Richmond Player Impact Matrix

flyder19

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Hi All, Flyder here! New to writing in the forum but not new to Richmond Basketball!

Ahead of the season opener against VMI, I've created the Richmond Player Impact Matrix, or RPIM for short. For each game this season, I'll be tracking RPIM for the entire team and posting results here as a recap for the previous game. RPIM uses all in-game statistics in connection with team averages to produce a cumulative RPIM score for each player per game. There are two bonus categories not from the stat sheet that will also be included: Turnover resulting in points for opponent and Clutch/Impact Plays (which is subjective, but should be clear)

Starting off, point values for 2PT, 3PT, and FT are based off of last season's averages (52%, 33%, and 72% respectively), though once enough games have been played, the RPIM will be calculated with the running averages and RPIM from previous games will be updated accordingly.

Excited to launch this here, and to let you get a glimpse into RPIM, here are the Totals from 2021-2022's players (not including bonus statistics):

PlayerRPIM
Jacob Gilyard283.19
Tyler Burton184.48
Grant Golden171.82
Matt Grace67.75
Connor Crabtree26.59
Nathan Cayo23.46
Andre Gustavson17.85
Dji Bailey6.27
Gabe Arizin0.50
Quentin Southall0.00
Sullivan Kulju-1.57
Jordan Gaitley-2.57
Marcus Randolph-9.97
Souleymane Koureissi-17.08
Nick Sherod-17.43
Isiah Wilson-57.16
 
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flyder19

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RPIM for VMI

RPIM MVP: Neal Quinn

PlayerRPIM
Neal Quinn8.31
Isiah Bigelow7.77
Tyler Burton4.36
Andre Gustavson3
Aidan Noyes2
Matt Grace1.77
Dji Bailey1.2
Mike Walz-1
Marcus Randolph-1.07
Jason Roche-1.3
Jason Nelson-3.52

Quinn's efficiency gets it done, though Bigelow showed some strong flashes and deserves a spot in the starting 5. Nelson had some electric plays but made some mistakes and missed too many free throws, but if he cleans that up, he'll be at the top consistently. Burton largely struggled but made up some gap with his Double Double via the boards.
 
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Section9.RowD

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RPIM for VMI

RPIM MVP: Neal Quinn

PlayerRPIM
Neal Quinn8.31
Isiah Bigelow7.77
Tyler Burton4.36
Andre Gustavson3
Aidan Noyes2
Matt Grace1.77
Dji Bailey1.2
Mike Walz-1
Marcus Randolph-1.07
Jason Roche-1.3
Jason Nelson-3.52
Hmmmm … welcome to the forum
 
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ur2K

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Can we get 2011's opinion on this before we pay any attention to it?
 
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fan2011

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My feeling is that this metric is what I would call an ad hoc composite metric, which generally means it is fun to look at but not super informative. If there is a white paper on the metric I will gladly read it and perhaps change my mind.
 
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flyder19

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if your formula shows Nelson had the worst impact in the game last night, then your formula doesn't work right.
Totally understand. It's a more holistic statistic across the Stat line measuring against total team statistics throughout the season. These numbers are only accounting for one game and so I'd expect this to be more representative as the season goes on, similar to the play of our players.

Also, RPIM will be adjusted for each player as numbers change throughout the season, so look for it to much more representative as the season evolves.

Overall, I think Nelson had a nice game for his first start. But, his performance at the line let him down and him taking the largest share of shots meant he is held to a high standard for the game.
 

VT4700

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if your formula shows Nelson had the worst impact in the game last night, then your formula doesn't work right.
No doubt. Nelson's FTs had no impact on the game, so why would they be given so much importance over all the really good things he did? And looking at the whole year last year, all 37 games, Crab was more impactful than Cayo??? And more impactful than Goose??? I don't think we will get any telling information at all from this, so count me out, but, if others like it, have fun.
 
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flyder19

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No doubt. Nelson's FTs had no impact on the game, so why would they be given so much importance over all the really good things he did? I don't think we will get any telling information at all from this, so count me out, but, if others like it, all good.
This is a good point and thanks for the feedback. Maybe I can look into adding in Score differential as a weighting mechanism for the entire season. That way, games like VMI where we win by 20+ will be weighted less compared to games where the differential is under 5. Therefore stong/weak performances mean more in those close games. Thoughts on this @VT4700 ?
 

spiderman

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Totally understand. It's a more holistic statistic across the Stat line measuring against total team statistics throughout the season. These numbers are only accounting for one game and so I'd expect this to be more representative as the season goes on, similar to the play of our players.

