Why “Mid-Mean” Outshines “Averages” for Football Stats: Calculate It in FileMaker

The Myth of Average, and an Alternative

Serious football fans swim in a sea of stats, many based on averages. Common examples include:

• Average points per game
• Average passing yards per game
• Average yards allowed per game

This type of stat dominates NFL apps and fantasy dashboards, but averages can mislead. Unusual plays and extreme games skew results, clouding typical performance. The mid-mean can provide a smarter, more reliable alternative.

What Is Mid-Mean, and Why Does It Matter?

The mid-mean averages the middle 50% of a dataset, discarding the top and bottom 25% of values. By ignoring outliers, it reveals a team’s or player’s consistent performance. In football, where blowouts or flukes distort averages, the mid-mean provides a clearer, more predictive metric.

Example 1: Miami Dolphins’ Scoring in 2023

In 2023, the Miami Dolphins scored 70 points against the Denver Broncos in Week Three. This elevated the tally of their first three games to 130, an average of 43.3 points per game. That 70-point outlier not only inflated their scoring average, it bloated the expectations of many Dolphin admirers.

But if we take a larger dataset, say the Dolphins first 12 games [36, 24, 70, 20, 31, 42, 17, 31, 14, 20, 34, 45]:

• Sort
• Discard top 25% (70, 45, 42) and bottom 25% (14, 17, 20)
• Calculate average only using the middle 50% (21, 24, 31, 31, 34, 36)

We see a more valid expectation for the Dolphins 2023 offense: 29.5 points per game. They certainly were one of the best offenses in the league; they were not historic. Mid-mean better reflects typical scoring, ideal for predictions.

Example 2: Chargers Run Game in 2024

A running back can post a lot of stuffed and meager runs, but if he hits on a couple big ones, perhaps late in the game when defenses are fatigued or overly-focused on pass protection, it can dramatically skew the average.

A great example of this in 2024 was the Charger's JK Dobbins. Behind a poor interior o-line, half his carries netted two yards or less. That doesn’t consistently move the chains! But Dobbins did redeem himself with lots (27) of chunk runs (10+ yards), and this explains why his seasonal yards-per-attempt settled at a glossy 4.6 pace. 

To be clear: the 2024 L.A. run game was very bi-polar and unreliable.

Calculating Mid-Mean in FileMaker

FileMaker lacks a native mid-mean function (Excel doesn't have it either), but you can compute it by processing records with a script. Steps include:

• Sort records by desired value(ascending).
• Count total records and calculate 25% to discard extreme records from each end.
• Working with the middle 50% of records, sum the value and divide by their count.
• Store the result in a field or variable and display.

Conclusion

The gap between average and mid-mean won't always be dramatic, and simple averages certainly have their place. But mid-mean is more reliable for fantasy football or matchup planning. Just make sure to compare apples to apples. It's no good, for instance, to compare the mid-mean rate of one player versus the simple average of another.

The mid-mean cuts through football’s variability, offering a robust metric for points, yards, or other stats. FileMaker users can utilize it to enhance their sports analytics, or more importantly, use it to uncover insights when measuring business or organizational performance. Try it in your databases and share your insights!

‍