A strategy often used in category head-to-head fantasy basketball leagues, a punting strategy is when a manager intentionally disregards one or more categories in favor of building up their strengths in another. If you’re playing in a category league, there is a danger in thinking you can compete and win in every category. The solution to that? Focus your attention on a majority of categories that you know could win you a matchup on a weekly basis. Sure, it won’t always be perfect but here’s some tips and tricks to keep in mind as you approach your draft and the start of the season.

The best part about planning for a punt strategy in today’s fantasy basketball world is the variety of fantasy basketball tools you have at your disposal. One of these tools we like to utilize is called a fantasy Z score. People who crunch Z scores are way smarter than us, so we’ll let their tools do the explaining in this article. Essentially, a Z score helps you determine a players value taking into consideration performance in one or a variety of categories. For this article, we are utilizing z scores provided by fantaZscores.com. Check them out if you want to master your punt!

Rules of a Good Punt

  • Never plan for a punt, but also be ready to embrace one. 
  • Usually, drafting best player available is the best strategy for any build. Don’t reach for players to fit your build since there’s still a lot of unanswered questions after draft day.
  • The less categories your league has, the harder it will be to punt multiple categories. 
  • Keep in mind injuries, trades, and working the waiver wire will always be ways of improving your punt post-draft.

Different types of punting strategies

Punting points 

Punting points is probably one of the more difficult strategies to nail down, since everyone seems to score at a higher pace in today’s game than ever before. The freedom here is you are able to focus on every category besides points early in the draft. This might look like passing on someone that scores 25ppg+ for someone that scores around 20ppg but grabs you more rebounds or dishes out more assists on a regular basis. Not a big difference in points, but the net difference you gain in other categories will be worth it. There’s a lot of “shiny prizes” in the early rounds, take this time to focus on players you think would be more consistent producers across categories regardless of scoring. 

Top Players Based on Z Scores for Punting Points:

Rk

Punt Rk

Name

Pos

Team

TotalZ

PtsZ

AstsZ

RebsZ

ThreesZ

StlsZ

BlksZ

FgsZ

FtsZ

TovsZ

Pts

Asts

Rebs

3s

Stls

Blks

Fgs

Fgas

Fts

Ftas

Tovs

34Joel EmbiidCPHI0.502.440.252.28-0.260.321.570.650.57-1.3930.574.1811.711.371.131.469.7919.629.6211.813.15
2310Myles TurnerCIND0.40-0.52-1.120.46-0.18-0.884.310.43-0.400.5812.861.057.071.450.672.814.769.361.882.501.29
1616Fred VanVleetPGTOR0.350.721.35-0.572.101.81-0.28-1.640.85-0.8320.316.684.453.721.710.546.8016.882.983.422.62
2924Nikola VucevicCCHI0.230.28-0.162.01-0.21-0.120.59-0.03-0.22-0.0317.643.2311.011.420.960.977.4815.811.261.661.86
5433Mo BambaCORL0.15-0.89-1.060.85-0.12-1.221.990.06-0.070.7910.651.208.061.510.541.664.178.690.801.031.08
5546Mikal BridgesSFPHO0.07-0.30-0.59-0.65-0.230.42-0.490.830.221.0614.172.264.231.401.170.445.5910.461.601.910.83
8447Draymond GreenPFGSW0.07-1.421.470.55-1.290.820.830.38-0.94-1.267.526.967.300.351.331.092.935.591.301.983.02
6356Kyle LowryPGMIA0.03-0.431.72-0.560.660.15-0.83-0.460.47-0.8813.407.524.482.291.060.274.389.952.352.762.67
6762Mike ConleyPGUTA-0.01-0.380.77-1.130.720.84-0.78-0.59-0.030.1313.695.353.012.351.330.294.7810.991.792.251.71
8165Marcus SmartPGBOS-0.02-0.651.00-0.820.041.73-0.86-0.78-0.06-0.4312.135.873.801.681.680.254.2310.112.002.522.24
Averages0.18-0.110.360.240.120.390.61-0.110.04-0.2315.294.436.511.751.160.985.4911.752.563.182.05

Z score data provided by fantazscores.com

Punting rebounds

Some of these are pretty obvious, but for this build we’re going guard heavy. Look for players that have multiple position eligibility since trying to roster an abnormal amount of guards could get tricky depending on how your league is set up. If you have a few PG/SG, SG/SF – that could go a long way in making sure you can roster a complete team every day regardless of position eligibility and games played. There’s some room for margin with this build since everyone rebounds.. You could still technically win a rebounding category with guards who produce above average in that category, but don’t always plan for that. Since you have to roster some C’s and PF’s, target players who can produce in other categories that are multi-position eligible.

