07-03-2024, 03:17 PM
(This post was last modified: 07-05-2024, 11:36 AM by wetwilleh. Edited 1 time in total.)
I wanted to take a look at the impact of the opposition on fantasy points earned. We might imagine scenarios where a team is more likely than average to give up a higher number of fantasy points to a certain position or have a strong ability to limit fantasy earnings.
Using the Fantasy results sheet I added a lookup for the team faced in each week. This will have the same limitation I’ve faced in the past where a double game week (weeks 3 and 4 this season) will not have game level data. So the values I report are weekly averages for the remaining weeks.
I also wanted to be able to limit the results to only include players reaching a certain rostered percentage threshold. It’s possible a teams results can be affected by facing a particularly weak position group multiple times so we want to have a way to control for that. It’s worth nothing this won’t control for the opposite problem, where a team faces a high scoring unit more often than average. Future analysis might want to create an indexed % performance above expectation for the position group, though data is limited for such an exercise.
Without further ado, let’s take a look at the overall results:
Heat mapping is by column. The reported metric is the weekly average of points awarded to that position type over the weeks that meet the rostering threshold reported at the top.
Just to get a flavor of the sort of data this provides and how we might use it, let’s explore at the fantasy points allowed to Defensive Backs over the season. The Yeti and Silverbacks led the league in interceptions thrown with 28 and 23 respectively a great source of points for the secondary. But we see another team the Fire Salamanders giving up the highest average with 12.8 points allowed per week to DB’s on at least 1 fantasy roster. Berlin home to many fantasy darlings this year did air it out at a high rate, achieving the most completions and thus tackle opportunities for corners which can partially explain the result. But there’s also the possibility for a few abnormal results or the quality of the competition faced is the primary driver.
Berlin faced the highest scoring DB, Kadarius Claypool II twice this season and they got lit up both times. Giving up 24 points on 2 picks and a forced fumble in week 7 and a pick six (along with a healthy smattering of tackles) in week 15. So you can see the partly cyclical nature of this sort of analysis, but I think we’ve already had some decent visibility into some real trends.
Some other quick trends highlighted by the results:
• Butchers gave up the most average points to Offensive Lineman owing in part to a low sack total (2nd worst in the league at 32 over the season – though a name change and a fearsome rookie nose tackle threaten to change that)
• Poor defenses the Hahalua and Yeti gave up the most points to kickers. While two strong defenses the Hawks and Crash gave up the least points to kickers. An interesting case is the Second Line with a strong defense who gave up a relatively high amount of points to kickers. Perhaps the game plan of the team led to more shorter field goals than average, or more opportunities for punts inside the 20 – an interesting but not so profitable possible avenue for future analysis.
• The Fire Salamanders gave up the most points to Linebackers they faced. They were tied for the league lead in sacks allowed. Curiously the Yeti who also led the league in sacks allowed and have a similar run/pass play preference to the Fire Salamanders gave up a good deal fewer points to LB. We’d have to look at more granular play and formation data to determine if there is a systematic cause for this (possibly more tackles for loss) or more likely it again can be chalked up to the quality of opposition.
These sort of trends may be useful as a tiebreaker in your fantasy draft. After the schedule is announced if you are close between two players maybe consider if they’ll be playing one of these particularly weak or strong teams and how that might affect the position group you’re drafting.
Now lets take a look at the offensive skill positions and see if there’s any actionable trends there. First we get a chance to again point out the poorly performing defenses of the Yeti and Hahalua giving up a great deal of points across the position groups. One team that had a middling year that have so far escaped mention are the Orange County Otters, who also had a particularly generous defense allowing a high average fantasy point total across all skill groups.
On the flip side there were some teams that were particularly stingy. The Hawks, Secondline, Sabercats and Crash all had lower quartile average points allowed across all position groups. Not only were these groups talented on the defensive side of the ball, but they were effective at keeping possession and running clock limiting offensive attempts from their foe. One team that might be surprising that followed this same general game plan is the Austin Copperheads, who had a middle of the pack scoring defense, but had one of the best defenses limiting yards particularly from opponents passing attacks.
The Outlaws were an interesting team this year, with an average defense overall, but one that was able to stop the run particularly well. They didn’t have the face the fearsome running attack of the Crash, and their strong offense forced opponents to play from behind making running less attractive. And I don’t want to minimize the talent on that side of the ball the Outlaws do have an impressive front 7, but their league leading performance with regard to fantasy points allowed to running backs is the result of a combination of these factors.
For these higher scoring position groups you might consider utilizing your waiver wire pickups to target certain matchups. I did that without success this fantasy season, hoping matchups against the Fire Salamanders and Yeti in the final two weeks would improve the performance of Maximus Boudreaux. It didn’t, but if you find yourself deciding between two marginal QB’s this draft season maybe you can find a pair with a favorable split of opponents causing one to have higher expected earnings in the first N games, and the other player for the remainder.
