This notebook contains a set of analyses for the selected user’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that Varghast is likely to own. This enables to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
This analysis is based on data from BoardGameGeek that was last updated on 2021-12-20.
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine a predictive model trained on a user’s collection for games published through 2019. How many games has the user owned/rated/played in the training set (games prior to 2019)?
username | dataset | period | games_owned | games_rated | games_played |
Varghast | training | published before 2020 | 142 | 125 | 153 |
Varghast | test | published 2020 or later | 10 | 3 | 11 |
There are two main (binary) outcomes we will be modeling for the user.
The first, own refers to whether the user currently lists a game as owned in their collection. The second, played refers to whether the user currently owns, has rated, or previously owned a game. This means the latter will generally have a larger list of games, but may still be a useful category to examine for people who play lots of games without necessarily owning them.
We will train predictive models to learn the probability that the user will own or play individual games based on their features.
We can examine coefficients from the trained modes, which are penalized logistic regressions fit to our two main outcomes. Positive values indicate that a feature increases a user’s probabilility of owning/rating a game, while negative values indicate a feature decreases the probability.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | In_Collection | All_Games | Ratio |
Varghast | End Game Bonuses | 11.3% | 1.1% | 10.1 |
Varghast | Communication Limits | 8.5% | 0.9% | 9.8 |
Varghast | Traitor Game | 5.6% | 0.6% | 9.6 |
Varghast | Renegade Game Studios | 5.6% | 0.8% | 7.0 |
Varghast | Asmodee | 20.4% | 5.1% | 4.0 |
Varghast | ZMan Games | 13.4% | 3.4% | 4.0 |
Varghast | Iello | 12.0% | 3.0% | 4.0 |
Varghast | Race | 7.0% | 1.8% | 3.9 |
Varghast | Pegasus Spiele | 15.5% | 4.6% | 3.4 |
Varghast | Tricktaking | 4.9% | 1.6% | 3.0 |
Varghast | Word Game | 4.9% | 1.7% | 2.9 |
Varghast | Deduction Game | 16.9% | 6.2% | 2.7 |
Varghast | Puzzle | 8.5% | 3.3% | 2.6 |
Varghast | Card Drafting | 28.9% | 11.6% | 2.5 |
Varghast | Kosmos | 7.7% | 3.3% | 2.4 |
Varghast | Set Collection | 39.4% | 17.2% | 2.3 |
Varghast | Ravensburger | 5.6% | 3.2% | 1.8 |
Varghast | Events | 1.4% | 2.0% | 0.7 |
Varghast | Grid Movement | 6.3% | 8.8% | 0.7 |
Varghast | Dice Rolling | 16.2% | 29.1% | 0.6 |
Varghast | Adventure | 4.2% | 6.7% | 0.6 |
Varghast | Humor | 1.4% | 5.7% | 0.2 |
Varghast | Wargame | 1.4% | 12.6% | 0.1 |
Varghast | Transportation | 0.0% | 2.8% | 0.0 |
Varghast | Childrens Game | 0.0% | 5.8% | 0.0 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can display this information in table form, displaying the 100 games with the highest probability of ownership, adding a blue line when the user does own the game.
