Algorithm beats sports betting markets, showing inefficiencies.
problem Inefficiencies in sports betting markets.
method Created a betting algorithm using a novel dataset and win probability model.
result Above market returns for various sports betting markets.
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.
Investigates sports betting strategies using modern portfolio theory and Kelly criterion.
problem Mitigating risk in sports betting investments.
method Modern portfolio theory and Kelly criterion, with modifications for practical risk control.
result Adaptive fractional Kelly method is suitable across various sports settings.
BBE simulates betting exchanges to generate synthetic data for AI research.
problem Lack of real data for AI/ML in betting exchanges.
method Agent-based simulation model of a sports-betting exchange.
result Generates large, high-resolution synthetic data for AI/ML.
BBE simulates sports betting exchanges for data generation.
problem Creating synthetic data for betting strategy testing.
method Agent-based model (ABM) for sports betting exchange simulation.
result Simulation runs up to 1000 times faster with GPU.
Random forest model predicts tennis match outcomes with 80% accuracy.
problem Predicting tennis match outcomes before the game starts.
method Used a large database of tennis match information and a random forest model.
result Identified serve strength as a key predictor of match outcome.
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.
Decentralized prediction markets use AMMs to pool and withdraw liquidity, improving financial properties.
problem Creating a fair and efficient decentralized prediction market.
method Developed a liquidity-based AMM structure for prediction markets, studied liquidity management, and proposed trading fees.
result The decentralized AMM structure satisfies financial properties and can be managed with liquidity withdrawal.
Study confirms mispricing in sportsbooks but finds data issues affect results.
problem Mispricing and inefficiency in online sportsbooks.
method Replication using Wikipedia buzz factor metric and backtesting.
result Data quality issues affect betting results; only one strategy remains profitable.
Study compares financial and gambling markets, finding similarities and potential applications.
problem Lack of comprehensive study on gambling markets compared to financial markets.
method Comprehensive comparison of five aspects: platform, product, procedure, participant, and strategy.
result Well-established financial strategies can be applied to gambling markets, particularly in peer-to-peer betting exchanges.
Machine learning predicts US will win most Olympic medals in 2020.
problem Improve Olympic medal forecasting accuracy.
method Two-stage Random Forest machine learning model.
result Model outperforms traditional forecasts for three previous Olympics.
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…
The paper proposes using experts' insights in machine learning tasks.
problem Lack of reliance on experts' opinions in machine learning tasks.
method A three-step framework for integrating experts' insights into machine learning models.
result Proposed models achieve more stable and lower log loss results compared to top solutions.
Prediction and modelling of competitive sports outcomes has received much recent attention, especially from the Bayesian statistics and machine learning communities. In the real world setting of outcome prediction, the seminal Élő update still remains, after more than 50 years, a valuable baseline which is difficult to…
Technology has had an unquestionable impact on the way people watch sports. Along with this technological evolution has come a higher standard to ensure a good viewing experience for the casual sports fan. It can be argued that the pervasion of statistical analysis in sports serves to satiate the fan's desire for detai…
The paper analyzes sports commentary to automatically recognize events and extract insights.
problem Automatically recognizing and categorizing major actions in sports events from commentary.
method Used multiple Natural Language Processing techniques for classification and sentiment analysis.
result Identified insights from analyzing live sport commentaries and classifying major actions.
This review explores ML in predicting team sport outcomes, identifying successful strategies and themes.
problem Predicting outcomes in team sports using machine learning.
method Survey of studies from 1996 to 2019, analyzing ML algorithms and their accuracies.
result Identifies common themes and strategies for future research in predicting team sport outcomes.
Law of iterated logarithm derived from betting strategy.
problem Deriving the law of the iterated logarithm.
method Using a betting strategy's wealth guarantee.
result Law of the iterated logarithm established.
Kelly betting is a prescription for optimal resource allocation among a set of gambles which are typically repeated in an independent and identically distributed manner. In this setting, there is a large body of literature which includes arguments that the theory often leads to bets which are "too aggressive" with resp…
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.
In the UK betting market, bookmakers often offer a free coupon to new customers. These free coupons allow the customer to place extra bets, at lower risk, in combination with the usual betting odds. We are interested in whether a customer can exploit these free coupons in order to make a sure gain, and if so, how the c…
We propose a novel "tree-averaging" model that utilizes the ensemble of classification and regression trees (CART). Each constituent tree is estimated with a subset of similar data. We treat this grouping of subsets as Bayesian ensemble trees (BET) and model them as an infinite mixture Dirichlet process. We show that B…
Wearables like smartwatches which are embedded with sensors and powerful processors, provide a strong platform for development of analytics solutions in sports domain. To analyze players' games, while motion sensor based shot detection has been extensively studied in sports like Tennis, Golf, Baseball; Table Tennis and…
Paper simplifies complex sports analytics models for better understanding.
problem Difficulty in interpreting deep learning models for sports analytics.
method Developed a linear model tree that mimics deep learning models and explains its knowledge.
result The linear model tree achieves high accuracy and provides actionable insights.