Also, RPIM will be adjusted for each player as numbers change throughout the season, so look for it to much more representative as the season evolves.

Overall, I think Nelson had a nice game for his first start. But, his performance at the line let him down and him taking the largest share of shots meant he is held to a high standard for the game.
ok, but I'm saying the formula doesn't work and you need to rethink it before people take it seriously.
13 points on 14 "shots", 2 rebounds, 3 assists, 2 steals and 0 turnovers can't be the lowest "impact" on the team for this one game.

your formula says a guy who made 1 garbage time bucket had the 5th highest impact for the team in this game. granted it was a nice shot, but no.
 

flyder19

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ok, but I'm saying the formula doesn't work and you need to rethink it before people take it seriously.
13 points on 14 "shots", 2 rebounds, 3 assists, 2 steals and 0 turnovers can't be the lowest "impact" on the team for this one game.

your formula says a guy who made 1 garbage time bucket had the 5th highest impact for the team in this game. granted it was a nice shot, but no.
Got it, I'll look into additional weighting mechanisms. This is brand new, and like the team, could use some tweaking, appreciate all the input though!
 

VT4700

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This is a good point and thanks for the feedback. Maybe I can look into adding in Score differential as a weighting mechanism for the entire season. That way, games like VMI where we win by 20+ will be weighted less compared to games where the differential is under 5. Therefore stong/weak performances mean more in those close games. Thoughts on this @VT4700 ?
That is probably a good idea, and makes sense. Also, looking at last year's numbers, I would try to adjust things enough where Nate and Goose would be well ahead of Crab, instead of behind him. Maybe the negatives are too negative in your formula? And, maybe the positives are not rated highly enough? Whatever the reason, a couple of guys who played well last year, and were a huge part of a lot of our wins should not end up behind a guy who averaged 2 points a game and did not play much.

Also, to get this as accurate as possible, maybe you could go back and look at each individual game last year, see if there were any strange results like the Nelson one from last night, and then see if tweaking the formula would help.

I do like seeing stats sometimes, but it is hard for me to get anything out of your chart. Maybe it would help to know a little more by showing what each player's top positive was and top negative? That would at least tell us a little more.
 

flyder19

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That is probably a good idea, and makes sense. Also, looking at last year's numbers, I would try to adjust things enough where Nate and Goose would be well ahead of Crab, instead of behind him. Maybe the negatives are too negative in your formula? And, maybe the positives are not rated highly enough? Whatever the reason, a couple of guys who played well last year, and were a huge part of a lot of our wins should not end up behind a guy who averaged 2 points a game and did not play much.

Also, to get this as accurate as possible, maybe you could go back and look at each individual game last year, see if there were any strange results like the Nelson one from last night, and then see if tweaking the formula would help.

I do like seeing stats sometimes, but it is hard for me to get anything out of your chart. Maybe it would help to know a little more by showing what each player's top positive was and top negative? That would at least tell us a little more.
Yeah, I'll look into this and look back at 2022. I like the idea of showing the most positive and most negative stat for the week for additional context and more intel. Feedback is super important to get it right, so continue to voice positive and constructive sentiments!
 

Spiders05

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Welcome to the Board. Think you have some refinements but look forward to seeing how the algorithm works out over the course of the year. Not sure how you're procuring your data but perhaps some additional backtesting across some prior UR teams beyond just last year.
 

flyder19

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Welcome to the Board. Think you have some refinements but look forward to seeing how the algorithm works out over the course of the year. Not sure how you're procuring your data but perhaps some additional backtesting across some prior UR teams beyond just last year.
Thank you! I'll run my updates against the cumulative statistics from the previous 5 seasons, but with the updates I'm working on now, it seems much more realistic!
 
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flyder19

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Adjustments have been made to RPIM based on everyone's input. Thanks for chiming in!