username | yearpublished | game_id | name | pred_played | pred_own | actual_played | actual_own |
Varghast | 2019 | 266507 | Clank!: Legacy – Acquisitions Incorporated | 0.81 | 0.89 | 0 | 0 |
Varghast | 2000 | 478 | Citadels | 0.80 | 0.84 | 0 | 0 |
Varghast | 2005 | 15062 | Shadows over Camelot | 0.88 | 0.80 | 0 | 0 |
Varghast | 2019 | 283863 | The Magnificent | 0.89 | 0.76 | 0 | 0 |
Varghast | 2014 | 157354 | Five Tribes | 0.49 | 0.73 | 1 | 1 |
Varghast | 2018 | 244711 | Newton | 0.66 | 0.72 | 0 | 0 |
Varghast | 2014 | 163412 | Patchwork | 0.37 | 0.65 | 0 | 0 |
Varghast | 2017 | 224037 | Codenames: Duet | 0.34 | 0.64 | 1 | 1 |
Varghast | 2015 | 181304 | Mysterium | 0.35 | 0.63 | 1 | 1 |
Varghast | 2012 | 118048 | Targi | 0.35 | 0.62 | 1 | 1 |
Varghast | 2011 | 70919 | Takenoko | 0.58 | 0.59 | 0 | 0 |
Varghast | 2014 | 156129 | Deception: Murder in Hong Kong | 0.47 | 0.58 | 1 | 1 |
Varghast | 2011 | 103686 | Mundus Novus | 0.37 | 0.56 | 0 | 0 |
Varghast | 2016 | 200147 | Kanagawa | 0.56 | 0.54 | 0 | 0 |
Varghast | 2019 | 276025 | Maracaibo | 0.49 | 0.54 | 0 | 0 |
Varghast | 2016 | 198773 | Codenames: Pictures | 0.19 | 0.54 | 0 | 0 |
Varghast | 2013 | 140620 | Lewis & Clark: The Expedition | 0.29 | 0.52 | 0 | 0 |
Varghast | 2019 | 281259 | The Isle of Cats | 0.33 | 0.47 | 0 | 0 |
Varghast | 2015 | 178900 | Codenames | 0.27 | 0.47 | 1 | 1 |
Varghast | 2019 | 270971 | Era: Medieval Age | 0.41 | 0.46 | 0 | 0 |
Varghast | 2008 | 33107 | Senji | 0.42 | 0.46 | 0 | 0 |
Varghast | 2017 | 174430 | Gloomhaven | 0.46 | 0.45 | 1 | 1 |
Varghast | 2015 | 182874 | Grand Austria Hotel | 0.25 | 0.44 | 0 | 0 |
Varghast | 2018 | 205896 | Rising Sun | 0.73 | 0.44 | 1 | 1 |
Varghast | 2014 | 148228 | Splendor | 0.51 | 0.43 | 0 | 0 |
Varghast | 2019 | 265285 | Queenz: To Bee or Not to Bee | 0.46 | 0.43 | 0 | 0 |
Varghast | 2009 | 54998 | Cyclades | 0.38 | 0.43 | 0 | 0 |
Varghast | 2015 | 175878 | 504 | 0.37 | 0.42 | 0 | 0 |
Varghast | 2014 | 153938 | Camel Up | 0.15 | 0.42 | 0 | 0 |
Varghast | 2013 | 52461 | Legacy: The Testament of Duke de Crecy | 0.41 | 0.41 | 0 | 0 |
Varghast | 2004 | 9220 | Saboteur | 0.57 | 0.41 | 0 | 0 |
Varghast | 2018 | 244331 | Blue Lagoon | 0.24 | 0.39 | 0 | 0 |
Varghast | 2018 | 258444 | Gingerbread House | 0.48 | 0.39 | 0 | 0 |
Varghast | 1995 | 46 | Medici | 0.21 | 0.39 | 0 | 0 |
Varghast | 2017 | 221805 | Breaking Bad: The Board Game | 0.30 | 0.38 | 0 | 0 |
Varghast | 2010 | 82702 | Funfair | 0.31 | 0.37 | 0 | 0 |
Varghast | 2016 | 198454 | When I Dream | 0.32 | 0.37 | 1 | 1 |
Varghast | 2018 | 225694 | Decrypto | 0.20 | 0.36 | 1 | 1 |
Varghast | 2016 | 205158 | Codenames: Deep Undercover | 0.14 | 0.36 | 1 | 1 |