Top Players Based on Z Scores for Punting Rebounds:

Rk

Punt Rk

Name

Pos

Team

TotalZ

PtsZ

AstsZ

RebsZ

ThreesZ

StlsZ

BlksZ

FgsZ

FtsZ

TovsZ

Pts

Asts

Rebs

3s

Stls

Blks

Fgs

Fgas

Fts

Ftas

Tovs

116Trae YoungPGATL0.592.072.68-0.851.44-0.15-1.19-0.392.55-2.2828.369.703.743.070.950.099.3620.326.587.283.99
1713Jimmy ButlerSFMIA0.440.900.820.00-1.161.66-0.420.111.89-0.3121.395.475.890.471.650.476.9814.546.957.982.12
2414Donovan MitchellSGUTA0.421.650.76-0.661.841.22-1.01-0.730.83-1.2225.875.344.213.461.480.189.2120.543.994.672.99
5740Tyrese MaxeyPGPHI0.140.250.30-1.060.13-0.71-0.510.190.730.7017.484.283.201.760.730.436.4413.272.843.281.17
5542Mikal BridgesSFPHO0.12-0.30-0.59-0.65-0.230.42-0.490.830.221.0614.172.264.231.401.170.445.5910.461.601.910.83
6746Mike ConleyPGUTA0.09-0.380.77-1.130.720.84-0.78-0.59-0.030.1313.695.353.012.351.330.294.7810.991.792.251.71
6354Kyle LowryPGMIA0.05-0.431.72-0.560.660.15-0.83-0.460.47-0.8813.407.524.482.291.060.274.389.952.352.762.67
8162Marcus SmartPGBOS0.00-0.651.00-0.820.041.73-0.86-0.78-0.06-0.4312.135.873.801.681.680.254.2310.112.002.522.24
8069Frank KaminskyCPHO-0.03-0.91-0.95-0.53-1.08-0.310.200.700.751.3510.561.444.560.560.890.784.007.332.002.220.56
9787Dorian Finney-SmithPFDAL-0.10-0.83-0.76-0.470.520.24-0.39-0.04-0.440.8811.001.884.692.151.100.494.088.650.701.041.00
84119Draymond GreenPFGSW-0.18-1.421.470.55-1.290.820.830.38-0.94-1.267.526.967.300.351.331.092.935.591.301.983.02
146140Isaiah HartensteinCLAC-0.25-1.29-0.55-0.40-1.43-0.700.921.10-0.720.638.282.354.880.210.741.133.375.381.341.941.24
Averages0.11-0.110.56-0.550.010.43-0.380.030.44-0.1415.324.874.501.651.180.495.4511.432.793.321.96

Z score data provided by fantazscores.com

Punting Assists

Ah, the white whale – guards who don’t assist. Again, position eligibility is key here. Players who are split SG/PG don’t primarily handle the ball meaning they usually tally up all of the usual guard stats with lower than average assist numbers. Again, it’s not always about drafting people who don’t produce in these categories, it’s about production in other categories. You might want to load up on quality C’s, PF’s and SF’s with a few guards who really fit this build to make the most of it. 

Top Players Based on Z Scores for Punting Assists:

