2025 State of IDP Report - Part 2
Leveraging data from 12,000 leagues to answer many lingering questions about scoring in IDP leagues.
As I mentioned in Part 1, one of the chief complaints lodged by IDP skeptics is the proliferation of scoring systems. This has become such a common refrain by those inside and outside of the IDP community that I have decided to do a deep dive into the data on IDP and non-IDP leagues to answer three questions in this part two of the report:
How messy is the IDP scoring landscape?
Is IDP scoring more complex than offensive scoring?
Are IDP leagues ahead of the curve in adopting offensive scoring innovations?
For these analyses, I enlisted my IDP After Show partner, Jake Kohlhagen, to obtain all scoring settings from 12,000 leagues on Sleeper (6,000 with IDP and 6,000 without). Answering some questions required removing outliers, but these removals are disclosed in the relevant analyses.
Given that this is a hefty article, I wanted to share some primary takeaways and potential action items from the start:
We should not obsess over scoring systems. Yes, they are messy in IDP, but so is offensive scoring.
IDP leagues tend to score more categories on offense, inadvertently diluting the value of IDP.
Good scoring systems add to the ‘IDP box score’ categories and/or choose higher values for IDP stats given the proliferation of offensive scoring in IDP leagues.
How much variance exists in IDP scoring?
To answer this question, I first removed extreme outliers from the overall scoring system. Specifically, I cut out the bottom 301 leagues in total IDP scoring across all categories (i.e., those leagues where tackles were worth 0.1 each and interceptions were worth 1 point) and the top 307 leagues in total scoring possibility (such as leagues that score sacks as 100 points). To establish an appropriate frame of reference, I repeated this analysis for the offense-only leagues as well, trimming leagues in the top or bottom 5th percentile for overall scoring.
The tables below list the following information for a given IDP stat:
Percentage of IDP leagues that use the scoring category
Big 3 recommended scoring for the category
IDP123 recommended scoring for the category
Mean scoring for the category
Central mean for the category (excluding the top and bottom 2.5% of values)
Standard deviation of the category (the spread of the numbers around the raw mean)
IQV of the category (the range between how the league in the 25th percentile scores the category and how the league in the 75th percentile scores the category)
While there are many interesting takeaways from the data, the most common scoring categories and their points stand out. In terms of scoring categories, IDP fantasy is clearly defined by the 12 categories typically found in an NFL box score. These ‘IDP box score’ categories have 95% usage or greater and a huge break to the next two, with usage rates just above 40%. All twelve of the most common scoring categories have presets in the prominent “Big 3” and “IDP123” scoring schemes, while the next two most popular only appear in Big 3. Nearly one-third of leagues also score some kind of IDP bonus.
What is scored in IDP leagues (at a minimum) is relatively straightforward: solo tackles, assists, tackles for loss, sacks, QB hits, fumbles (forced and recovered), interceptions, passes defended, blocked kicks, safeties, and touchdowns.
Variation within the categories can be explored in multiple ways, but each relevant metric paints a similar story. When exploring the difference between leagues in the 25th and 75th percentiles (i.e., the middle 50% of IDP leagues), we see very little variation across many core categories, with few exceptions. Seven of the twelve categories have no variation within this middle group (TFL = 2, QB hit = 1, FF = 3, FR = 3, BK = 3, Saf = 3, TD = 6). Two categories are tightly grouped, with solo tackles scored between 1.5 and 2 and assists ranging from .75 to 1 point each. The largest disparities are for passes defended (2.3 to 3), interceptions (5 to 6), and sacks (4 to 6). While these variations can be the difference in a tight week, there is not as big a chasm in scoring as has been feared.
Turning to standard deviations, these should be interpreted with caution, as the data are not normally distributed, as evidenced by the central means being almost universally lower than the raw averages, suggesting a skew towards higher values. Still, it is noteworthy that all twelve categories scored in IDP123 fall within one standard deviation of the mean, while nine of the fifteen categories scored in Big 3 are within these ranges.