Varghast | 2019 | 257066 | Sierra West | 0.16 | 0.34 | 0 | 0 |
Varghast | 2019 | 260710 | Amul | 0.47 | 0.34 | 0 | 0 |
Varghast | 2018 | 246297 | Shadows: Amsterdam | 0.11 | 0.33 | 0 | 0 |
Varghast | 2017 | 230802 | Azul | 0.15 | 0.32 | 1 | 1 |
Varghast | 2014 | 152241 | Ultimate Werewolf | 0.33 | 0.32 | 0 | 0 |
Varghast | 2005 | 18258 | Mission: Red Planet | 0.27 | 0.32 | 0 | 0 |
Varghast | 2018 | 260428 | Pandemic: Fall of Rome | 0.15 | 0.32 | 0 | 0 |
Varghast | 2012 | 121921 | Robinson Crusoe: Adventures on the Cursed Island | 0.26 | 0.31 | 0 | 0 |
Varghast | 2016 | 168681 | Beyond Baker Street | 0.28 | 0.31 | 0 | 0 |
Varghast | 2007 | 31260 | Agricola | 0.40 | 0.31 | 0 | 0 |
Varghast | 2012 | 120677 | Terra Mystica | 0.17 | 0.31 | 0 | 0 |
Varghast | 2019 | 284083 | The Crew: The Quest for Planet Nine | 0.44 | 0.31 | 1 | 1 |
Varghast | 2016 | 187653 | Covert | 0.17 | 0.30 | 0 | 0 |
Varghast | 2012 | 122515 | Keyflower | 0.16 | 0.30 | 0 | 0 |
Varghast | 2010 | 73439 | Troyes | 0.36 | 0.29 | 1 | 1 |
Varghast | 2017 | 220308 | Gaia Project | 0.15 | 0.29 | 0 | 0 |
Varghast | 2010 | 62219 | Dominant Species | 0.13 | 0.29 | 0 | 0 |
Varghast | 2008 | 38032 | Byzanz | 0.15 | 0.28 | 0 | 0 |
Varghast | 2014 | 148949 | Istanbul | 0.17 | 0.28 | 0 | 0 |
Varghast | 2019 | 253185 | Chai | 0.17 | 0.28 | 0 | 0 |
Varghast | 2019 | 270970 | Century: A New World | 0.25 | 0.27 | 0 | 0 |
Varghast | 2004 | 11945 | Linq | 0.07 | 0.27 | 0 | 0 |
Varghast | 2008 | 38159 | Ultimate Werewolf: Ultimate Edition | 0.35 | 0.27 | 0 | 0 |
Varghast | 2012 | 123096 | Space Cadets | 0.26 | 0.27 | 0 | 0 |
Varghast | 2019 | 263155 | One Key | 0.16 | 0.27 | 0 | 0 |
Varghast | 2015 | 181761 | Plums | 0.19 | 0.27 | 0 | 0 |
Varghast | 2017 | 175324 | Fog of Love | 0.14 | 0.26 | 0 | 0 |
Varghast | 2014 | 154203 | Imperial Settlers | 0.24 | 0.26 | 0 | 0 |
Varghast | 2016 | 236217 | Timebomb | 0.18 | 0.26 | 0 | 0 |
Varghast | 2010 | 73171 | Earth Reborn | 0.23 | 0.25 | 0 | 0 |
Varghast | 2008 | 30549 | Pandemic | 0.23 | 0.25 | 0 | 0 |
Varghast | 2006 | 21241 | Neuroshima Hex! 3.0 | 0.38 | 0.25 | 0 | 0 |
Varghast | 2013 | 127024 | Room 25 | 0.39 | 0.25 | 0 | 0 |
Varghast | 2012 | 128882 | The Resistance: Avalon | 0.29 | 0.25 | 0 | 0 |
Varghast | 2009 | 45134 | Arcana | 0.19 | 0.24 | 0 | 0 |
Varghast | 2008 | 38054 | Snow Tails | 0.11 | 0.24 | 0 | 0 |
Varghast | 2008 | 34635 | Stone Age | 0.11 | 0.23 | 1 | 1 |
Varghast | 2015 | 140934 | Arboretum | 0.12 | 0.23 | 1 | 1 |
Varghast | 2016 | 205716 | New Angeles | 0.23 | 0.23 | 0 | 0 |
Varghast | 2019 | 245655 | The King's Dilemma | 0.31 | 0.23 | 0 | 0 |
Varghast | 2017 | 234487 | Altiplano | 0.22 | 0.23 | 0 | 0 |
Varghast | 2008 | 38506 | Witch of Salem | 0.34 | 0.22 | 0 | 0 |