Rk

Punt Rk

Name

Pos

Team

TotalZ

PtsZ

AstsZ

RebsZ

ThreesZ

StlsZ

BlksZ

FgsZ

FtsZ

TovsZ

Pts

Asts

Rebs

3s

Stls

Blks

Fgs

Fgas

Fts

Ftas

Tovs

32Joel EmbiidCPHI0.772.440.252.28-0.260.321.570.650.57-1.3930.574.1811.711.371.131.469.7919.629.6211.813.15
2311Myles TurnerCIND0.48-0.52-1.120.46-0.18-0.884.310.43-0.400.5812.861.057.071.450.672.814.769.361.882.501.29
2117Devin BookerSGPHO0.331.800.54-0.341.060.32-0.60-0.251.22-0.5826.794.845.032.691.130.389.7420.904.635.342.38
2725DeMar DeRozanPFCHI0.241.980.58-0.29-0.98-0.29-0.730.812.02-0.5827.874.925.160.660.890.3210.1820.206.847.802.38
4629Gary Trent JrSGTOR0.210.39-0.70-1.241.361.90-0.82-1.260.520.8418.332.012.732.991.740.276.4315.512.492.911.04
5436Mo BambaCORL0.17-0.89-1.060.85-0.12-1.221.990.06-0.070.7910.651.208.061.510.541.664.178.690.801.031.08
7553Lauri MarkkanenSFCLE0.05-0.21-1.00-0.090.60-0.70-0.38-0.460.601.0014.751.335.662.230.740.495.1311.522.262.610.89
8266Norman PowellSGLAC-0.020.50-0.65-1.050.73-0.19-0.43-0.250.190.3218.962.133.222.360.930.476.2013.444.205.181.53
11469Brook LopezCMIL-0.03-0.60-1.38-0.71-0.17-1.010.96-0.120.410.9612.380.464.081.460.621.154.6910.081.541.770.92
9780Dorian Finney-SmithPFDAL-0.07-0.83-0.76-0.470.520.24-0.39-0.04-0.440.8811.001.884.692.151.100.494.088.650.701.041.00
Averages0.210.41-0.53-0.060.26-0.150.55-0.040.460.2818.422.405.741.890.950.956.5213.803.504.201.57

Z score data provided by fantazscores.com

Punting Percentages

By far the most freeing punt build – grab any player regardless of what they shoot. Want to bolster blocks? Grab that center who shoots 50% from the free-throw line. Want to increase your 3-pointer production? Grab that guard who shoots less than 30% from the field but only shoots 3’s – it really doesn’t matter! Since most category leagues have 2 percentages (FG% and FT%), punting both already lowers your chances of competing in 2 categories. Not ideal, but if you nail the other positions then you should be clear sailing! By pairing a lower shooting guard from the field who is pretty effective from the line with a high efficient big man from the field but not pretty at the line, there may be a possibility you net even. That’s mad scientist stuff though so if you go down that path, be prepared for several sleepless nights sweating small percentages in these categories.

Top Players Based on Z Scores for Punting Percentages:

Rk

Punt Rk

Name

Pos

Team

TotalZ

PtsZ

AstsZ

RebsZ

ThreesZ

StlsZ

BlksZ

FgsZ

FtsZ

TovsZ

Pts

Asts

Rebs

3s

Stls

Blks

Fgs

Fgas

Fts

Ftas

Tovs

62Stephen CurryPGGSW0.751.581.19-0.262.830.83-0.65-0.971.93-1.4725.476.315.234.451.330.368.3619.124.304.663.22
167Fred VanVleetPGTOR0.640.721.35-0.572.101.81-0.28-1.640.85-0.8320.316.684.453.721.710.546.8016.882.983.422.62
2930Nikola VucevicCCHI0.270.28-0.162.01-0.21-0.120.59-0.03-0.22-0.0317.643.2311.011.420.960.977.4815.811.261.661.86
5242OG AnunobySFTOR0.130.19-0.44-0.150.771.22-0.32-0.62-0.380.1817.122.605.502.401.480.526.4414.521.852.461.67
4745Al HorfordCBOS0.12-0.97-0.110.70-0.34-0.771.32-0.080.200.9410.163.367.681.290.711.333.868.251.161.380.94
7350D'Angelo RussellPGMIN0.090.351.53-1.011.08-0.14-0.69-1.280.31-0.7518.097.083.322.710.950.346.1715.003.053.692.54
9967Buddy HieldSGIND-0.01-0.06-0.34-0.601.61-0.27-0.75-1.250.39-0.0615.622.834.363.230.900.315.5113.561.371.571.89
12680Julius RandlePFNYK-0.060.690.671.590.04-0.70-0.28-1.49-0.83-1.6620.105.149.941.670.740.547.1117.314.215.573.40
13683Cole AnthonyPGORL-0.070.060.91-0.210.40-0.77-0.84-1.580.70-0.8316.345.685.352.030.710.265.4914.033.323.892.62
10590Patrick BeverleyPGMIN-0.09-1.140.45-0.69-0.200.380.44-0.70-0.600.619.194.624.141.431.160.903.057.521.662.291.26
9892Kyle KuzmaPFWAS-0.110.19-0.031.020.31-0.960.37-0.44-0.98-0.7717.123.538.501.940.640.866.4114.182.363.322.56
Averages0.150.170.460.170.760.05-0.10-0.920.12-0.4217.014.646.322.391.030.636.0614.202.503.082.23

Z score data provided by fantazscores.com

Punting Blocks

This one is pretty simple – big men who don’t block. This may be a little shocking, but there’s a lot of those out there! This build will be pretty even across the roster.. Most guards have lower than average blocks compared to the outliers, so you’ll have an even blend of every category.

