NBA Trend Testing: PER and Opponent Plus/Minus

With our Trends tool, you can see current and historical matches for players in matchups that meet the specified criteria. This makes it pretty easy to track performance within the result set. In this series, I thought it might be cool to take it one step further. I will be creating a Trend early in the week, playing the “Current Matches” in my lineups throughout the week on FanDuel and then reviewing the Trend at the end of the week.

This Monday, I created the following Trend:

Description

During the past couple of weeks in the “Trend Testing” Series, I’ve used Trends to determine whether some combination of stats would be useful. I love using custom Trends as tools to test assumptions people have made or even to try out my own theories about fantasy basketball. Sometimes though, it’s nice to just make a solid, dependable Trend that you can go to for plays while building your team. That’s the type of Trend I’m going to attempt to create this week.

Today, we’re going combine PER and Opp Pos +/- to find efficient players in good spots. I’ve been wanting to create a Trend with the new Opp Pos +/- stat and this seems like a good chance to do so. Targeting high PER players against teams that have struggled guarding the position makes sense logically, and the Trend comes with a relatively high Plus/Minus and Consistency Rating:

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The filters I used were:

• The player’s PER is between 20-52 *Note: League average is around 15
• Opp Pos +/- is between 4.5 and 17

Results

3/14

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On 3/14, we actually had two matches, Lillard and Jonas Valanciunas. JV actually got injured during the first quarter of his game, so I don’t think it’s fair to include that score here.

Lillard commanded a high 23.55 PER coming into the game and stood to benefit from a +4.88 Plus/Minus given up by OKC to PGs. Those numbers look fine, but one thing this Trend did not account for was blowout factor. Lillard’s failure to return value was more due to the scoreboard than to his matchup against Westbrook.

3/15

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On Tuesday, I rostered two of the most expensive centers who both returned as matches. Honestly, this is another example where it wouldn’t have been a bad idea to add a Vegas filter to the Trend as the opposition consisted of the Lakers and 76ers. Luckily, neither game was a huge blowout – heading into halftime, the Nets looked like they were going to put the game away quickly, but a second half run by Philly earned a few more minutes for Brooklyn’s starters.

The results don’t stand out as exceptional, but each player finished around +2 compared to their implied point totals. Unfortunately, two days into the week, we still have not sniffed the overall +3.89 Plus/Minus.

3/16

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That brings us to Wednesday, where we had three matches – Cousins, IT, and Jordan. Again, we have three games decided by 15 points or more, but this time, we were able to salvage the results, for the most part.

OKC’s path of destruction continued through Boston, which left Thomas about a point and a half below expectations, but that was more than made up for by DeAndre’s +14.5 score coming at only 2% ownership. The quarter of the field that rostered Boogie at center was happy that he was able to salvage a usable score in the midst of Sacramento’s continued breakdown.

Conclusion

Whether or not there are more blowouts later in the season than there are earlier in the year is something that would need to be studied – but it sure feels like there are after the past seven to 10 days of basketball. Anytime you roster a high-priced player, like those listed in the results this week, who is facing a weak opponent, the risk is obvious. If the game does become a blowout, your player will probably be one of the first ones to the bench.

If you were to use this Trend moving forward as we get into the end of March and April, I would recommend considering a game’s spread, if not explicitly adding a spread filter to your Trend. With all of that being said, I do think this Trend sets up well for cash games. Although its performance this week wasn’t the greatest, over the long haul, I think the results will be relatively consistent based on the overall rating.

If you’d like to take this Trend for a test drive tonight on FanDuel, here are the Current Matches:

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With our Trends tool, you can see current and historical matches for players in matchups that meet the specified criteria. This makes it pretty easy to track performance within the result set. In this series, I thought it might be cool to take it one step further. I will be creating a Trend early in the week, playing the “Current Matches” in my lineups throughout the week on FanDuel and then reviewing the Trend at the end of the week.

This Monday, I created the following Trend:

Description

During the past couple of weeks in the “Trend Testing” Series, I’ve used Trends to determine whether some combination of stats would be useful. I love using custom Trends as tools to test assumptions people have made or even to try out my own theories about fantasy basketball. Sometimes though, it’s nice to just make a solid, dependable Trend that you can go to for plays while building your team. That’s the type of Trend I’m going to attempt to create this week.

Today, we’re going combine PER and Opp Pos +/- to find efficient players in good spots. I’ve been wanting to create a Trend with the new Opp Pos +/- stat and this seems like a good chance to do so. Targeting high PER players against teams that have struggled guarding the position makes sense logically, and the Trend comes with a relatively high Plus/Minus and Consistency Rating:

tt1

 

The filters I used were:

• The player’s PER is between 20-52 *Note: League average is around 15
• Opp Pos +/- is between 4.5 and 17

Results

3/14

tt2

 

On 3/14, we actually had two matches, Lillard and Jonas Valanciunas. JV actually got injured during the first quarter of his game, so I don’t think it’s fair to include that score here.

Lillard commanded a high 23.55 PER coming into the game and stood to benefit from a +4.88 Plus/Minus given up by OKC to PGs. Those numbers look fine, but one thing this Trend did not account for was blowout factor. Lillard’s failure to return value was more due to the scoreboard than to his matchup against Westbrook.

3/15

tt3

 

On Tuesday, I rostered two of the most expensive centers who both returned as matches. Honestly, this is another example where it wouldn’t have been a bad idea to add a Vegas filter to the Trend as the opposition consisted of the Lakers and 76ers. Luckily, neither game was a huge blowout – heading into halftime, the Nets looked like they were going to put the game away quickly, but a second half run by Philly earned a few more minutes for Brooklyn’s starters.

The results don’t stand out as exceptional, but each player finished around +2 compared to their implied point totals. Unfortunately, two days into the week, we still have not sniffed the overall +3.89 Plus/Minus.

3/16

tt4

 

That brings us to Wednesday, where we had three matches – Cousins, IT, and Jordan. Again, we have three games decided by 15 points or more, but this time, we were able to salvage the results, for the most part.

OKC’s path of destruction continued through Boston, which left Thomas about a point and a half below expectations, but that was more than made up for by DeAndre’s +14.5 score coming at only 2% ownership. The quarter of the field that rostered Boogie at center was happy that he was able to salvage a usable score in the midst of Sacramento’s continued breakdown.

Conclusion

Whether or not there are more blowouts later in the season than there are earlier in the year is something that would need to be studied – but it sure feels like there are after the past seven to 10 days of basketball. Anytime you roster a high-priced player, like those listed in the results this week, who is facing a weak opponent, the risk is obvious. If the game does become a blowout, your player will probably be one of the first ones to the bench.

If you were to use this Trend moving forward as we get into the end of March and April, I would recommend considering a game’s spread, if not explicitly adding a spread filter to your Trend. With all of that being said, I do think this Trend sets up well for cash games. Although its performance this week wasn’t the greatest, over the long haul, I think the results will be relatively consistent based on the overall rating.

If you’d like to take this Trend for a test drive tonight on FanDuel, here are the Current Matches:

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