Varghast | 2012 | 119391 | Il Vecchio | 0.34 | 0.22 | 0 | 0 |
Varghast | 2013 | 146278 | Tash-Kalar: Arena of Legends | 0.16 | 0.22 | 0 | 0 |
Varghast | 2017 | 217372 | The Quest for El Dorado | 0.27 | 0.22 | 0 | 0 |
Varghast | 2019 | 269752 | Noctiluca | 0.17 | 0.22 | 0 | 0 |
Varghast | 2008 | 35677 | Le Havre | 0.19 | 0.22 | 0 | 0 |
Varghast | 2013 | 134453 | The Little Prince: Make Me a Planet | 0.17 | 0.22 | 0 | 0 |
Varghast | 2014 | 155426 | Castles of Mad King Ludwig | 0.21 | 0.21 | 0 | 0 |
Varghast | 2016 | 176371 | Explorers of the North Sea | 0.13 | 0.21 | 0 | 0 |
Varghast | 2010 | 67185 | Sobek | 0.22 | 0.21 | 0 | 0 |
Varghast | 2009 | 39683 | At the Gates of Loyang | 0.33 | 0.21 | 0 | 0 |
Varghast | 2019 | 273477 | Obscurio | 0.22 | 0.21 | 0 | 0 |
Varghast | 2014 | 166384 | Spyfall | 0.31 | 0.21 | 0 | 0 |
Varghast | 2018 | 249821 | Codenames: Harry Potter | 0.15 | 0.20 | 0 | 0 |
Varghast | 2014 | 136594 | Dragon's Hoard | 0.17 | 0.20 | 0 | 0 |
Varghast | 2008 | 39463 | Cosmic Encounter | 0.13 | 0.20 | 0 | 0 |
Varghast | 2014 | 156336 | Onirim (Second Edition) | 0.15 | 0.19 | 0 | 0 |
Varghast | 2015 | 181161 | Brick Party | 0.12 | 0.19 | 0 | 0 |
Varghast | 2011 | 104006 | Village | 0.15 | 0.19 | 0 | 0 |
Varghast | 2018 | 246761 | Cahoots | 0.15 | 0.19 | 0 | 0 |
We can also more formally assess how well the model did in resampling by looking at the area under the receiver operating characteristic. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
username | outcome_type | .metric | .estimator | .estimate |
Varghast | own | roc_auc | binary | 0.874 |
Varghast | played | roc_auc | binary | 0.869 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing.
What games does the model think Varghast is most likely to own that are not in their collection?
username | yearpublished | game_id | name | pred_own | actual_own |
Varghast | 2019 | 266507 | Clank!: Legacy – Acquisitions Incorporated | 0.89 | 0 |
Varghast | 2000 | 478 | Citadels | 0.84 | 0 |
Varghast | 2005 | 15062 | Shadows over Camelot | 0.80 | 0 |
Varghast | 2019 | 283863 | The Magnificent | 0.76 | 0 |
Varghast | 2018 | 244711 | Newton | 0.72 | 0 |
What games does the model think Varghast is least likely to own that are in their collection?
username | yearpublished | game_id | name | pred_own | actual_own |
Varghast | 1900 | 521 | Crokinole | 0.00 | 1 |
Varghast | 2015 | 175117 | Celestia | 0.00 | 1 |
Varghast | 2018 | 247160 | Dinosaur Tea Party | 0.00 | 1 |
Varghast | 2018 | 264637 | Yokohama Duel | 0.01 | 1 |
Varghast | 2019 | 272453 | KeyForge: Age of Ascension | 0.01 | 1 |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned/played.
