specifically, we consider tweets pertaining to specific teams and games in the NFL season and use them alongside statistical game data to build predic…

2013-10-25abs ↗pdf ↗

We prove that every spherical football (also known as a spherical soccer ball) is a branched cover, branched only in the vertices, of the standard football made up of 12 pentagons and 20 hexagons. We also give examples showing that the corresponding result is not true for footballs of higher genera. Moreover, we classi…

2006-06-08abs ↗pdf ↗

This thesis uses predictive models to forecast football injuries.

problem Understanding and predicting football injuries in athletes.
method The study employed machine learning algorithms, feature selection, and exposure records to predict injuries.
result The models accurately predicted injury recovery times, training hours, and fatigue indicators.

The study uses unsupervised machine learning to identify top European football teams.

problem Selecting teams for the new European football Super League.
method Used Laplacian eigenmaps clustering on performance data.
result Successfully identified four clusters of teams based on performance metrics.

TacticAI helps football coaches improve tactics by analyzing corner kicks.

problem Developing effective responses to rival teams' tactics algorithmically.
method TacticAI combines predictive and generative components to suggest player setups and position adjustments.
result TacticAI's model suggestions are favored over existing tactics 90% of the time by football domain experts.

Study describes how compact Ricci solitons degenerate as cone angles approach zero.

problem Understanding degenerations of compact Ricci solitons as cone angles approach zero.
method Completely describes the degenerations of compact Ricci solitons, including the Gromov--Hausdorff limit of cigar solitons from conical teardrop solitons.
result Gromov--Hausdorff limit of cigar solitons from conical teardrop solitons.

AI benchmarks evaluate football team performance using generative models.

problem Evaluating human performance in complex interactive tasks is error-prone and unreliable.
method Trained Conditional VRNN Model on player and ball tracking data to imitate and predict team interactions.
result Trained model as a useful benchmark for evaluating team performance in football.

Twitter has been proven to be a notable source for predictive modelling on various domains such as the stock market, the dissemination of diseases or sports outcomes. However, such a study has not been conducted in football (soccer) so far. The purpose of this research was to study whether data mined from Twitter can b…

2014-11-05abs ↗pdf ↗

Extract useful information from football players' trajectories.

problem Automatic processing of two-dimensional positional data during matches.
method Newtonian mechanics, Kalman filter, Generative Adversarial Nets, Variational Autoencoders, Discriminator network.
result Deep generative models can learn underlying structure and statistics of trajectories.

The Kelly betting theory can sometimes lead to overly conservative bets.

problem Kelly betting can be too conservative in some cases.
method The authors use empirical data and theoretical distribution to compare Kelly bets, identifying cases where theoretical bets are much smaller than empirical bets.
result Theoretical Kelly bets can lead to no betting at all when the distribution is unbounded.

Study examines heart and football-shaped metrics, verifying geometric structure.

problem Analyzing reducible spherical conical metrics and their geometric properties.
method Examined 1-parameter heart shape and 3-parameter football shape families, verified structure theorem, used explicit metric and geodesic calculations.
result Naturally arise from Abelian differentials of the third kind, offer new evidence for spherical geometry and complex analytic structure interaction.

Modeling horse race betting odds with Ornstein-Uhlenbeck process.

problem Analyzing how herding and informed bettors affect odds movements.
method Deriving an Ornstein-Uhlenbeck process from vote shares and odds movements data.
result Identified microscopic and macroscopic patterns in odds convergence.

Predictive models of training load data failed to accurately predict injuries in Australian football.

problem Predicting injuries in Australian football using training load data.
method Training load data from GPS, accelerometers, and player ratings were analyzed using various predictive models.
result The best model for hamstring injuries had an AUC of 0.76, but overall predictive performance was poor.

This paper optimizes sports betting strategies using neural networks and portfolio theory.

problem Optimizing betting strategies in sports gambling.
method Combining neural network models with portfolio optimization, integrating Von Neumann-Morgenstern Expected Utility Theory and the Kelly Criterion.
result Achieved 135.8% relative profit during the English Premier League season.

New betting strategy reduces regret to ln(ln n) with protection against adversarial data.

problem Tackles the problem of minimizing regret in betting against adversarial and stochastic data.
method Combines insights from Robbins and Cover, using a mixture strategy.
result Exhibits a regret of O(ln(ln n)) on almost all paths, with O(log n) regret on the complement.

Testing-by-betting strategies almost surely go bankrupt under null hypotheses.

problem Understanding the behavior of betting strategies under null hypotheses.
method Analyzed the asymptotics of betting strategies under null distributions, focusing on the almost sure divergence of sums.
result Testing-by-betting strategies go bankrupt with probability one under any non-degenerate null distribution.

The betting CI outperforms classical methods in constructing confidence intervals for bounded means.

problem Constructing nonasymptotic confidence intervals for bounded means.
method A betting-based approach to define and time-uniform variants of confidence intervals (CSs).
result The betting CI matches the fundamental limits, outperforming existing empirical Bernstein CIs.

We show that spheres of positive constant curvature with nn (n3n\geq3) conic points converge to a sphere of positive constant curvature with two conic points (or called an (American) football) in Gromov-Hausdorff topology when the corresponding singular divisors converge to a critical divisor in the sense of Troyanov.…

2015-01-27abs ↗pdf ↗

Sequential tests for two-sample and independence testing using betting strategies.

problem Testing sequential data for two-sample and independence without kernel selection issues.
method Prediction-based betting strategies that adaptively determine distribution and joint distribution.
result Prediction-based tests outperform kernel-based approaches in high-dimensional or structured data settings.

A quantum memory model for Kelly betting with amplified or attenuated outcomes.

problem Optimizing Kelly betting strategies with quantum memory elements.
method Semi-classical model using quantum memory to encode payoff, modeled as random lasing dynamics.
result Best strategy is to invest all capital in coherent state amplitude for optimal performance.

The study shows how probability weighting can lead to betting in a risk-averse economy.

problem Understanding how probability weighting affects economic behavior and risk aversion.
method Examining a von Neumann-Morgenstern economy with an RDU agent to model probability weighting effects.
result Probability weighting can lead to endogenous betting in an economy with common beliefs.

Optimizing betting frequency in dynamic games with Kelly criterion.

problem Finding the optimal betting frequency in a dynamic game setting.
method Using Kelly's expected logarithmic growth criterion, the study analyzes the performance of high-frequency and low-frequency bettors.
result The optimal performance gn* changes with n, and the high-frequency case does not always lead to the best performance.

This work examines the effects of allowing borrowing in betting-based hypothesis testing.

problem The impact of allowing borrowing in betting-based hypothesis testing.
method Examined the consequences of allowing borrowing in each round, adjusting the rejection threshold accordingly.
result There is no extra price to pay for the possibility of borrowing if a path-dependent threshold is used.