---
updatedAt: 2026-04-23T20:18:52.000Z
agentTools:
  siteIndex: https://developer.sportradar.com/llms.txt
  projectIndex: https://developer.sportradar.com/insights/llms.txt
---

# NBA Player Betting Trends Docs

## Intro

The Player Betting Trends endpoint provides detailed insights into individual player performance in various betting scenarios. Player betting trends are available for various sport-specific individual performance metrics, such as hits, points scored, rushing yards, and other relevant statistics. By analyzing historical data and context-dependent trends, users can understand how players perform under different conditions.

An example of a player betting trend can be seen below:

<Image align="center" border={true} src="https://files.readme.io/699d29bfe6c422fcf4b29bd609507405ce9dda2a55530b12b76aed328a2ed9c4-image.png" className="border" />

<br />

## Betting Markets Offered

* Total steals (including overtime)
* Total blocks (including overtime)
* Total points (including overtime)
* Total assists (including overtime)
* Total rebounds (including overtime)
* Total 3-point field goals (including overtime)
* Total points plus assists plus rebounds (including overtime)
* Total points plus rebounds (including overtime)
* Total points plus assists (including overtime)
* Total rebounds plus assists (including overtime)

<br />

## One-Parameter Scenarios

<Table align={["left","left"]}>
  <thead>
    <tr>
      <th>
        Scenario / Filter
      </th>

      <th>
        Description
      </th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td>
        **Straight Up**
      </td>

      <td>
        Performance over last X games without any specific conditions
      </td>
    </tr>

    <tr>
      <td>
        **Home / Away**
      </td>

      <td>
        Performance based on whether the game is at home or on the road
      </td>
    </tr>

    <tr>
      <td>
        **Vs Top Defense**
      </td>

      <td>
        Performance against top defensive teams
      </td>
    </tr>

    <tr>
      <td>
        **Vs Bottom Defense**
      </td>

      <td>
        Performance against bottom defensive teams
      </td>
    </tr>

    <tr>
      <td>
        **B2B Team Flag**
      </td>

      <td>
        Performance in back-to-back games
      </td>
    </tr>

    <tr>
      <td>
        **Opponent WP**
      </td>

      <td>
        Performance against teams with a winning or losing record
      </td>
    </tr>

    <tr>
      <td>
        * _Favorite /  
          Underdog_*
      </td>

      <td>
        Performance as a favorite or underdog in the matchup
      </td>
    </tr>

    <tr>
      <td>
        **After Result***
      </td>

      <td>
        Performance after a win or loss in the previous game
      </td>
    </tr>

    <tr>
      <td>
        **Opponent**
      </td>

      <td>
        Performance against specific opponents
      </td>
    </tr>

    <tr>
      <td>
        **Season Type**
      </td>

      <td>
        Performance during different parts of the season (e.g., regular season, playoffs)
      </td>
    </tr>
  </tbody>
</Table>

* Only available after first games of season (i.e. does not go back to previous season)

<br />

## One-Parameter Scenario Examples

* Luka Doncic has failed to exceed 32.5 points in 4 straight playoff games (29.5 points/game average)
* Luka Doncic has exceeded 1.5 steals in 4 of his last 5 games against top 10 scoring defenses (2.4 steals/game average)
* Luka Doncic has failed to exceed 42.5 points + rebounds in 11 of his last 12 games after a win (36.8 points + rebounds/game average)

<br />

## Two-Parameter Scenarios

<Table align={["left","left"]}>
  <thead>
    <tr>
      <th>
        Scenario / Filter
      </th>

      <th>
        Description
      </th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td>
        * _Home / Away + Vs
          Bottom Defense_*
      </td>

      <td>
        Performance at home or on the road against bottom defensive teams
      </td>
    </tr>

    <tr>
      <td>
        * _Home / Away + Vs  
          Top Defense_*
      </td>

      <td>
        Performance at home or on the road against top defensive teams
      </td>
    </tr>

    <tr>
      <td>
        * _Home / Away + After  
          Result_**
      </td>

      <td>
        Performance at home or on the road after a win or loss
      </td>
    </tr>

    <tr>
      <td>
        * _Home / Away + B2B  
          Team Flag_*
      </td>

      <td>
        Performance at home or on the road in back-to-back games
      </td>
    </tr>

    <tr>
      <td>
        * _Home / Away +  
          Opponent WP_*
      </td>

      <td>
        Performance at home or on the road against teams with a winning or losing record
      </td>
    </tr>

    <tr>
      <td>
        * _Home / Away +  
          Favorite / Underdog_*
      </td>