rank | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Takenoko | Targi | Lewis & Clark: The Expedition | Five Tribes | Mysterium | Kanagawa | Codenames: Duet | Newton | Clank!: Legacy – Acquisitions Incorporated |
2 | Mundus Novus | Robinson Crusoe: Adventures on the Cursed Island | Legacy: The Testament of Duke de Crecy | Patchwork | Codenames | Codenames: Pictures | Gloomhaven | Rising Sun | The Magnificent |
3 | Village | Terra Mystica | Room 25 | Deception: Murder in Hong Kong | Grand Austria Hotel | When I Dream | Breaking Bad: The Board Game | Blue Lagoon | Maracaibo |
4 | The Gnomes of Zavandor | Keyflower | Tash-Kalar: Arena of Legends | Splendor | 504 | Codenames: Deep Undercover | Azul | Gingerbread House | The Isle of Cats |
5 | Ninjato | Space Cadets | The Little Prince: Make Me a Planet | Camel Up | Plums | Beyond Baker Street | Gaia Project | Decrypto | Era: Medieval Age |
6 | Tragedy Looper | The Resistance: Avalon | Ultimate Werewolf: Inquisition | Ultimate Werewolf | Arboretum | Covert | Fog of Love | Shadows: Amsterdam | Queenz: To Bee or Not to Bee |
7 | Mage Knight Board Game | Il Vecchio | Patchistory | Istanbul | Brick Party | Timebomb | Altiplano | Pandemic: Fall of Rome | Sierra West |
8 | Pastiche | Legends of Andor | BANG! The Dice Game | Imperial Settlers | The King Is Dead | New Angeles | The Quest for El Dorado | Codenames: Harry Potter | Amul |
9 | Ora et Labora | Uchronia | Concept | Castles of Mad King Ludwig | FUSE | Explorers of the North Sea | Bunny Kingdom | Cahoots | The Crew: The Quest for Planet Nine |
10 | Pergamon: Second Edition | Love Letter | Scotland Yard Master | Spyfall | Raptor | Kingdomino | Codenames: Disney – Family Edition | Human Punishment: Social Deduction 2.0 | Chai |
11 | Mondo | Yedo | Longhorn | Dragon's Hoard | Mission: Red Planet (Second Edition) | Terraforming Mars | Bärenpark | Micropolis | Century: A New World |
12 | Trajan | Archipelago | Hanamikoji | Onirim (Second Edition) | Pandemic Legacy: Season 1 | Pandemic: Reign of Cthulhu | Downforce | Hardback | One Key |
13 | Dungeon Fighter | One Night Werewolf | UGO! | One Night Ultimate Werewolf | Elysium | Agricola (Revised Edition) | The Fox in the Forest | Prowler's Passage | The King's Dilemma |
14 | Discworld: Ankh-Morpork | The Manhattan Project | The Phantom Society | Sheriff of Nottingham | Mombasa | Honshū | Pulsar 2849 | The Grizzled: Armistice Edition | Noctiluca |
15 | PAX | Agricola: All Creatures Big and Small | Sushi Go! | Abyss | ...and then, we held hands. | Inis | Wendake | Spy Club | Obscurio |
16 | The Blue Lion | Lords of Waterdeep | Rococo | Chimera | Blood Rage | Clank!: A Deck-Building Adventure | Magic Maze | Azul: Stained Glass of Sintra | Nova Luna |
17 | Alcatraz: The Scapegoat | Tokaido | The Ravens of Thri Sahashri | Haru Ichiban | Texas Showdown | Sushi Go Party! | Codenames: Marvel | Gunkimono | Paris: La Cité de la Lumière |
18 | Old Men of the Forest | Libertalia | Eight-Minute Empire: Legends | Port Royal | One Night Revolution | Pandemic: Iberia | Twilight Imperium: Fourth Edition | Coimbra | Last Bastion |
19 | Letters from Whitechapel | Noah | Impulse | Dragon Run | Holmes: Sherlock & Mycroft | Dream Home | Werewords | Passing Through Petra | It's a Wonderful World |
20 | Principato | Eight-Minute Empire | Glass Road | Madame Ching | Bullfrogs | Assembly | Century: Spice Road | Reykholt | Watergate |
21 | Pantheon | Okiya | The Doom That Came to Atlantic City | Witness | Between Two Cities | Captain Sonar | Paper Tales | Narabi | The Quest for El Dorado: The Golden Temples |
22 | A Game of Thrones: The Board Game (Second Edition) | Suburbia | Händler der Karibik | Pandemic: The Cure | One Night Ultimate Werewolf: Daybreak | Archaeology: The New Expedition | Ex Libris | Imhotep: The Duel | Ishtar: Gardens of Babylon |
23 | Dr. Shark | Qin | Tajemnicze Domostwo | Gaïa | One Night Ultimate Vampire | Port Royal: Unterwegs! | Majesty: For the Realm | Patchwork Express | Tainted Grail: The Fall of Avalon |
24 | Panic Station | Shadows over Camelot: The Card Game | Forbidden Desert | Dead of Winter: A Crossroads Game | The Bloody Inn | The Oracle of Delphi | Smash Up: What Were We Thinking? | Century: Eastern Wonders | Marco Polo II: In the Service of the Khan |
25 | Nightfall | A Fake Artist Goes to New York | Carcassonne: South Seas | La Granja | Joraku | Camel Up Cards | Sundae Split | Luxor | Pandemic: Rapid Response |
Interactive table for predictions from resampling.
