Marked PPM: MLB

Each spring, Marked rolls out its latest baseball predictions for another season of major league action. We first introduced our MLB team ratings during the 2020 season and used them to survey the playoff picture. At this same time, we began publishing our MLB Predictions dashboard, which uses our team ratings to preview upcoming games and show the chance that each team will make the postseason (or win the World Series), Here’s how they work.

Team ratings

Our MLB projection system is the most complex out of all the sports Marked PPM can predict. What makes it so intricute is the amount of variance between the players active in each game. Because of this, the approach used in the MLB version of Marked PPM is entirely player based, with no full team data used (to access the ratings for each player, subscribe to an analytics plan, analytics+ plan, or the mecca plan). In addition to individual player ratings for position players and pitchers, home-field advantage, park and era effects, travel, and rest are all taken into account.

Once the team's starting pitcher, and their lineup is announced, then ratings for the team can be formulated. The ratings are on a scale of 100, with higher ratings being attributed to higher projected runs scored, and lower ratings attributed to lower projected runs scored. Therefore, you want your team's hitting rating to be above 100, and want your teams pitching and fielding ratings to be below 100. Once the rating for each aspect of the team is calculated, they will then be adjusted based on the opponents skill level to create the final game

For our purposes, each MLB team carries a rating that estimates its current skill level. (The average is about 1500.) After every game is played, the winning team gains some rating points while the losing team loses the same number of points, based on the chances our model gave each team to win the game beforehand (and the margin of victory). For example, a win by a big underdog results in a bigger exchange of points than a win by a favorite — and the larger the margin of victory, the larger the exchange.

Pregame team rating adjustments

Before every game, we adjust each team’s rating based on whether it has home-field advantage, how far it has traveled to the game, how many days of rest it’s had and which pitcher is slated to start.

Here are the particulars of those first three adjustments:

  • Home-field advantage is worth 5 rating points. For games played without fans in attendance, home-field advantage is worth 2.5 rating points.

  • The penalty for travel is worth up to about 4 points and is calculated with miles_traveled**(1.0/3.0) * -0.31

  • Each day of rest (up to a maximum of three) is worth 1 point.

Like our team ratings, these game scores are normalized for eras and stadiums, so pitchers from throughout history can be directly compared with one another. They’re also adjusted to take the opposing team’s offensive strength into account, so a pitcher earns more credit for a great start against a top team than against a mediocre one.

Whenever a pitcher makes a start, it contributes to his rolling game score (rGS) — the model’s best guess as to how the pitcher would perform in a typical start. (Pitchers who haven’t started before are assigned a below-average rGS, but that score is more influenced by each successive start than the score of an established pitcher.) In addition to each pitcher’s rGS, we maintain an rGS for each team that incorporates every game score produced by any starting pitcher for that team.

A pitcher’s adjustment to his team’s rating, then, is all about his rGS relative to his team’s rGS; pitchers who are better than the team’s rGS give the team a bonus when they start, and pitchers below the team’s rGS give the team a penalty. Note that one pitcher may have a higher overall rGS than another pitcher but a smaller team rating adjustment; this generally means that his team has a better rotation aside from him, or that he started more games (and thus, his game scores contributed more to the team’s rGS).

A pitcher’s adjustment is calculated with:

ratingAdj = 4.7 * (pitcher\,rGS – team\,rGS)

The addition of starting pitcher adjustments gives our model about a 1 percentage point improvement in the percentage of games correctly “called” and a corresponding improvement in the mean squared error of our game-by-game forecasts.

Preseason ratings

Before a season begins, we have to come up with a set of starting ratings for each team. Our preseason team ratings are made up of two components:

  • 67 percent comes from the team’s preseason win projection according to three computer projection systems: Baseball Prospectus’s PECOTA, FanGraphs’ depth charts and Clay Davenport’s predictions — all scaled to an Elo range.

  • 33 percent comes from the team’s final rating at the end of the previous season, reverted to the mean by one-third.

As part of all this, we also need to compute a preseason rolling game score rating for each team’s pitching staff. Our preseason team rGS ratings are an average of the team’s starting pitcher rGSs, weighted by the individual pitchers’ projected starts in FanGraphs’ depth charts.

From ratings to a forecast

Now it’s time to turn these team and player ratings into probabilities, tracking how often each team makes the playoffs or wins the World Series. To do this, we run Monte Carlo simulations, playing out the season thousands of times. As with our other sports forecasts, we run these simulations “hot,” meaning that a team’s rating doesn’t stay static — rather, it changes within each simulated season based on the results of every simulated game, including the bonus for playoff wins. Starting with the 2020 season, our team ratings change at three-quarters of the speed they previously changed. As a result, the “hot” simulations have a bit less variance, and the forecast’s overall uncertainty is decreased a touch.

These simulated games also account for starting pitching matchups; for games in which a starter is not yet known, we assume that the most-rested pitcher from the team’s regular rotation will play. During the postseason, we assume teams use a four-man rotation.

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