Filter WNBA datasets and in-season plans by class, category, or in-season plan. View samples to see the content and format of the dataset.
* You can sign up for a free account and get the 30% member discount on all of the WNBA historical datasets.
* You can contact us to get your 15% renewal discount on any season pass. Note that you should have purchased a “season pass” before.
The information inside BigDataBall’s WNBA datasets is invaluable for analyzing WNBA games, players. With a little to no Excel skills, BigDataBall’s WNBA datasets can be very helpful in understanding the WNBA and making educated choices about the women’s basketball sport.
DATASET The dataset the game belongs to
DATE Date of the game
TEAM Team name
VENUE Venue of the game for the team. Either played on the 'Road' or at 'Home'
1Q First quarter score
2Q Second quarter score
3Q Third quarter score
4Q Fourth quarter score
OT1 First over-time period score
OT2 Second over-time period score
OT3 Third over-time period score
OT4 Fourth over-time period score
OT5 Fifth over-time period score
F Total points scored at the end of the game
MIN Total minutes that the team (sum all players' individual times) played.
FG Field Goals Made
FGA Field Goals Attempted
3P Three Point Field Goals Made
3PA Three Point Field Goals Attempted
FT Free Throws Made
FTA Free Throws Attempted
OR Offensive Rebounds
DR Defensive Rebounds
TOT Total Rebounds
PF Personal Fouls
TO Total number of turnovers assigned to players
TO TO (Total turnovers assigned to players)+(Total turnovers assigned to teams)
POSS Total possessions. It is assumed that both teams use same number of possessions in a game
PACE Estimate of number of possessions per 48 minutes by a team
OEFF Offensive Efficiency
DEFF Defensive Efficiency
TEAM REST DAYS Rest days type of the team
OPENING SPREAD Opening spread (in numeric format)
CLOSING ODDS Closing odds (spread and O/U in numeric format)
1st HALF ODDS First half odds in numeric format
2nd HALF ODDS Second half odds in numeric format
Consider how various factors affect the outcome of games. The WNBA data can be used to examine the impact of intangibles on game results, such as home court advantage, player injuries, and rest days. Researchers can utilize this data to improve player or game selection based on their strengths and weaknesses. You can perform several analysis with this information, such as:
Project the outcome of upcoming games: Models that forecast a team’s likelihood of winning can be constructed using data found in the box scores. If you want to know how the WNBA betting market thinks a game will turn out, look at the betting odds.
Recognize WNBA League Wide Patterns: The historical WNBA data can be used to follow WNBA game style changes over the time. You can look at stats like the game’s scoring, offensive / defensive efficieny, pace (game-tempo) growth or decline, or the percentage of made three-pointers. Get ahead of the competition and create your strategy that reflects the current WNBA facts.
Create A Betting Model: You can utilize the WNBA datasets to build your winning betting strategies. You could, for instance, build a model that uses box score stats and play-by-play data to forecast the results of games. Another option is to devise a method for finding games with misaligned betting odds.
The Impact of Home Court: Find out how much of a difference home court makes and look at how teams or even the players perform on the road compared at their own arena.
The Impact of Rest Days: You can find out how much rest your players need to be at their best by analyzing the effect of rest days on team performance.
The Impact of Key Player Injuries: You could pinpoint the most significant players who contribute a team’s W/L record. This would be useful for pinpointing replacement players and focusing new minutes distribution.