How well did a model trained on a user’s collection through 2019 perform in predicting games for the user from 2020?
username | outcome_type | yearpublished | .metric | .estimator | .estimate |
Varghast | own | 2020 | roc_auc | binary | 0.938 |
Varghast | played | 2020 | roc_auc | binary | 0.926 |
Table of top 25 games from 2020, highlighting games that the user owns.
username | yearpublished | game_id | name | pred_own | pred_played | actual_own | actual_played |
Varghast | 2020 | 288169 | The Fox in the Forest Duet | 0.56 | 0.49 | 1 | 1 |
Varghast | 2020 | 307844 | Atheneum: Mystic Library | 0.49 | 0.56 | 0 | 0 |
Varghast | 2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.43 | 0.41 | 0 | 0 |
Varghast | 2020 | 296151 | Viscounts of the West Kingdom | 0.43 | 0.38 | 0 | 0 |
Varghast | 2020 | 293556 | Gloomy Graves | 0.39 | 0.33 | 0 | 0 |
Varghast | 2020 | 184267 | On Mars | 0.33 | 0.43 | 0 | 0 |
Varghast | 2020 | 314040 | Pandemic Legacy: Season 0 | 0.25 | 0.17 | 0 | 0 |
Varghast | 2020 | 300322 | Hallertau | 0.22 | 0.22 | 0 | 0 |
Varghast | 2020 | 320819 | Dinner in Paris | 0.22 | 0.20 | 0 | 0 |
Varghast | 2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 0.21 | 0.18 | 0 | 0 |
Varghast | 2020 | 301767 | Mysterium Park | 0.20 | 0.17 | 1 | 1 |
Varghast | 2020 | 311193 | Anno 1800 | 0.20 | 0.23 | 0 | 0 |
Varghast | 2020 | 256317 | Guild Master | 0.17 | 0.20 | 0 | 0 |
Varghast | 2020 | 279537 | The Search for Planet X | 0.17 | 0.19 | 0 | 0 |
Varghast | 2020 | 293678 | Stellar | 0.16 | 0.17 | 1 | 1 |
Varghast | 2020 | 295486 | My City | 0.15 | 0.13 | 1 | 1 |
Varghast | 2020 | 313817 | Hello Neighbor: The Secret Neighbor Party Game | 0.15 | 0.17 | 0 | 0 |
Varghast | 2020 | 245658 | Unicorn Fever | 0.14 | 0.12 | 0 | 0 |
Varghast | 2020 | 316377 | 7 Wonders (Second Edition) | 0.14 | 0.16 | 0 | 0 |
Varghast | 2020 | 301880 | Raiders of Scythia | 0.13 | 0.11 | 0 | 0 |
Varghast | 2020 | 306735 | Under Falling Skies | 0.13 | 0.09 | 1 | 1 |
Varghast | 2020 | 319966 | The King Is Dead: Second Edition | 0.13 | 0.10 | 0 | 0 |
Varghast | 2020 | 323784 | Ghost Letters | 0.13 | 0.12 | 0 | 0 |
Varghast | 2020 | 299074 | Space Battle Lunchtime Card Game | 0.12 | 0.12 | 0 | 0 |
Varghast | 2020 | 309862 | Gudetama: The Tricky Egg Card Game | 0.12 | 0.13 | 0 | 0 |
Examine the top games for the test set.