More factors are taken into account to measure impact, such as Minutes and Shot Attempts, and various Statistics weights have been adjusted (Fouls weighted less as an example). I think this paints a much more accurate picture of the 2021-2022 season, but let me know what you think! I also included RPIM/Game to account for injuries (Goose for example missing the start of the season):

PlayerRPIMRPIM/Game
Jacob Gilyard540.8214.62
Tyler Burton424.7611.48
Grant Golden387.7010.48
Nathan Cayo209.085.65
Matt Grace175.054.62
Andre Gustavson125.354.48
Nick Sherod104.632.83
Connor Crabtree72.842.08
Isiah Wilson27.100.82
Dji Bailey26.531.66
Gabe Arizin0.600.60
Quentin Southall0.100.10
Sullivan Kulju-1.00-0.33
Jordan Gaitley-2.00-0.67
Marcus Randolph-4.35-0.48
Souleymane Koureissi-6.32-0.45

Going game by game, here are the RPIM MVP's along with their best and worst games RPIM-wise from last season. Really shows Gilyard's consistency, as well as Burtons lack thereof (while still performing well in many games). Fun fact: Matt Grace is the only one on this list where his Best Game was not when he was the MVP, that was against Dayton in the A-10 Tournament with an RPIM of 16.83:

PlayerRPIM MVP'sBest GameRPIMWorst GameRPIM
Jacob Gilyard14Fordham35.36Dayton (A-10)1.81
Tyler Burton12St. Bonaventure (H)26.58VCU (H)-9.96
Grant Golden9Bucknell30.88Toledo-8.46
Nathan Cayo1La Salle (A)19.82Drake-7.75
Matt Grace1GA State18.83VCU (A)-4.01

I'll be sharing RPIM's from the previous 4 seasons as well, stay tuned there. As always, open for any and all feedback!
 

VT4700

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My concern here would be the negative numbers. As poorly as those guys might have played that game, they shouldn't be lower than a guy who didn't play.
 

Section9.RowD

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My concern here would be the negative numbers. As poorly as those guys might have played that game, they shouldn't be lower than a guy who didn't play.
hmm - but sort of like a negative WAR in baseball, right?
 

flyder19

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@VT4700 I understand your concern there, but I will push back slightly. Not that I'm an expert by any means, but negative numbers are quite common when it comes to player stats, the most common of those being Plus/Minus for basketball. Though I will say, I'm not a big fan of negative numbers either, hence why I'm creating something new away from Plus/Minus.

For example, comparing Marcus Smart to Peyton Pritchard (Celtics fan here), Plus/Minus on the season so far says Marcus Smart is -34 (-3.4/game) whereas Peyton Pritchard is +2 (+0.7/game). It's clear this does not represent actual player performance and impact for the Celtics

Using RPIM, Smart would have a score of 118.79 and Pritchard would be at -0.18. Smart may have some negative RPIM games individually, but cumulatively, he's far more impactful on the Celtics' results. Compared to Tatum's 235.93 RPIM, however, it's clear who's the star.

This is not to say RPIM is the golden metric, but negatives are just a part of poor performance, and making it cumulative adjusts for these poor performances
 
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VT4700

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@VT4700 I understand your concern there, but I will push back slightly. Not that I'm an expert by any means, but negative numbers are quite common when it comes to player stats, the most common of those being Plus/Minus for basketball. Though I will say, I'm not a big fan of negative numbers either, hence why I'm creating something new away from Plus/Minus.

For example, comparing Marcus Smart to Peyton Pritchard (Celtics fan here), Plus/Minus on the season so far says Marcus Smart is -34 (-3.4/game) whereas Peyton Pritchard is +2 (+0.7/game). It's clear this does not represent actual player performance and impact for the Celtics

Using RPIM, Smart would have a score of 118.79 and Pritchard would be at -0.18. Smart may have some negative RPIM games individually, but cumulatively, he's far more impactful on the Celtics' results. Compared to Tatum's 235.93 RPIM, however, it's clear who's the star.

This is not to say RPIM is the golden metric, but negatives are just a part of poor performance, and making it cumulative adjusts for these poor performances
But, with plus minus, you know exactly what that is. When a guy is on the floor and not on the floor. If Marcus Smart has a negative number and a guy has a 0, that tells me Boston got outscored while Smart was on the floor. But, it doesn't mean Smart played poorly, and the guy with a 0 plus minus played better.

You are trying to find impact, which should be more dramatic and more telling than +/-. Smart can still impact the game positively for the Celtics even though his +/- might be negative. So, my issue with negatives with your formula is if Tyler has a bad game like he did against VCU and gets a negative 8 for this, and then gets a positive 8 for a good game, this means he had the same impact as a guy who didn't play over those 2 games. I would disagree with that. That is why I would weigh the positives more and the negatives less. But, share what the numbers for the VMI game look like with your adjustments. Maybe it will be more telling now.
hmm - but sort of like a negative WAR in baseball, right?
Maybe this is why I don't like his stats as much as others might. I think war is an awful stat. But, just my opinion, and just giving suggestions. If others like it the way it is, cool.
 
