DataBaller features
Last updated September 8, 2026
Sports Intelligence on Demand
Ask your NBA, NFL, and MLB questions. Get original in-depth analysis and predictive insights. Discover what’s driving results, compare players, and explore what comes next.
Put DataBaller’s advanced sports analytics system to work on your questions. It brings together comprehensive sports performance data, exacting calculations, and our own performance models. Your question directs the work: DataBaller brings the relevant calculations, comparisons and forecasts together in one investigation.
Choose the player, team, matchup or stretch of games. Explore the findings and the data behind them, then ask what you want to investigate next.
Understand performance
Go beyond season totals to understand how players produce and why team results change. Compare stretches of games, separate playing time from production, and consider the strength of the opponents faced. Put player value in context with workload, performance and measures such as MLB wins above replacement.
Player analysis. Explore statistics, game logs and league leaders. Go beyond the season total to understand how a player produces.
Team analysis. Explore standings and team statistics to understand how results have changed.
Trends over time. Focus on a stretch of games, compare it with an earlier period, and investigate which numbers moved. Separate changes in playing time from changes in production per minute or opportunity.
Opponent context. Examine performance against the strength of the teams faced. Investigate whether a scoring surge or improved run prevention looks different once the schedule is considered.
League leaders. Explore who leads the league in available statistics and compare their production.
Coverage: NBA, NFL and MLB; available statistics and comparisons vary by league. MLB WAR is specific to baseball.
Last verified: September 8, 2026. Related release: v0.6, September 1, 2026—MLB player value and historical-coverage checks. Read the release notes.
Compare players and teams
Put production, efficiency and playing time side by side to explore a player comparison, fantasy trade or roster move. Bring your league’s scoring rules to focus on what matters to you. Compare team strengths and recent results for a matchup, or examine available odds and line movement alongside the performance analysis.
Player comparisons. Put production, efficiency and playing time side by side. Compare the same period or examine how each player’s recent performance differs from their own history.
Fantasy research. Bring a player comparison, trade question or roster question, along with your league’s scoring rules. Explore the differences that matter to your situation. NFL fantasy rankings and average draft position add context about how players are being valued in drafts.
Team comparisons. Compare team strengths and recent results. DataBaller’s Power Rating provides another way to examine how teams stack up.
Matchup analysis. Bring team comparisons and available player context to a specific matchup, with supported estimates explained alongside their assumptions.
Research the odds. Explore available sportsbook spreads, moneylines, totals and player props alongside performance analysis. Where recorded history exists, investigate how a line has moved. MLB lines and props are available today; NBA and NFL coverage will depend on recorded markets becoming available.
Coverage: player and team comparisons across NBA, NFL and MLB. Fantasy market data, sportsbook coverage and recorded odds history vary; an available line is a dated quote, not a promise of a currently executable price.
Last verified: September 8, 2026. Related release: v0.5, August 24, 2026—team models and matchup forecasts. Read the release notes.
Explore our performance models
Investigate changes in a player’s role, whether recent production looks sustainable, and where scoring might head next. Our own models also compare team strength and examine whether wins and losses line up with scoring margins. Explore the factors behind each reading and what they suggest for your player, team or matchup.
DataBaller’s Performance Shift — Has their role changed? Examine changes in a player’s deployment, such as minutes and usage in basketball or carries and targets in football. Available for NBA and NFL players; there is no MLB Performance Shift model.
DataBaller’s Sustainability Score — How does their recent production compare with their established level? Investigate shooting efficiency in basketball, outcomes on balls in play in baseball, and yards per touch in football. The model explains the relevant differences and what its reading means for that sport.
DataBaller’s Scoring Shift — Where might production go next? Explore projected changes in NBA scoring, MLB batting or pitching production, and NFL rushing or receiving production. Examine the factors contributing to a forecast. NFL quarterback scoring forecasts are not available. NBA offseason readings describe the completed season; they are not forecasts for the next season.
DataBaller’s Power Rating — How strong is this team? Compare NBA, NFL and MLB teams on a scale tied to scoring margins, and explore supported matchup outlooks.
DataBaller’s Team Sustainability — Does the record match the performance? Compare a team’s wins and losses with what its scoring margins suggest across the NBA, NFL and MLB.
Each model answers a specific question. Its coverage depends on the player or team, available history and the period being analyzed. Forecasts apply to a defined horizon; the explanation should make that horizon and the limits of the outlook clear.
Last verified: September 8, 2026. Related releases: v0.5, August 24, 2026—team models; v0.6, September 1, 2026—NFL and MLB Scoring Shift. Explore the model methods · Read the release notes.
Direct the investigation through conversation
Ask in your own words. Choose the players, teams, matchup or period you want to examine. DataBaller’s AI puts the analytical system to work on your question.
Keep digging. Ask what changed, compare another player, narrow the period or explore a different explanation. Follow-ups let you take the analysis further as new questions emerge.
Explore charts and profiles. See comparisons and trends in charts where they help explain the findings. Open linked player and team profiles to explore more context.
Return to your conversations. Revisit past analyses and continue an investigation on desktop or mobile.
Last verified: September 8, 2026.
Read an analysis, then make it your own
Published stories. Browse public DataBaller analyses without an account. See what other investigations uncovered, with the date and context of each story.
Follow your own angle. Start a follow-up conversation from a published story to explore the question that interests you.
Share eligible analyses. Analyses that meet the publication requirements can become public stories. Publication eligibility and account controls determine what can be shared.
Last verified: September 8, 2026. Explore stories.
Coverage and continued improvement
DataBaller analyzes NBA, NFL and MLB players, teams and games using current and historical records. The depth of history and the statistics available depend on the league and the question. Injury and roster information can add context where available; an absence from an injury report does not establish that a player is healthy or available.
We continue to expand the data, develop our models and improve the experience. This page describes available capabilities. Our broader ambition is to build the world’s best sports intelligence platform: the most comprehensive, the most insightful, and the easiest to use.
“Last verified” records when we checked a section against the product. Release notes explain what changed and when. An analysis has its own data and model dates; this page’s verification date does not make a historical story a current outlook.
About DataBaller · What’s new · Plans and access
What do you want to find out? Ask DataBaller.
See DataBaller at work
Three questions. Three ways to go deeper into the game. Read the original DataBaller analyses.
Same record. A different story.
MLB · Understand performance · August 9–September 11, 2026
The Dodgers went 10–5 in two consecutive 15-game stretches. But scoring rose from 4.47 to 5.20 runs a game—and accounting for opponents made the offensive improvement more pronounced. See what the record alone missed.
Your league. Your scoring. A different comparison.
NBA · Compare players and teams · 2025–26 regular season
Compare Doncic and SGA under one fan’s scoring rules. See how rebounds, assists, turnovers and games played shape the result—and why points per game tell only part of the story.
Read the Doncic–SGA analysis →
Lower scoring. Nearly the same minutes.
NBA · Explore our performance models · 2025–26 regular season
Austin Reaves’s scoring fell from 28.4 to 20.65 points a game between his first and last 20 appearances. His minutes barely changed. Explore the shot volume and efficiency behind the drop, with DataBaller’s Performance Shift adding context about his role against his longer-term baseline.