username | yearpublished | game_id | name | rank | own | played |
Varghast | 2020 | 288169 | The Fox in the Forest Duet | 1 | 0.56 | 0.49 |
Varghast | 2020 | 307844 | Atheneum: Mystic Library | 2 | 0.49 | 0.56 |
Varghast | 2020 | 291457 | Gloomhaven: Jaws of the Lion | 3 | 0.43 | 0.41 |
Varghast | 2020 | 296151 | Viscounts of the West Kingdom | 4 | 0.43 | 0.38 |
Varghast | 2020 | 293556 | Gloomy Graves | 5 | 0.39 | 0.33 |
Varghast | 2020 | 184267 | On Mars | 6 | 0.33 | 0.43 |
Varghast | 2020 | 314040 | Pandemic Legacy: Season 0 | 7 | 0.25 | 0.17 |
Varghast | 2020 | 320819 | Dinner in Paris | 8 | 0.22 | 0.20 |
Varghast | 2020 | 300322 | Hallertau | 9 | 0.22 | 0.22 |
Varghast | 2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 10 | 0.21 | 0.18 |
Varghast | 2020 | 301767 | Mysterium Park | 11 | 0.20 | 0.17 |
Varghast | 2020 | 311193 | Anno 1800 | 12 | 0.20 | 0.23 |
Varghast | 2020 | 256317 | Guild Master | 13 | 0.17 | 0.20 |
Varghast | 2020 | 279537 | The Search for Planet X | 14 | 0.17 | 0.19 |
Varghast | 2020 | 293678 | Stellar | 15 | 0.16 | 0.17 |
Varghast | 2020 | 295486 | My City | 16 | 0.15 | 0.13 |
Varghast | 2020 | 313817 | Hello Neighbor: The Secret Neighbor Party Game | 17 | 0.15 | 0.17 |
Varghast | 2020 | 316377 | 7 Wonders (Second Edition) | 18 | 0.14 | 0.16 |
Varghast | 2020 | 245658 | Unicorn Fever | 19 | 0.14 | 0.12 |
Varghast | 2020 | 306735 | Under Falling Skies | 20 | 0.13 | 0.09 |
Varghast | 2020 | 319966 | The King Is Dead: Second Edition | 21 | 0.13 | 0.10 |
Varghast | 2020 | 301880 | Raiders of Scythia | 22 | 0.13 | 0.11 |
Varghast | 2020 | 323784 | Ghost Letters | 23 | 0.13 | 0.12 |
Varghast | 2020 | 299074 | Space Battle Lunchtime Card Game | 24 | 0.12 | 0.12 |
Varghast | 2020 | 309862 | Gudetama: The Tricky Egg Card Game | 25 | 0.12 | 0.13 |
Varghast | 2021 | 298102 | Roll Camera!: The Filmmaking Board Game | 1 | 0.68 | 0.65 |
Varghast | 2021 | 324856 | The Crew: Mission Deep Sea | 2 | 0.55 | 0.43 |
Varghast | 2021 | 343905 | Boonlake | 3 | 0.38 | 0.37 |
Varghast | 2021 | 310873 | Carnegie | 4 | 0.36 | 0.31 |
Varghast | 2021 | 291859 | Riftforce | 5 | 0.33 | 0.37 |
Varghast | 2021 | 332944 | Sobek: 2 Players | 6 | 0.30 | 0.29 |
Varghast | 2021 | 316287 | Quest | 7 | 0.30 | 0.27 |
Varghast | 2021 | 331635 | Kameloot | 8 | 0.27 | 0.28 |
Varghast | 2021 | 285967 | Ankh: Gods of Egypt | 9 | 0.27 | 0.21 |
Varghast | 2021 | 319792 | Fly-A-Way | 10 | 0.24 | 0.14 |
Varghast | 2021 | 340466 | Unfathomable | 11 | 0.23 | 0.27 |
