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Another NBA season is beginning and as usual, for the fifth year in a row, I am here at Razzball to talk fantasy with you fine folks. As is the custom, the first article of the year is always a review of last year’s projections. This process started all the way back in 2017, before Covid-19 existed, when England was still a part of the EU, and I weighed 7 kgs less. If you are interested in diving into the math behind the whole review process, read the initial article here and shoot me a question in the comments below for any clarifications. On a side note, my thoughts and affiliations for the past NBA season can be summed up as such:

He deserves it more than anyone and his long journey from the open courts and streets in Greece to the NBA championship has been a joy to behold, not only as a fellow Greek but as an admirer of his dedication, persistence, and commitment.

With this out of the way let’s get to the focus of this article.

Missed Players

Every year in this portion of the article we summarize the players that are categorized as “misses.” These are the players that have a value difference between the projected and the actual value that is above the standard deviation. Again, if you are interested to learn more, check the first article of the review series here. The first line for each player is my projection from last year, while the second is their actual stats for the 2020-21 season, the third is the difference, and finally the fourth is the difference expressed as a percentage of the respective standard deviation.

Name Val Pts 3pt Reb Ast Stl Blk Fg% Ft% To
James Harden 0.89 33.78 4.5 6.6 7.5 1.8 0.7 44 87 4.6
0.60 24.61 2.75 7.93 10.80 1.20 0.75 47 86 4.0
Diff -0.29 -9.16 -1.75 1.33 3.30 -0.60 -1.8 3 -1 -0.6
SD% 0.08 0.62 0.68 -0.46 0.55 0.64 -0.90 -0.58 -0.89 -0.34
         
Anthony Davis 0.86 26.24 1.3 9.6 3.2 1.5 2.2 50 83 2.5
0.28 21.81 0.7 7.9 3.1 1.3 1.6 49 74 2.1
Diff -0.58 -4.43 -0.6 -1.7 -0.1 -0.2 -0.6 -1 -9 -0.4
SD% 1.14 -0.22 -0.45 -0.33 -0.93 -0.39 0.13 -0.85 0.12 -0.49
     
Nikola Jokic 0.53 21.15 1.2 10.1 7.3 1.3 0.7 53 83 3.2
0.86 26.36 1.3 10.8 8.3 1.3 0.7 57 87
3.1
Diff 0.33 5.21 0.1 0.7 1.0 0.0 0.0 4 4 -0.1
SD% 0.22 -0.08 -0.93 -0.70 -0.52 -0.95 -0.96 -0.42 -0.48 -0.87
 
Jusuf Nurkic 0.29 16.75 0.4 10.8 3.6 1.1 1.5 50 79 2.5
-0.08 11.46 0.3 9.0 3.4 1.0 1.1 51 62 2.0
Diff -0.36 -5.29 -0.1 -1.8 -0.2 -0.1 -0.4 1 -17 -0.5
SD% 0.35 -0.07 -0.93 -0.26 -0.90 -0.80 -0.15 -0.78 1.06 -0.39
Kevin Durant 0.25 25.03 2.2 5.8 4.1 0.7 0.8 49 88 3.1
0.59 26.94 2.4 7.1 5.5 0.7 1.3 0.54 88 3.4
Diff 0.34 1.91 0.2 1.3 1.4 0.0 0.5 0.05 0 0.3
SD% 0.24 -0.66 -0.78 -0.49 -0.32 -0.96 -0.02 -0.23 -0.97 -0.62
Andre Drummond 0.22 17.69 0.1 13.5 2.5 1.7 1.6 55 57 3.3
-0.09 14.93 0.0 12.0 2.0 1.4 1.1 49 60 2.7
Diff -0.31 -2.76 -0.1 -1.5 -0.5 -0.3 -0.5 -6 3 -0.6
SD% 0.14 -0.51 -0.90 -0.39 -0.79 -0.09 0.08 -0.06 -0.64 -0.31
Myles Turner 0.12 11.91 1.4 7 1.2 0.8 2.2 47 75 1,4
0.40 12.60 1.5 6.5 1.0 0.9 3.4 48 78 1.4
Diff 0.28 0.69 0.1 -0.5 -0.2 0.1 1.2 1 3 0
SD% 0.04 -0.88 -0.93 -0.81 -0.92 -0.86 1.39 -0.81 -0.62 -0.97
Hassan Whiteside -0.02 10.77 0.1 9.1 0.7 0.4 1.8 59 66 1.1
-0.47 8.14 0.0 6.0 0.6 0.3 1.3 56 52 1.1
Diff -0.45 -2.63 -0.1 -3.1 -0.1 -0.2 -0.5 -3 -14 0
SD% 0.65 -0.54 -0.90 0.26 -0.93 -0.59 0.05 -0.55 0.71 -0.99
Eric Bledsoe -0.08 15.87 1.4 5 4.6 1.1 0.4 47 79 2.3
-0.38 12.24 1.7 3.4 3.8 0.8 0.3 42 69 1.6
Diff -0.30 -3.63 0.3 -1.6 -0.8 -0.3 -0.1 -5 -10 -0.7
SD% 0.10 -0.36 -0.71 -0.37 -0.61 -0.10 -0.87 -0.19 0.24 -0.17
   
