"I love Open Source Football: Latest posts"

2022-06-11 20:42:27

Open Source FootballHomeContributingAuthorsAbout☰Latest postsAug. 15, 2021Joseph ChernakExploring Quarterback Volatility with Gini CoefficientsVolatilitynflfastRGAMAnalyzing how volatile individual QB seasons are with gini coefficients and a volatility over expected (VOLoe) GAM model.July 30, 2021Jonas TrostleEvauluating defenses by how well they play the offense's WR 1FiguresnflfastRDefenseCornerback performance is hard to measure, but we can try.June 27, 2021Richard AndersonEstimating Team Ability From EPAnflfastRstanWe build a series of models to estimate team ability from EPA dataJune 7, 2021Ben BaldwinComputer Vision with NFL Player Tracking Data using torch for RTorchMachine learningComputer visionCoverage classification Using CNNs.April 17, 2021Ben BaldwinNFL win probability from scratch using xgboost in RxgboostnflfastRxgboost and RFeb. 5, 2021Ben BaldwinnflfastR EP, WP, CP xYAC, and xPass modelsFiguresnflfastRDecision TreesxgboostModel CalibrationA description of the nflfastR Expected Points (EP), Win Probability (WP), Completion Probability (CP) Expected Yards after Catch (xYAC), and Expected Pass (xPass) models.Feb. 5, 2021David AndersonGunslingers and Game ManagersQuarterback AnalysisnflfastRStupid Internet ArgumentsQuantifying Quarterbacks' performance along the "game manager" and "gunslinger" dimensions.Feb. 4, 2021Ben DominguezModeling NFL game outcomes using Python and scikit-learnpythonscikit-learnGame PredictionUse Python and scikit-learn to model NFL game outcomes and build a pre-game win probability model.Jan. 21, 2021Jack LichtensteinExploring Stability and Predictive Power of Penalties in the NFLnflfastREPAPenalty EPAPredictionUse nflfastR to calculate penalty EPA and understand the randomness of penalties to improve prediction accuracy of game outcomesJan. 11, 2021Adrian CadenaAnalyzing Home Field Advantage in the NFLnflfastRArticlesHome Field AdvantageMulti-season analysis of league and team-specific home-field advantage in the NFL.Dec. 29, 2020Jack LichtensteinExploring Rolling Averages of EPAnflfastREPAAdjusting EPARolling EPAPredictionUse nflfastR to develop lagged rolling averages of EPA to best predict a game's outcomeOct. 3, 2020Peter OwenStill elite: What the numbers tell us about Aaron RodgersThe more you look into the numbers, the better it looks for Aaron RodgersSept. 26, 2020Arthur GymerReceiving by PositionFiguresnflfastRPositional breakdownReceivingBreaking down the receiving game by position using nflfastR data.Sept. 9, 2020Mike IreneCreating an Expected Field Goal Metricfield goalnflfastRplacekickerUsing nflfastR play-by-play data to measure kicker performance.Sept. 8, 2020Richard AndersonEstimating Run/Pass Tendencies with tidyModels and nflfastRtidyModelsnflfastRstanThis article shows how to use tidyModels to predict QB dropbacks and uses a multilevel model to show which teams are run/pass heavy after accounting for game scriptSept. 6, 2020Dennis BrooknerRaphael Laden-GuindonRERUNExonerating punters for long returnsAug. 31, 2020Ben BaldwinDefense and rest time re-visitednflfastRArticlesDoes incorporating actual rest time help us predict how a defense will do?Aug. 31, 2020Anthony ReinhardCalculating Expected Fantasy Points for ReceiversFantasy FootballnflfastRnflfastR xYAC ModelUse the nflfastR xYAC & CP models to calculate how many fantasy points an average receiver would expect to earn on each target.Aug. 29, 2020Jonathan GoldbergAdding ESPN and 538 Game Predictions to nflfastR DataScrapingGame PredicitionsnflfastRHere, we'll look at how to scrape ESPN's and 538's pregame predictions and merge them into nflfastR dataAug. 29, 2020Analytics DarkwebFaceted and Animated HeatmapsFiguresAnimationnflfastRCombining lessons from multiple posts to create faceted or animated heatmaps.Aug. 29, 2020Ethan DouglasPlayer Density and Completion Surface EstimatesnflfastRpythonMethods for modeling density estimates and expected completion percentages across the football field for individual players.Aug. 28, 2020Analytics DarkwebFast Data LoadingEfficiencyLoading your nfl data at 10x speed!Aug. 27, 2020Adrian CadenaIndividual Expected Completion using Logistic Generalized Additive Mixed ModelsLogistic Generalized Additive Mixed ModelsMixed EffectsCompletion Probability InterceptCase study how to leverage Generalized Additive Mixed Models (GAMM) to estimate