      <td>
        Performance at home or on the road as a favorite or underdog
      </td>
    </tr>
  </tbody>
</Table>

* Only available after first game of season (i.e. does not go back to previous season)

<br />

## Two-Parameter Scenario Examples

* Luka Doncic has exceeded 3.5 three pointers made in 6 of his last 7 games on the road as an underdog (4.6 three pointers made/game average)
* Luka Doncic has exceeded 9.5 assists in 8 of his last 9 games at home against opponents with a losing recor (11.1 assists/game average)
* Luka Doncic has exceeded 8.5 rebounds in 13 of his last 15 games on the road after a win (10.2 rebounds/game average)

<br />

## Data Points

* **day:** The date of the event in YYYYMMDD format.
* **book:** The name of the sportsbook providing the odds.
* **line:** The line associated with the given market (if applicable).
* **odds:** The betting odds for the market.
* **rank:** The rank of the trend in the latest set of trends produced
* **type:** A dictionary containing details about the type of bet:
* **flavor:** Additional flavor text or subcategory for the bet.
* **market:** The market type for the bet (e.g., moneyline).
* **sport:** The sport the data pertains to (e.g., MLB).
* **total:** The consensus total line for the game
* **ngames:** The number of games considered in the trend.
* **opp\_id:** The sportradar US-id (UUID) for the opposing team.
* **param1:** The first parameter defining the scenario/filter for the trend (e.g. “opp”)
* **value1:** The value of the first parameter (e.g. “NYJ”)
* **param2:** The first parameter defining the scenario/filter for the trend (if applicable)
* **value2:** The value of the second parameter.
* **spread:** The point spread for the game.
* **book\_id:** The unique sportradar identifier for the sportsbook.
* **game\_id:** The unique sportradar US-id (UUID) for the game.
* **matchup:** The matchup identifier for the event in format:\*\* \{AwayTeam}*at*\{HomeTeam}.
* **team\_id:** The unique sportradar US-id (UUID) for the team.
* **weekday:** The day of the week the game is played.
* **prop\_id:** The unique Fansure assigned identifier for the trend. Same as tracking\_id
* **cover\_pct:** The percentage of time the line is exceeded in the games in the trend
* **data\_type:** team\_betting\_trends
* **game\_date:** The date and time of the game in ISO 8601 format.
* **odds\_type:** The type of odds (e.g., moneyline).
* **opp\_sr\_id:** The unique sportradar US-id (UUID) for the opposing team
* **statistic:** The statistic being referred to by the trend (e.g. for moneyline, statistic = wins)
* **team\_name:** The full name of the team.
* **text\_long:** A detailed description of the trend.
* **date\_lastn:** The dates of the n games which define the trend in ascending order.
* **game\_sr\_id:** The unique sportradar id (srid) for the game
* **push\_lastn:** The number of push outcomes in the n games in the trend window.
* **team\_sr\_id:** The unique sportradar id (srid) for the team
* **text\_short:** A short description of the trend.
* **trackingId:** The unique Fansure assigned tracking ID for the trend. Same as prop\_id
* **trend\_type:** The type of trend (hot or cold).
* **under\_odds:** The betting odds for the under (if applicable).
* **cover\_lastn:** The number of times the line was exceeded in the n games in the trend
* **stats\_lastn:** List of statistical values associated with each of the n games in the trend
* **abbreviation:** The abbreviation of the team name.
* **content\_long:** A detailed description of the trend including the odds.
* **gameId\_lastn:** List of the unique sportradar US-id (UUID) for each game in the trend
* **losses\_lastn:** The number of times the line was not exceeded in the n games in the trend
* **odds\_type\_id:** The unique sportradar identifier for the odds type.
* **matchup\_lastn:** List of the matchup strings for each game in the trend.
* **opp\_team\_name:** The full name of the opposing team.
* **interest\_score:** The interest score for the trend.
* **seasontype\_lastn:** List of the season type (e.g., REG, PST) for the n games in the trend
* **best:** Indicates whether this is the best available odds or line for the event (true / false).
* **position:** The position of the player in the context of the data (e.g., P for pitcher).
* **market\_id:** The unique identifier for the betting market.
* **over\_odds:** The betting odds for the over.
* **exceed\_lastn:** The number of times the line was exceeded in the n games in the trend
* **participant\_id:** The unique sportradar US-id (UUID) for the participant (player).
* **mean\_performance:** The player’s average performance for the statistic of interest in the games covered by the trend
* **player\_relevance:** The relevance score of the player associated with the trend
* **participant\_sr\_id:** The unique sportradar id (srid) for the participant (player)
* **participant\_full\_name:** The full name of the participant (player).