Chris Boucher -0.11 9.41 0.9 6.7 1 0.6 1.4 46 80
0.8
0.19 13.63 1.5 6.7 1.1 0.6 1.9 51 79
0.8
Diff 0.29 4.23 0.6 0.0 0.1 0.0 0.5 5 -1 0
SD% 0.08 -0.25 -0.43 -0.99 -0.97 -0.95 -0.09 -0.12 -0.85 -0.96
   
Dwight Powell -0.11 10.44 0.4 6 1.6 1 0.7 62 70
1
-0.40 5.90 0.1 4.1 1.1 0.6 0.5 62 78
0.7
Diff -0.29 -4.54 -0.3 -1.9 -0.5 -0.4 -0.2 0 8 -0.3
SD% 0.08 -0.20 -0.70 -0.22 -0.76 0.09 -0.63 -0.97 -0.01 -0.64
   
Danuel House -0.16 10.45 2 4.4 1.4 1.1 0.5 42 81 0.8
-0.47 8.75 1.5 3.7 1.9 0.6 0.4 40 65 1
Diff -0.31 -1.70 -0.5 -0.7 0.5 -0.5 -0.1 2 -16 0.2
SD% 0.15 -0.70 -0.52 -0.70 -0.76 0.42 -0.89 -0.67 0.93 -0.77
   
Elfrid Payton -0.17 11.21 0.3 5 7.7 1.5 0.5 44 65 2.5
-0.56 10.14 0.4 3.4 3.2 0.7 0.1 43 68 1.6
Diff -0.39 -1.07 0.1 -1.6 -4.5 -0.8 -0.4 1 3 -0.9
SD% 0.45 -0.81 -0.86 -0.36 1.10 1.08 -0.28 -0.89 -0.61 -0.01
   
Mike Conley -0.17 15.92 2.3 3 5 1 0.2 43 83 2.2
0.12 16.22 2.7 3.5 6.0 1.4 0.2 44 85 1.9
Diff 0.29 0.30 0.4 0.5 1.0 0.4 0.0 1 2
-0.3
SD% 0.07 -0.95 -0.61 -0.82 -0.54 0.03 -0.95 -0.70 -0.73 -0.70
   
Terry Rozier -0.21 14.97 2.3 4.2 3.3 0.9 0.2 42 85 1.9
0.17 20.39 3.2 4.4 4.2 1.2 0.4 45 82 1.9
Diff 0.38 5.43 0.9 0.2 0.9 0.3 0.2 3 -3 0
SD% 0.42 -0.04 -0.12 -0.92 -0.56 -0.04 -0.64 -0.59 -0.60 -0.97
   
Nemanja Bjelica -0.26 9.02 1.4 5.4 1.5 0.7 0.5 48 80 1
-0.58 6.54 0.7 3.4 1.9 0.4 0.1 45 73 0.9
Diff -0.32 -2.48 -0.7 -2.0 0.4 -0.3 -0.4 -3 -7 -0.1
SD% 0.20 -0.56 -0.36 -0.20 -0.83 -0.19 -0.26 -0.58 -0.10 -0.88
   
Kyle Anderson -0.26 7.18 0.6 5.2 2.9 0.9 0.8 49 69 1.3
0.08 12.38 1.4 5.7 3.6 1.2 0.8 47 78 1.2
Diff 0.34 5.20 0.8 0.5 0.7 0.3 0.0 -2 9 -0.1
SD% 0.26 -0.08 -0.27 -0.78 -0.66 -0.12 -0.95 -0.65 0.12 -0.94
   