the individual probability of completion per Quarterback as a random effect.Aug. 26, 2020Sam HoppenOpen Source (Fantasy) Football: Visualizing TRAP BacksFiguresnflfastRFantasy FootballUsing nflfastR data to visualize where on the field running backs get their carries and how that translates to the Trivial Rush Attempt Percentage (TRAP) model.Aug. 25, 2020Anthony GadaletaExpected Turnovers for QuarterbacksFiguresnflfastRturnoversquarterbacksBuilding expected interceptions and expected fumbles models to find QBs likely to increase or decrease their interceptions and/or turnovers per dropback from 2019 to 2020.Aug. 24, 2020Ben BaldwinGetting into sports analyticsGetting startedCollection of short answers to common questions.Aug. 24, 2020Sebastian CarlVisualizing EPSN's Total QBR Using Interactive PlotsScrapingespnscrapeRInteractive plotsTotal QBRFiguresHow to get ESPN data and create interactive plots using the plotly ggplot2 library.Aug. 23, 2020Austin RyanExploring Wins with nflfastRTidymodelsFiguresnflfastRLooking at what metrics are important for predicting wins. Creating expected season win totals and comparing to reality.Aug. 22, 2020Robby GreerRanking QBs Using Era Adjusted EloElopythonUse 538's QB Elo value, a highly predictive measurement of QB impact, to compare QB careers across eraAug. 21, 2020Max BolgerGame Excitement and Win Probability in the NFLnflfastRpythonGame excitement calculation and a win probability figure.Aug. 21, 2020Ethan DouglasNFL Pass Location VisualizationnflfastRpythonMethods for visualizing NFL passing location data.Aug. 21, 2020Austin RyanRodgers Efficiency DeclineFiguresnflfastRCPOE / EPA functionsPackersA look into Rodgers Efficiency Decline. Also some functions for plotting EPA/CPOE moving averages.Aug. 20, 2020Anthony ReinhardVisualizing the Run/Pass Efficiency GapFiguresnflfastRUsing nflfastR data to show how much more efficient passing is than rushing at the team levelAug. 20, 2020Jonathan GoldbergAdjusting EPA for Strength of OpponentOpponent adjusted EPAFiguresnflfastRThis article shows how to adjust a team's EPA per play for the strength of their opponent. The benefits of adjusted EPA will be demonstrated as well!Aug. 20, 2020Ben BaldwinPython contributing examplenflfastRpythonShowing how to contribute using Python codeAug. 19, 2020Analytics DarkwebMatching players without ID keysFiguresRosternflfastRRebuilding player graphs when ID keys go missing or are corrupted.Aug. 19, 2020Analytics DarkwebNeural Nets using RKerasTensorflownflfastRUsing Keras in R to build neural networks.Aug. 19, 2020Ben BaldwinThe accumulation of QB hits vs passing efficiencyFiguresnflfastRDo quarterbacks who get hit see their performance decline throughout the game?Aug. 19, 2020Sebastian CarlWins Above ExpectationFiguresnflfastRThis article looks at the percentage of snaps with win probability over an arbitralily chosen critical value and compares it with the true win percentage.Aug. 18, 2020Sebastian CarlPFR's Bad Throw Percentage for QuarterbacksScrapingPFRFiguresnflfastRThis article shows how to scrape football data from Pro Football Reference andhow to plot the bad throw percentage data for quarterbacks.CategoriesArticles(40)Adjusting EPA(1)Animation(1)Articles(2)Completion Probability Intercept(1)Computer vision(1)CPOE / EPA functions(1)Decision Trees(1)Defense(1)Efficiency(1)Elo(1)EPA(2)espnscrapeR(1)Fantasy Football(2)field goal(1)Figures(15)GAM(1)Game Predicitions(1)Game Prediction(1)Getting started(1)Home Field Advantage(1)Interactive plots(1)Keras(1)Logistic Generalized Additive Mixed Models(1)Machine learning(1)Mixed Effects(1)Model Calibration(1)nflfastR(31)nflfastR xYAC Model(1)Opponent adjusted EPA(1)Packers(1)Penalty EPA(1)PFR(1)placekicker(1)Positional breakdown(1)Prediction(2)python(6)Quarterback Analysis(1)quarterbacks(1)Receiving(1)Rolling EPA(1)Roster(1)scikit-learn(1)Scraping(3)stan(2)Stupid Internet Arguments(1)Tensorflow(1)tidyModels(1)Tidymodels(1)Torch(1)Total QBR(1)turnovers(1)Volatility(1)xgboost(2)More articles »Latest postsCorrectionsIf you see mistakes or want to suggest changes, please create an issue on the source repository.ReuseText and figures are licensed under Creative Commons Attribution CC BY-NC 4.0. Source code is available at https://github.com/mrcaseb/open-source-football, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".©2020 - Website creator Sebastian Carl (Twitter: @mrcaseb)