The MLB season will be over in a week or so. That means the 2024 season is just around the corner!
I am using ChatGPT for some insight into my home-made projections while I await Steamer. Here’s what she says about projecting a player’s HR total in response to the following query:
ME: In MLB fantasy baseball, what are the best predictive metrics like barrel rate to predict a player’s homerun total the following season?
In MLB fantasy baseball, predicting a player’s home run total for the following season can be challenging, but there are several metrics and factors you can consider to make more informed projections. While barrel rate is a valuable metric, it’s important to combine it with other statistics and factors to create a well-rounded projection. Here are some key metrics and considerations to help you predict a player’s home run total:
Barrel Rate: Barrel rate measures how often a player makes ideal contact with the ball, resulting in the best combination of exit velocity and launch angle for home runs. A high barrel rate indicates a player’s ability to consistently hit the ball hard and at an optimal angle. This metric can be a good indicator of power potential.
Exit Velocity: Exit velocity measures how fast the ball comes off a player’s bat. Players with consistently high exit velocities are more likely to hit home runs because they generate more power. Statcast data provides exit velocity information.
Launch Angle: A player’s launch angle, or the angle at which the ball leaves the bat, can significantly impact their home run production. Players who consistently hit the ball at launch angles that optimize power are more likely to hit home runs.
Historical Performance: Review a player’s past seasons to see if they have a history of hitting for power. Look at their home run totals over the last few seasons and their career as a whole. Consistency in power production is often a good sign.
Plate Discipline: A player’s plate discipline can also affect their home run production. A batter who has a good eye and swings at pitches within the strike zone is more likely to make solid contact. Metrics like O-Swing% (percentage of pitches swung at outside the strike zone) and Z-Swing% (percentage of pitches swung at inside the strike zone) can be informative.
Ballpark Factors: Consider the ballpark in which the player will be playing. Some ballparks are more hitter-friendly and can boost a player’s home run numbers.
Age and Health: Younger players may continue to develop power, while older players may see declines. Additionally, a player’s health and injury history can impact their ability to hit for power.
Team and Lineup Context: The quality of a player’s supporting cast and their spot in the lineup can affect their RBI and run-scoring opportunities, which can indirectly impact home run production.
Offseason Changes: Pay attention to any changes in a player’s offseason training regimen, swing adjustments, or approach changes. These factors can influence power production.
Statistical Models: Some fantasy baseball analysts use statistical models and projections to estimate a player’s future performance. These models often incorporate various metrics and historical data to make predictions.
Keep in mind that while these metrics and factors can be helpful, there are no guarantees in fantasy baseball. Players can experience unexpected fluctuations in performance due to various factors, including luck and variance. It’s essential to use these metrics as part of a comprehensive analysis and not rely solely on one statistic to make your predictions.
These are some good suggestions. Let’s see what she says about an Excel formula to generate a useful formula to use with projected plate appearances. Here’s my query:
Those were some good suggestions for my MLB projections. Now I need to formulate an Excel formula to crunch some of those metrics. Can you suggest an excel formula to use the following metrics: barrel rate; launch angle; exit velocity; and plate discipline. Also, please add the metric OPS to the list. I would like to generate a number that is + or – 1.00. In my example, 1.00 is the average number of homeruns for MLB players who had at least 400 Plate Appearances.
To create an Excel formula that calculates a projected home run number based on the metrics you mentioned (barrel rate, launch angle, exit velocity, plate discipline, and OPS), you can use a weighted average approach. You’ll assign weights to each metric based on their importance and then sum up the weighted values to generate a projection. Here’s a formula that you can use as a starting point:
Excel=(((BarrelRate * WeightBarrelRate) + (LaunchAngle * WeightLaunchAngle) + (ExitVelocity * WeightExitVelocity) + (PlateDiscipline * WeightPlateDiscipline) + (OPS * WeightOPS)) – AverageHR) / StandardDeviationHR
In this formula:
BarrelRate, LaunchAngle, ExitVelocity, PlateDiscipline, and OPS should be replaced with the actual values for each player.
WeightBarrelRate, WeightLaunchAngle, WeightExitVelocity, WeightPlateDiscipline, and WeightOPS are weights you can assign to each metric. These weights should add up to 1. You can adjust them to emphasize the importance of each metric in your projections.
AverageHR should be replaced with the average number of home runs for MLB players who had at least 400 Plate Appearances.
StandardDeviationHR can be the standard deviation of home runs for the same group of players. This helps you scale the result to a range of approximately +1.00 to -1.00.
Here’s a step-by-step guide on how to use this formula:Calculate the average and standard deviation of home runs for MLB players with at least 400 Plate Appearances.
This is great. Based on your knowledge of these various metrics and their historical predict value, what weights would you assign to each metric?
Assign appropriate weights to each metric based on their importance.
Replace the placeholders in the formula with the actual values for each player and the calculated average and standard deviation.
The result will give you a projected home run value for each player, which you can use for your fantasy baseball projections.
Please note that this formula is a basic starting point and may need further refinement based on your specific analysis and data. Additionally, consider normalizing the metric values if they are on different scales to ensure that no single metric dominates the projection.
Assigning weights to each metric depends on your analysis and how much you believe each metric contributes to a player’s home run production. It’s essential to consider historical predictiveness, but also keep in mind that the effectiveness of these metrics can vary from season to season and from player to player. Here’s a general guideline for assigning weights based on their historical predictiveness:
Barrel Rate: Barrel rate is a strong indicator of a player’s ability to make solid contact, and it tends to correlate well with power production. Assigning a relatively high weight to barrel rate, such as 0.3 or 0.4, can be a good starting point.
Launch Angle: Launch angle is crucial for determining the trajectory of the ball. Assign a moderate weight, such as 0.2 or 0.3, as it can significantly impact home run production.
Exit Velocity: Exit velocity measures the speed of the ball off the bat and is an important component of power. Assign a weight similar to launch angle, such as 0.2 or 0.3.
Plate Discipline: Plate discipline metrics like O-Swing% and Z-Swing% indirectly impact power production by influencing a player’s ability to make solid contact. Assign a lower weight, perhaps 0.1 or 0.2, as plate discipline alone may not be as predictive of home runs.
OPS: OPS (On-base Plus Slugging) is a well-rounded metric that includes both on-base percentage and slugging percentage. It captures a player’s ability to get on base and hit for power. Assign a moderate weight, such as 0.2 or 0.3, to OPS.
Remember that these weights are just a starting point, and you may need to adjust them based on your analysis, data, and the specific context of the season. It’s also a good idea to track the actual performance of the players you project to see how well your weights and formula are working, and then make adjustments accordingly. Over time, you can refine your weights to improve the accuracy of your projections.
Author: ChatGPT Title: “Predicting MLB Fantasy Baseball Home Run Totals: Key Metrics and Factors”
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