Julius Randle -0.27 18.16 0.9 9 2.7 0.8 0.4 47 73 2.9
0.18 24.11 2.3 10.2 6.0 0.9 0.3 46 81 3.4
Diff 0.45 5.95 1.4 1.2 3.3 0.1 -0.1 -1 8 0.5
SD% 0.68 0.05 0.30 -0.52 0.56 -0.72 -0.70 -0.84 -0.02 -0.45
   
Aron Baynes -0.28 12.78 1.6 6.1 1.8 0.2 0.7 47 80 1.4
-0.56 6.11 0.5 5.2 0.9 0.3 0.4 44 71 0.9
Diff -0.28 -6.67 -1.1 -0.9 -0.9 0.1 -0.3 -3 -9 -0.5
SD% 0.04 0.18 0.04 -0.62 -0.57 -0.72 -0.46 -0.47 0.12 -0.39
   
Harrison Barnes -0.29 14.87 1.6 4.8 2 0.6 0.2 45 81 1.3
0.00 16.09 1.7 6.6 3.5 0.7 0.2 50 83 1.6
Diff 0.29 1.22 0.1 1.8 1.5 0.1 0.0 5 2 0.3
SD% 0.08 -0.78 -0.88 -0.26 -0.31 -0.61 -0.98 -0.24 -0.76 -0.65
 
JJ Redick -0.30 14.05 2.8 2 1.9 0.3 0.2 45 90 1.2
-0.64 7.43 1.5 1.5 1.2 0.3 0.1 40 94 0.8
Diff -0.33 -6.62 -1.3 -0.5 -0.7 -0.1 -0.1 -5 4 -0.4
SD% 0.24 0.17 0.25 -0.78 -0.65 -0.86 -0.73 -0.14 -0.49 -0.56

The percentages highlighted in red represent the stats that I missed on and were greater than the standard deviation. The closer the percentage is to 100, the greatest my miss, whereas negative percentages indicate that I succeeded in the prediction. If you see a -100%, you are legally obliged to buy me an authentic Brian Scalabrine shirt with his holy sweat still on it and send it to my last known address, as this indicates a bullseye prediction with no error. Obviously, I only included in the above array the “missed” players, but I can assure you I did the exact same procedure for the remaining 134 players that were classified as “hits”. Some players that stand out from the misses are:

Anthony Davis: After a legitimate fantasy MVP season, Davis burned many owners in redraft last year with a sharp decline in ft% and blocks while only playing 36 games. He is bound for a bounce-back season.

Nikola Jokic: His MVP season meant fantasy goodness for the people who drafted him at a discount last year. It will not be possible this season as it wil take a top 3 pick to get him.

Kevin Durant: He is back to his usual scary self and is a fantasy monster when healthy.

Hassan Whiteside: After finishing the year ranked 9th in per-game value for Portland, I was expecting a decline in value and ranked him 73rd but even that proved far too optimistic as his short stint with Sacramento was a disaster.

Terry Rozier: Scary Terry had an awesome season with Charlotte and was rewarded with a generous max extension for his efforts. His improvement in the fg% department was key to his increased value. Let’s see if he can continue his upward trend this year.

Julius Randle: Didn’t see his explosion in NY coming but after all, he was the Most Improved Player last season so I get a pass here? Maybe? Pretty please?

Conclusions

The whole process concludes with the calculation of the absolute mean difference in value between my projection and the actual stats of the 2020-21 season. As a reminder, the smaller this number, the more accurate the projections. This number by itself does not mean much, but it can be used as a comparison with the accuracy of my projections from the previous years. For reference, this number was 0.156 in 2017, 0.16 in 2018, and 0.162 in 2019. Now please ignore the alarming trend that my predictions are getting a bit worse every season and let’s focus on this year’s number which is….

0.149!

I must admit I am such a fantasy nerd that I got genuinely happy when my Excel sheet spit out that number as the final answer, which is better than all the previous seasons. Let’s hope that the projections for the 2021-22 season, which should be coming in the following weeks, are as accurate as the last ones and, more importantly, that they help you meaningfully in your drafting.

Thank you for the patience in reading the whole article as it is more math-heavy than a usual fantasy article and let me know if you have any questions regarding the process used or any other offseason fantasy questions in the comments below!