I thought this would be an interesting exploration of possible applications to fantasy, but there are some serious limitations. I do think some sort of indexed performance above expectation is needed to truly affect draft rankings or waiver strategy over the course of a season. But hopefully you found something of interest in this analysis or at least a way to make fun of your rival team with numbers!
Using the Fantasy results sheet I added a lookup for the team faced in each week. This will have the same limitation I’ve faced in the past where a double game week (weeks 3 and 4 this season) will not have game level data. So the values I report are weekly averages for the remaining weeks.
I also wanted to be able to limit the results to only include players reaching a certain rostered percentage threshold. It’s possible a teams results can be affected by facing a particularly weak position group multiple times so we want to have a way to control for that. It’s worth nothing this won’t control for the opposite problem, where a team faces a high scoring unit more often than average. Future analysis might want to create an indexed % performance above expectation for the position group, though data is limited for such an exercise.
Without further ado, let’s take a look at the overall results:
Heat mapping is by column. The reported metric is the weekly average of points awarded to that position type over the weeks that meet the rostering threshold reported at the top.
Just to get a flavor of the sort of data this provides and how we might use it, let’s explore at the fantasy points allowed to Defensive Backs over the season. The Yeti and Silverbacks led the league in interceptions thrown with 28 and 23 respectively a great source of points for the secondary. But we see another team the Fire Salamanders giving up the highest average with 12.8 points allowed per week to DB’s on at least 1 fantasy roster. Berlin home to many fantasy darlings this year did air it out at a high rate, achieving the most completions and thus tackle opportunities for corners which can partially explain the result. But there’s also the possibility for a few abnormal results or the quality of the competition faced is the primary driver.
Berlin faced the highest scoring DB, Kadarius Claypool II twice this season and they got lit up both times. Giving up 24 points on 2 picks and a forced fumble in week 7 and a pick six (along with a healthy smattering of tackles) in week 15. So you can see the partly cyclical nature of this sort of analysis, but I think we’ve already had some decent visibility into some real trends.
Some other quick trends highlighted by the results:
• Butchers gave up the most average points to Offensive Lineman owing in part to a low sack total (2nd worst in the league at 32 over the season – though a name change and a fearsome rookie nose tackle threaten to change that)
• Poor defenses the Hahalua and Yeti gave up the most points to kickers. While two strong defenses the Hawks and Crash gave up the least points to kickers. An interesting case is the Second Line with a strong defense who gave up a relatively high amount of points to kickers. Perhaps the game plan of the team led to more shorter field goals than average, or more opportunities for punts inside the 20 – an interesting but not so profitable possible avenue for future analysis.
• The Fire Salamanders gave up the most points to Linebackers they faced. They were tied for the league lead in sacks allowed. Curiously the Yeti who also led the league in sacks allowed and have a similar run/pass play preference to the Fire Salamanders gave up a good deal fewer points to LB. We’d have to look at more granular play and formation data to determine if there is a systematic cause for this (possibly more tackles for loss) or more likely it again can be chalked up to the quality of opposition.
These sort of trends may be useful as a tiebreaker in your fantasy draft. After the schedule is announced if you are close between two players maybe consider if they’ll be playing one of these particularly weak or strong teams and how that might affect the position group you’re drafting.
Now lets take a look at the offensive skill positions and see if there’s any actionable trends there. First we get a chance to again point out the poorly performing defenses of the Yeti and Hahalua giving up a great deal of points across the position groups. One team that had a middling year that have so far escaped mention are the Orange County Otters, who also had a particularly generous defense allowing a high average fantasy point total across all skill groups.
On the flip side there were some teams that were particularly stingy. The Hawks, Secondline, Sabercats and Crash all had lower quartile average points allowed across all position groups. Not only were these groups talented on the defensive side of the ball, but they were effective at keeping possession and running clock limiting offensive attempts from their foe. One team that might be surprising that followed this same general game plan is the Austin Copperheads, who had a middle of the pack scoring defense, but had one of the best defenses limiting yards particularly from opponents passing attacks.
The Outlaws were an interesting team this year, with an average defense overall, but one that was able to stop the run particularly well. They didn’t have the face the fearsome running attack of the Crash, and their strong offense forced opponents to play from behind making running less attractive. And I don’t want to minimize the talent on that side of the ball the Outlaws do have an impressive front 7, but their league leading performance with regard to fantasy points allowed to running backs is the result of a combination of these factors.
For these higher scoring position groups you might consider utilizing your waiver wire pickups to target certain matchups. I did that without success this fantasy season, hoping matchups against the Fire Salamanders and Yeti in the final two weeks would improve the performance of Maximus Boudreaux. It didn’t, but if you find yourself deciding between two marginal QB’s this draft season maybe you can find a pair with a favorable split of opponents causing one to have higher expected earnings in the first N games, and the other player for the remainder.
I thought this would be an interesting exploration of possible applications to fantasy, but there are some serious limitations. I do think some sort of indexed performance above expectation is needed to truly affect draft rankings or waiver strategy over the course of a season. But hopefully you found something of interest in this analysis or at least a way to make fun of your rival team with numbers!