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flyder19

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@VT4700 Gotcha, totally understand that point, and thanks for your continued suggestions. Here is the updated RPIM from VMI as it stands with changes. Let me know if this is more in line with your thoughts on the game. Overall, the RPIM's weren't that strong in this game, and I think that reflects the team's performance, could've been stronger:

PlayerRPIM
Isiah Bigelow11.92
Neal Quinn11.46
Tyler Burton10.71
Andre Gustavson7.05
Matt Grace4.97
Dji Bailey4.65
Jason Nelson2.78
Aidan Noyes2.45
Jason Roche1.9
Marcus Randolph1.08
Mike Walz-0.7
 
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Section9.RowD

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@VT4700 Gotcha, totally understand that point, and thanks for your continued suggestions. Here is the updated RPIM from VMI as it stands with changes. Let me know if this is more in line with your thoughts on the game. Overall, the RPIM's weren't that strong in this game, and I think that reflects the team's performance, could've been stronger:

PlayerRPIM
Isiah Bigelow11.92
Neal Quinn11.46
Tyler Burton10.71
Andre Gustavson7.05
Matt Grace4.97
Dji Bailey4.65
Jason Nelson2.78
Aidan Noyes2.45
Jason Roche1.9
Marcus Randolph1.08
Mike Walz-0.7
Even if I am a bit lukewarm about sports analytics in general, I continue to love what you are doing with this - seems imo that you have tweaked enough for the 1st game .. let's see how your latest model works after Friday night .. very curious about what your background/career is. Realizing we all have the right to be anonymous if so desired on this spectactular forum, shockingly I sit in Section 9 Row D if you happen to be local to the RVA and go to games - would love to chat - won't be at the UNI game since will be out of town but attend pretty much all games including the Wich State game on Thursday the 17th.
 

flyder19

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Even if I am a bit lukewarm about sports analytics in general, I continue to love what you are doing with this - seems imo that you have tweaked enough for the 1st game .. let's see how your latest model works after Friday night .. very curious about what your background/career is. Realizing we all have the right to be anonymous if so desired on this spectactular forum, shockingly I sit in Section 9 Row D if you happen to be local to the RVA and go to games - would love to chat - won't be at the UNI game since will be out of town but attend pretty much all games including the Wich State game on Thursday the 17th.
Thanks @Section9.RowD, unfortunately I'm one of those New England implants who made their way back North after graduating, though I was able to snag a Section 5 seat for the home opener and $80 round trip tickets! My career has nothing to do with stats and spreadsheets, but I'm just a big fan of them on the side and thought about doing this for a while. At Richmond, you could find me at every game in a headset on the court, so let's just say all the malfunctions on Monday night hurt me personally. Staff has had a lot of turnover
 

Section9.RowD

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Thanks @Section9.RowD, unfortunately I'm one of those New England implants who made their way back North after graduating, though I was able to snag a Section 5 seat for the home opener and $80 round trip tickets! My career has nothing to do with stats and spreadsheets, but I'm just a big fan of them on the side and thought about doing this for a while.
Awesome - maybe you see you in Brooklyn then? A relatively large group of my mid 90s grad friends will be in the Spider section for both the Monday and Tuesday night games Turkey day week.
 
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flyder19

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For those curious, here are the RPIM's for 2017-2021 seasons. As expected, TJ dominated his final year and Gilyard the same right from the jump throughout his career. Sherod's 2017-2018 season stands out as well:

2016-2017

PlayerRPIMRPIM/Game
TJ Cline508.3014.52
Shawndre' Jones380.9310.88
De'Monte Buckingham312.128.92
Khwan Fore229.496.56
Nick Sherod208.905.97
Julius Johnson160.214.58
Marshall Wood51.311.66
Joe Kirby27.781.11
Kwesi Abakah20.910.60
Chase Fletcher0.200.07
Jesse Pistokache-0.06-0.01
Paul Friendshuh-0.51-0.06
Keith Oddo-0.8-0.80
Grant Golden*-1.1335-0.13

