About Magla Metrics

We provide data, not picks. Our platform empowers you with advanced metrics, probabilities, and predictive models, giving you the tools and transparency to enhance your strategies and make smarter, more informed decisions on your own.

All models are updated in real-time as new lineup, injury, and game information becomes available for MLB, NBA, NFL, and Soccer. Our system ingests live data feeds and recalculates player and team projections continuously throughout the day and even during games as in-play stats evolve. Do not be surprised to see predictions change on the fly as games unfold based on in-game play contributing to stat changes.

We leverage official league APIs to ensure data accuracy, pulling structured datasets for lineups, starters, player performance, injuries, and venue environments directly from the source.

Each prediction model is uniquely calibrated using key statistical indicators relevant to that sport, from batting splits and home/away performance in MLB to scoring efficiency and pace-of-play metrics in NBA, NFL, and Soccer.

Our platform utilizes advanced statistical modeling, custom weighting systems, and machine learning algorithms to normalize and process player, team, and venue data. These models dynamically adapt to changing inputs to deliver predictive accuracy across sports.

We convert raw model scores into user-friendly outputs, displayed as percentage probabilities or confidence ratings on a 0-100+ scale to help you quickly identify opportunities and risk factors within each slate.

Predictions and results are presented through simple, clean tables ranked by likelihood. This allows users to quickly focus on high-confidence predictions without the noise and clutter of unnecessary data.

MLB Game Winner Prediction Model How to read

• Away Indicators / Home Indicators
  Snapshot stats for each team, including starting pitcher ERA, combined batting averages, recent win rate, recent bat strength, and a final model score for that team.
• Signal Strength
  Difference between team model scores on a 0–100+ scale. The higher the signal strength, the stronger the prediction.
• Prediction
  Team with the higher model score is the predicted game winner.
• Vegas Odds
  Consensus betting odds accross the major sportsbooks as of that morning. Not updated in real time.
• Result
  Displays live score and final winner upon completion.

Tip: Signal strength over 75 indicates a strong signal.

MLB YRFI / NRFI Prediction Model How to read

• Ballpark
  Ballpark factors are weighed into the model.
• Combined Average YRFI
  Combined season long historical average of each team to score a run in the first inning.
• Combined Pitcher ERA
  Combined ERA of each team's starting pitcher.
• Top-3 Batters Considered
  Model will only consider the recent hotness of the top 3 batters on each team once official lineups are released. If this column says "No" then the model score is not reflective of the top 3 batters. This will automatically update to "Yes" and the model score will adjust once official lineups are released for that game.
• Model Score
  Aggregated view that drives the Yes/No lean for a first‑inning run. The higher the score the more likelihood of YRFI and the lower the score the more likelihood of NRFI. Scores in the middle around 40-50% are slight leans at best, essentially coinflips.
• Prediction
  YRFI or NRFI prediction based on the model score.
• Result
  First‑inning outcome upon completion.

Tip: Model score over 75% indicates a strong signal for YRFI and under 25% indicates a strong signal for NRFI.

MLB Player Homerun Prediction Model (Top 40) How to read

• Opp Pitcher HR/9
  Average number of homeruns given up by the opposing starting pitcher per 9 innings.
• L5 HRs
  Number of homeruns hit in last 5 games.
• Ballpark
  Ballpark factors are weighed into the model.
• Model Score
  Higher model score suggests stronger homerun likelihood relative to the full slate.
• Result
  Displays a checkmark when the player hits a homerun.

Tip: Model score over 100 indicates a very strong signal.

MLB Player Hits Prediction Model (Top 40) How to read

• L10 Hit Games
  Number of games with at least 1 hit in that player's last 10 games.
• Ballpark
  Ballpark factors are weighed into the model.
• Model Score
  Higher model score suggests stronger hit likelihood relative to the full slate.
• Result
  Displays a checkmark when the player gets a hit.

Tip: Model score over 100 indicates a very strong signal.

NFL Game Winner Prediction Model How to read

• Statistical Sources
  Week 1 predictions are based on previous season's statistics applied to current season depth charts. As current season progresses, current season statistics are automatically trickled into the model. Model accuracy should improve drastically as current season progresses.
• Away Team / Home Team
  Snapshot stats for each team and a final model score for that team.
• Signal Strength
  Difference between team model scores on a 0–500+ scale. The higher the signal strength, the stronger the prediction.
• Prediction
  Team with the higher model score is the predicted game winner.
• Result
  Displays live score and final winner upon completion.

Tip: Signal strength over 250 indicates a strong signal.

NFL Anytime Touchdown Prediction Model (Top 40) How to read

• Statistical Sources
  Week 1 predictions are based on previous season's statistics applied to current season depth charts. As current season progresses, current season statistics are automatically trickled into the model. Model accuracy should improve drastically as current season progresses.
• Model Score
  Higher model score suggests stronger hit likelihood relative to the full slate.
• Result
  Displays a checkmark when the player gets a hit.

Tip: Model score over 0.500 indicates a strong signal.

UFC Fight Predictions How to read

• UFC model is under construction as historical data sets are being processed. Stay tuned for more information.

Tip: Coming soon.