Varghast | 2021 | 299255 | Vienna Connection | 12 | 0.22 | 0.14 |
Varghast | 2021 | 342848 | World of Warcraft: Wrath of the Lich King | 13 | 0.22 | 0.16 |
Varghast | 2021 | 313262 | Shamans | 14 | 0.19 | 0.15 |
Varghast | 2021 | 333553 | For the King (and Me) | 15 | 0.18 | 0.20 |
Varghast | 2021 | 291847 | Mantis Falls | 16 | 0.17 | 0.36 |
Varghast | 2021 | 342942 | Ark Nova | 17 | 0.16 | 0.19 |
Varghast | 2021 | 326804 | Rorschach | 18 | 0.16 | 0.15 |
Varghast | 2021 | 340455 | King of the Valley | 19 | 0.15 | 0.14 |
Varghast | 2021 | 290236 | Canvas | 20 | 0.15 | 0.13 |
Varghast | 2021 | 308989 | Bristol 1350 | 21 | 0.14 | 0.12 |
Varghast | 2021 | 339906 | The Hunger | 22 | 0.14 | 0.14 |
Varghast | 2021 | 282776 | Tumble Town | 23 | 0.13 | 0.14 |
Varghast | 2021 | 307862 | Dollars to Donuts | 24 | 0.13 | 0.09 |
Varghast | 2021 | 313730 | Harsh Shadows | 25 | 0.12 | 0.09 |
Varghast | 2022 | 283137 | Human Punishment: The Beginning | 1 | 0.33 | 0.37 |
Varghast | 2022 | 317511 | Tindaya | 2 | 0.31 | 0.52 |
Varghast | 2022 | 334065 | Verdant | 3 | 0.31 | 0.31 |
Varghast | 2022 | 295770 | Frosthaven | 4 | 0.24 | 0.20 |
Varghast | 2022 | 331106 | The Witcher: Old World | 5 | 0.24 | 0.21 |
Varghast | 2022 | 326945 | Castles of Mad King Ludwig: Collector's Edition | 6 | 0.14 | 0.15 |
Varghast | 2022 | 305096 | Endless Winter: Paleoamericans | 7 | 0.10 | 0.06 |
Varghast | 2022 | 304051 | Creature Comforts | 8 | 0.10 | 0.10 |
Varghast | 2022 | 335427 | Wild: Serengeti | 9 | 0.09 | 0.09 |
Varghast | 2022 | 319807 | Shogun no Katana | 10 | 0.09 | 0.08 |
Varghast | 2022 | 320718 | Hidden Leaders | 11 | 0.06 | 0.06 |
Varghast | 2022 | 322289 | Darwin's Journey | 12 | 0.06 | 0.05 |
Varghast | 2022 | 312959 | Rallyman: DIRT | 13 | 0.06 | 0.06 |
Varghast | 2022 | 295374 | Long Shot: The Dice Game | 14 | 0.06 | 0.05 |
Varghast | 2022 | 348463 | ECO: Coral Reef | 15 | 0.06 | 0.06 |
Varghast | 2022 | 271601 | Feed the Kraken | 16 | 0.05 | 0.06 |
Varghast | 2022 | 317321 | Darkest Dungeon: The Board Game | 17 | 0.05 | 0.04 |
Varghast | 2022 | 280726 | Legacies | 18 | 0.05 | 0.05 |
Varghast | 2022 | 240980 | Blood on the Clocktower | 19 | 0.04 | 0.04 |
Varghast | 2022 | 324090 | Scarface 1920 | 20 | 0.04 | 0.05 |
Varghast | 2022 | 256680 | Return to Dark Tower | 21 | 0.04 | 0.03 |
Varghast | 2022 | 258779 | Planet Unknown | 22 | 0.04 | 0.04 |
Varghast | 2022 | 338067 | 6: Siege – The Board Game | 23 | 0.04 | 0.04 |
Varghast | 2022 | 273814 | Deliverance | 24 | 0.04 | 0.07 |
Varghast | 2022 | 281549 | Beast | 25 | 0.04 | 0.04 |