Top Players Based on Z Scores for Punting Blocks:

Rk

Punt Rk

Name

Pos

Team

TotalZ

PtsZ

AstsZ

RebsZ

ThreesZ

StlsZ

BlksZ

FgsZ

FtsZ

TovsZ

Pts

Asts

Rebs

3s

Stls

Blks

Fgs

Fgas

Fts

Ftas

Tovs

117Trae YoungPGATL0.632.072.68-0.851.44-0.15-1.19-0.392.55-2.2828.369.703.743.070.950.099.3620.326.587.283.99
1614Fred VanVleetPGTOR0.470.721.35-0.572.101.81-0.28-1.640.85-0.8320.316.684.453.721.710.546.8016.882.983.422.62
3225Jrue HolidayPGMIL0.290.381.41-0.550.341.56-0.500.51-0.35-0.9518.286.824.491.971.610.437.1314.242.042.692.73
2934Nikola VucevicCCHI0.190.28-0.162.01-0.21-0.120.59-0.03-0.22-0.0317.643.2311.011.420.960.977.4815.811.261.661.86
5343CJ McCollumSGNOP0.131.020.65-0.611.310.32-0.66-0.36-1.09-0.2322.105.084.342.941.130.358.6518.771.872.742.05
5547Mikal BridgesSFPHO0.10-0.30-0.59-0.65-0.230.42-0.490.830.221.0614.172.264.231.401.170.445.5910.461.601.910.83
6349Kyle LowryPGMIA0.08-0.431.72-0.560.660.15-0.83-0.460.47-0.8813.407.524.482.291.060.274.389.952.352.762.67
6755Mike ConleyPGUTA0.04-0.380.77-1.130.720.84-0.78-0.59-0.030.1313.695.353.012.351.330.294.7810.991.792.251.71
7467Gordon HaywardSFCHO-0.02-0.020.00-0.520.12-0.12-0.47-0.270.470.1915.883.614.571.760.960.455.7812.592.573.041.65
4774Al HorfordCBOS-0.05-0.97-0.110.70-0.34-0.771.32-0.080.200.9410.163.367.681.290.711.333.868.251.161.380.94
12396Kevin LoveCCLE-0.13-0.40-0.630.530.90-1.69-0.88-0.630.350.5413.612.167.242.530.350.244.4210.282.242.681.32
Averages0.160.180.64-0.200.620.20-0.38-0.280.31-0.2117.055.075.392.251.090.496.2013.502.402.892.03

Z score data provided by fantazscores.com

Punting Steals

Usually you enter the draft with a list of players you want to target who are steal-gods. If you find yourself doing the opposite and punting steals, you pretty much can just draft like normal. Most defensive stats come in pairs (blocks & steals, rebounds & blocks, etc) so don’t go out of your way to not gather steals. It’s still a very important category that can go either way any given week! Plus, you never know who might come knocking for some steals later in the year with a trade. 

Top Players Based on Z Scores for Punting Steals:

Rk

Punt Rk

Name

Pos

Team

TotalZ

PtsZ

AstsZ

RebsZ

ThreesZ

StlsZ

BlksZ

FgsZ

FtsZ

TovsZ

Pts

Asts

Rebs

3s

Stls

Blks

Fgs

Fgas

Fts

Ftas

Tovs

22Kevin DurantPFBRK0.922.321.220.590.46-0.350.541.202.74-1.7429.876.387.402.090.870.9510.5120.276.767.443.47
188Kristaps PorzingisPFWAS0.510.70-0.560.85-0.10-0.731.96-0.321.270.2620.202.338.061.530.731.656.9015.044.865.611.59
4525Zach LaVineSGCHI0.251.410.40-0.511.13-1.02-0.680.041.00-0.7624.404.524.602.760.610.348.4317.704.785.602.55
4732Al HorfordCBOS0.21-0.97-0.110.70-0.34-0.771.32-0.080.200.9410.163.367.681.290.711.333.868.251.161.380.94
5434Mo BambaCORL0.19-0.89-1.060.85-0.12-1.221.990.06-0.070.7910.651.208.061.510.541.664.178.690.801.031.08
7054Jakob PoeltlCSAS0.04-0.42-0.361.35-1.62-0.892.141.89-2.870.2413.462.789.320.010.661.746.039.751.382.791.60
6555Clint CapelaCATL0.04-0.82-1.042.34-1.64-0.681.171.52-2.511.3111.081.2411.850.000.741.265.008.161.082.280.59
6456Jordan PooleSGGSW0.040.420.17-0.971.15-0.56-0.76-0.501.47-0.6618.494.003.422.780.790.306.2413.923.243.502.46
7561Lauri MarkkanenSFCLE0.01-0.21-1.00-0.090.60-0.70-0.38-0.460.601.0014.751.335.662.230.740.495.1311.522.262.610.89
12368Kevin LoveCCLE-0.03-0.40-0.630.530.90-1.69-0.88-0.630.350.5413.612.167.242.530.350.244.4210.282.242.681.32
9170Tyler HerroSGMIA-0.030.790.17-0.361.02-0.88-1.13-0.650.75-0.8520.713.984.982.650.670.127.5917.002.883.322.64
Averages0.200.18-0.250.480.13-0.860.480.190.270.1017.033.037.121.760.670.926.2112.782.863.481.74

Z score data provided by fantazscores.com

Punting Turnovers

Punting turnovers is pretty much a result of drafting high usage players, which you’re going to do especially in the early rounds. Turnovers are a part of the game and everyone will register a few a game. It’s a tricky science to try and “win” the TO category, usually that’s something that would swing your way if you’re dealing with a lot of injuries or have low games played in a week. Don’t fixate so much on projections here, instead review previous seasons stats and expect a similar number.

Top Players Based on Z Scores for Punting Turnovers:

Rk

Punt Rk

Name

Pos

Team

TotalZ

PtsZ

AstsZ

RebsZ

ThreesZ

StlsZ

BlksZ

FgsZ

FtsZ

TovsZ

Pts

Asts

Rebs

3s

Stls

Blks

Fgs

Fgas

Fts

Ftas

Tovs

11Nikola JokicCDEN1.361.851.883.09-0.321.200.352.580.21-2.0827.087.8913.771.311.470.8510.3217.725.126.323.80
2418Donovan MitchellSGUTA0.491.650.76-0.661.841.22-1.01-0.730.83-1.2225.875.344.213.461.480.189.2120.543.994.672.99
3623Darius GarlandPGCLE0.430.952.18-1.020.930.78-1.17-0.291.10-1.9221.668.573.292.561.310.107.9717.253.163.543.65
3935Bam AdebayoCMIA0.280.51-0.091.64-1.641.090.221.45-0.96-0.8619.073.3910.070.001.430.797.2513.024.576.072.64
7155Brandon IngramSFNOP0.051.110.87-0.03-0.29-1.00-0.42-0.330.51-0.9722.655.585.821.350.620.478.2417.874.845.852.75
8457Draymond GreenPFGSW0.05-1.421.470.55-1.290.820.830.38-0.94-1.267.526.967.300.351.331.092.935.591.301.983.02
12667Julius RandlePFNYK-0.040.690.671.590.04-0.70-0.28-1.49-0.83-1.6620.105.149.941.670.740.547.1117.314.215.573.40
10377Jusuf NurkicCPOR-0.08-0.16-0.352.03-1.370.26-0.140.87-1.77-0.7615.042.8011.050.271.110.615.7310.713.304.792.55
13694Cole AnthonyPGORL-0.170.060.91-0.210.40-0.77-0.84-1.580.70-0.8316.345.685.352.030.710.265.4914.033.323.892.62
10799Harrison BarnesPFSAC-0.230.07-0.52-0.110.21-0.82-1.01-0.090.460.3216.432.425.611.840.690.185.0810.834.435.361.53
Averages0.210.530.780.69-0.150.21-0.350.08-0.07-1.1219.185.387.641.481.090.516.9314.493.824.802.90

Z score data provided by fantazscores.com

Like what you see? Subscribe here!

Daily emails you can digest in 5 minutes or less!

  • Highlights and summaries of previous performance
  • Weekly scheduling outlook

  • Player trends and analysis
  • Fantasy basketball rankings
  • Tools to help you become a better manager