MLB data in spreadsheets for historical seasons and current season. You can filter by data type or by season and view sample files to see what columns are included in each dataset.
MLB Data In Excel Spreadsheets
How MLB Data Works & Who It Is For
BigDataBall does the collection, cleaning and unifying of the various MLB stats, odds and fantasy data obtained across many sources and enriches it in a xlsx output format. Datasets enables doing MLB data analytics at your own convenience and easiness of using Excel spreadsheet. Our MLB data is used by individuals such as bettors/fantasy players, data journalists, and academic researchers.
What You Can Do With MLB Datasets
Start working on the data in Excel in no time, or you can directly import data from Excel into an analysis or visualization tool, R (R is most commonly adopted by our users), or Google Sheets. Once the import is completed, several analyses can be done on the given information to learn more about the baseball players and games. Here are some ways:
Player Performance Analysis
– Range of batting averages: Look at the range of batting averages to figure out how well players did.
– Home run distribution: Look at how home runs are spread out to find power hitters.
– Stolen base analysis: figure out how often players steal bases and how often they succeed.
– Strikeout analysis: Look at how often players strike out to figure out how good they are at making contact.
– On-base percentage (OBP): Use the OBP to figure out how well a player can get to second base.
Assess Team Performance
– Win-loss analysis: Look at how well teams did based on which pitchers won and which pitchers lost.
– Runs per game: Figure out how many runs each team scores on average per game.
– Earned run average (ERA): To figure out how well the starting pitchers on each team are doing, add up their ERAs.
Game Analysis
– Run distribution: Look at how the runs made in games are spread out to find games with a lot of runs.
– Pitch count analysis: Find out how many pitches pitchers throw on average in each game.
– Analysis of a pitcher’s quality start: figure out what percentage of their starts are good.
– No-hitter analysis: Find games where pitchers didn’t give up any hits.
Analysis of Players and Teams
– How each player contribute for his team: Analyze the stats of each person based on which team they are on.
– How players do at their positions: Compare how well each player did in his or her role.
Spotting Trends Using Historical MLB Data
– Seasonal performance trends: Look at the performance of players and teams over several seasons to find trends and patterns.
– Handedness analysis is a way to judge how well a player hits or pitches based on which hand they use.
Make Better Conclusions Based on Historical MLB Betting Odds Data
The betting odds for each game in the dataset add a new level to the analyses and can give clues about how the betting market thinks games will turn out. MLB Odds data from the past can be useful in a number of ways:
Find Out Power Rankings
– Comparing pre-game odds: Looking at historical odds data lets you figure out how teams were seen in the past in terms of their strength and possibility of winning.
– Assessing underdogs and favorites: If you look at the odds, you can see when underdogs won or when favorites lost, which can help you predict unexpected results and possible upsets.
Learn How the MLB Betting Market Moves
– Line movement analysis: By looking at the difference between the odds at the beginning and the odds at the end, you can see how the market’s mood changed over time. Changes in the odds that are big enough to be noticed can be caused by things like accidents, weather, or public opinion.
– Analysis of public vs. sharp money: Looking at how the odds change can help you tell the difference between how the public and sharp money affect the market. For example, a big change in the odds right before a game could mean that more knowledgeable or professional bettors have joined the market.
Spot Value Bet Opportunities
– Comparing odds and outcomes: You can use historical odds data to judge how accurate the betting market’s forecasts are. By comparing the suggested probabilities from the odds to the actual results, you can figure out when the market may have undervalued or overvalued certain teams or players.
– Making betting strategies: You can use historical odds data to make and try different betting strategies, such as taking advantage of biases in the market, finding profitable betting opportunities, or figuring out how well different betting systems work.
Predictive Modeling
– Employ your own prediction model by adding odds as features: Data on chances from the past can be added to predictive models as features. By taking into account how the market thinks a game will turn out, models may be able to make more accurate predictions.
Changing performance metrics: Changing player or team performance metrics based on odds can give a more accurate picture of their real performance by taking into account how good the other team is.
Overall, having a rich MLB dataset can help you understand where there are chances for value betting. It gives a more complete picture of the game and helps find hidden patterns and trends out of the numbers alone.