Finally, by exploring the means, we can learn even more about variability in scoring. Despite notable differences, the correlation between the Big 3 scoring settings and IDP123 is 0.85. Both systems correlate more strongly with the mean and the central mean, with Big 3 at 0.95 and IDP123 at 0.98, suggesting that the values may differ, but the patterns are incredibly similar. It is also noteworthy that both prominent scoring schemes overshoot the mean in totality, as a player who tallied a single stat in each of the twelve core categories would score 45 points in Big 3 (plus any sack, interception return, or fumble return yardage), 39 points in IDP123, and 37.39 using the central mean.
Despite exploitable differences, there is a great deal of consistency in the values and patterns in which common IDP plays are scored, suggesting an over-fixation on scoring systems.
How does this compare to scoring in offense-only leagues?
To help better put these numbers into context, I report the same data for offensive scoring categories in the 5,392 non-extreme offense-only leagues.
The first thing that stands out is the sheer number of potential scoring categories on offense. At 51 categories, this is more than double the potential IDP scoring categories! Similar to IDP, there are 11 offensive scoring categories that are commonplace, with usage rates of 96% or higher and tight end reception bonuses nearing 75%. Sixteen scoring categories are used between 20-30% of leagues, with another seven in the 10-20% range.
While there are also 12 core scoring categories on offense, there are an additional 16 categories that are used in at least one-fifth of leagues.
Turning to the variance that exists within these categories, the IQVs show remarkable consistency of the core stats with two exceptions, interceptions (-2 to -1) and passing TDs (4 to 6), mirroring the differences observed for interceptions and sacks for IDP. The smaller standard deviations suggest smaller differences in offense from league to league, but this should be put into context: five of the core offensive categories have means of 1 or less, whereas only one of the core IDP scoring categories has a mean of less than 1. Where things get messy is in the less commonly scored categories, as both IQVs and standard deviations grow considerably in these stats.
Offensive scoring is more standardized, but the variations that do exist suggest that, as systems have become more complex, there has been an under-fixation on offensive scoring.
Are IDP leagues innovative (or unnecessarily complex) on offense?
One takeaway from the preceding sections is that systems such as IDP123 (and particularly Big 3) tend to overemphasize IDP scoring beyond the settings used in most leagues. Another is that offensive scoring options have proliferated significantly since both IDP scoring systems were designed. From the perspective of the ratio of offensive player scoring to IDP scoring, the logical conclusion is that IDP123 is likely functioning as designed in leagues with ‘standard’ offensive scoring, whereas Big 3 scoring is better suited for leagues which have adopted innovations in offensive scoring. The previous table suggests that offense-only leagues skew towards vanilla scoring systems, with things like rushing first downs (26.2%), receiving first downs (24.6%), rush attempts (16.2%), big-play bonuses (21.1%-25.8%), and big-game bonuses (12.6%-22.8%) all relatively rare. However, two things are missing from this analysis: the number of scoring categories used by the average league, and the usage rates in leagues that use offensive players and IDP.
As seen from the table above, IDP leagues use (on average) 20.8 of the 51 available offensive scoring categories, whereas offense-only leagues average 17.6. While these may be driven by extreme outliers, they are not in these cases. Only 31% of IDP leagues use 12 or fewer offensive scoring categories, with 46% using 20 or more. Furthermore, the average IDP league scores 15 categories, with subsequent analyses revealing that only 36% of IDP leagues use 12 or fewer categories, while 60% use 15 or more.
Finally, we turn to usage rates of offensive scoring categories in IDP leagues. As seen in the table above, IDP leagues lag behind in many of the big 12 offensive scoring categories, due to the 24 IDP-only leagues in the sample. In every other one of the 39 offensive scoring categories, usage rates are higher in IDP leagues than in offense-only leagues (often by double-digit margins).
IDP leagues tend to score more offensive categories than offense-only leagues and frequently add more IDP scoring categories to create balance.
I hope you have enjoyed this deep dive into the state of IDP scoring. If you are curious about anything I discuss above or any data I have but did not report out here, just let me know, and I am happy to keep the conversation going!
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