Paper approximates Kelly betting for wealth growth.
problem Optimizing wealth growth in Kelly betting.
method Taylor-based approximation for quadratic programming.
result Closed-form approximate solution with interesting properties.
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.
Gamblers lose in long bets despite casino claims, study shows.
problem Gamblers losing in seemingly fair gambling scenarios.
method Theoretical and experimental analysis of two-armed Futurity slot machines.
result Casinos have a win rate greater than 50% in long bets, making them unfair.
Framework for real-time win probability and player ability in sports.
problem Real-time evaluation and player assessment in team sports.
method Continuous dominance indicator (T-score) and T-process formulation.
result Decomposes competitive advantage into interpretable statistical components.
Blockchain fan tokens boost sports fan engagement by 50%.
problem Low fan engagement in sports decisions.
method Analyzed 3,576 fan token polls to identify determinants of participation.
result Fan tokens engage 4,003 participants per poll, 50% of token holders.
We introduce a general framework for continuous-time betting markets, in which a bookmaker can dynamically control the prices of bets on outcomes of random events. In turn, the prices set by the bookmaker affect the rate or intensity of bets placed by gamblers. The bookmaker seeks a price process that maximizes his exp…
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.
Enhanced ICM ensemble detects concept drift better with novel betting functions.
problem Addressing Concept Drift in machine learning models.
method Refined ICM approach with improved betting functions and base estimators.
result The ensemble approach outperforms previous methods on benchmark datasets.
Extends Kelly Criterion to more complex betting scenarios.
problem Maximizing long-term growth in complex betting models.
method Generalizes Kelly Criterion to Lévy processes and high-frequency limits.
result Improved strategies for high-frequency betting.
PEAK tests means of multiple data streams with sequential betting.
problem Testing means of multiple data streams with nonparametric methods.
method Sequential, nonparametric testing using a betting scheme.
result PEAK provides up to 85% reduction in samples for stopping.
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.
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.
We develop a model of how information flows into a market, and derive algorithms for automatically detecting and explaining relevant events. We analyze data from twenty-two "political stock markets" (i.e., betting markets on political outcomes) on the Iowa Electronic Market (IEM). We prove that, under certain efficienc…
A new method combines multiple bounds and betting strategies for selective prediction, improving risk coverage in data-scarce settings.
problem Selective prediction with risk control in data-scarce domains.
method Combines concentration inequalities, multiple-testing corrections, and betting-based confidence sequences.
result Transfer-Informed Betting achieves tighter bounds and better coverage in data-scarce settings.
Scores political leanings in Web3 betting markets.
problem Understanding political motivations in decentralized prediction markets.
method Constructing PBLS from Polymarket data, analyzing 15k addresses, 4k events, 8k markets.
result Validated PBLS through internal and external comparisons, revealing political and profit motives.
A simplified Bayesian approach for online sports rating.
problem Rating players/teams based on game outcomes.
method Bayesian approach using Kalman filter principles.
result Known algorithms like Elo and TrueSkill are special cases.
Kelly criterion, that maximizes the expectation value of the logarithm of wealth for bookmaker bets, gives an advantage over different class of strategies. We use projective symmetries for a explanation of this fact. Kelly's approach allows for an interesting financial interpretation of the Boltzmann/Shannon entropy. A…
Sequential Kernel-based Conditional Independence Testing via Adaptive Betting
problem Testing conditional independence
method Testing-by-betting on an adaptively optimized Kernel Conditional Independence statistic
result Significantly reduces Type I error inflation while preserving high power
Rugby-Bot predicts multiple metrics from a single source using fine-grain data.
problem Complexity of sporting events requires multiple metrics for accurate analysis.
method Multi-task learning with fine-grain spatial data and wide-and-deep learning.
result Predictions are consistent and can be in distribution form.
Paper improves CI and CS for bounded means using betting and mixtures.
problem Estimating means of bounded random variables.
method Composite nonnegative martingales, testing by betting, method of mixtures.
result Empirically outperforms existing CI and CS methods.
We revisit the trading invariance hypothesis recently proposed by Kyle and Obizhaeva by empirically investigating a large dataset of bets, or metaorders, provided by ANcerno. The hypothesis predicts that the quantity $I:=\ri/N^{3/2}$, where $\ri$ is the exchanged risk (volatility × volume × price) and N…