2017-2018

PlayerRPIMRPIM/Game
Jacob Gilyard390.2112.19
Nick Sherod385.1412.04
De'Monte Buckingham301.5010.05
Grant Golden280.948.78
Khwan Fore187.266.46
Julius Johnson112.843.53
Nathan Cayo46.471.45
Joe Kirby24.280.90
Solly Stansbury20.381.20
Keith Oddo5.301.06
Jordin Madrid-Andrews-1.51-0.12
Paul Friendshuh-7.22-0.33

2018-2019

PlayerRPIMRPIM/Game
Jacob Gilyard452.9414.61
Grant Golden320.439.71
Nathan Cayo275.358.34
Jake Wojcik224.126.79
Andre Gustavson151.244.88
Noah Yates125.203.79
Julius Johnson103.573.34
Nick Sherod*58.349.72
Matt Grace52.691.70
Souleymane Koureissi35.191.35
Bryce Schneider4.411.10
Keith Oddo3.260.36
Jordan Gaitley0.350.12
Sullivan Kulju0.300.10
Tomas Verbinskis-2.24-2.24

2019-2020

PlayerRPIMRPIM/Game
Jacob Gilyard436.4514.08
Nick Sherod316.8310.22
Grant Golden287.549.92
Nathan Cayo220.127.34
Blake Francis169.936.80
Andre Gustavson116.723.77
Jake Wojcik96.723.12
Tyler Burton94.133.14
Matt Grace26.510.91
Souleymane Koureissi23.290.78
Tomas Verbinskis9.553.18
Jordan Gaitley2.800.35
Gabe Arizin0.000.00
Sullivan Kulju-7.90-0.99

2020-2021 (Covid Shortened Season)

PlayerRPIMRPIM/Game
Jacob Gilyard302.5413.15
Grant Golden214.2110.20
Tyler Burton206.909.00
Blake Francis150.397.52
Nathan Cayo146.386.36
Matt Grace85.293.71
Andre Gustavson76.574.25
Connor Crabtree25.926.48
Souleymane Koureissi14.920.65
Dji Bailey13.871.54
Isiah Wilson5.960.30
Sullivan Kulju4.732.37
Gabe Arizin0.300.15
Quentin Southall0.200.20
Jordan Gaitley0.02140.0107

(* = Key Injury)

Let me know if this fits with your observations!
 
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VT4700

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@VT4700 Gotcha, totally understand that point, and thanks for your continued suggestions. Here is the updated RPIM from VMI as it stands with changes. Let me know if this is more in line with your thoughts on the game. Overall, the RPIM's weren't that strong in this game, and I think that reflects the team's performance, could've been stronger:

PlayerRPIM
Isiah Bigelow11.92
Neal Quinn11.46
Tyler Burton10.71
Andre Gustavson7.05
Matt Grace4.97
Dji Bailey4.65
Jason Nelson2.78
Aidan Noyes2.45
Jason Roche1.9
Marcus Randolph1.08
Mike Walz-0.7
Nelson barely above Noyes? Yikes!

Nelson: 28 minutes, 13 pts, 3 assists, 2 steals, 2 rebounds, and 0 turnovers.

Noyes: 2 minutes, 2 points.
 

VT4700

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For those curious, here are the RPIM's for 2017-2021 seasons. As expected, TJ dominated his final year and Gilyard the same right from the jump throughout his career. Sherod's 2017-2018 season stands out as well:

2016-2017

PlayerRPIMRPIM/Game
TJ Cline508.3014.52
Shawndre' Jones380.9310.88
De'Monte Buckingham312.128.92
Khwan Fore229.496.56
Nick Sherod208.905.97
Julius Johnson160.214.58
Marshall Wood51.311.66
Joe Kirby27.781.11
Kwesi Abakah20.910.60
Chase Fletcher0.200.07
Jesse Pistokache-0.06-0.01
Paul Friendshuh-0.51-0.06
Keith Oddo-0.8-0.80
Grant Golden*-1.1335-0.13

2017-2018

PlayerRPIMRPIM/Game
Jacob Gilyard390.2112.19
Nick Sherod385.1412.04
De'Monte Buckingham301.5010.05
Grant Golden280.948.78
Khwan Fore187.266.46
Julius Johnson112.843.53
Nathan Cayo46.471.45
Joe Kirby24.280.90
Solly Stansbury20.381.20
Keith Oddo5.301.06
Jordin Madrid-Andrews-1.51-0.12
Paul Friendshuh-7.22-0.33

2018-2019

PlayerRPIMRPIM/Game
Jacob Gilyard452.9414.61
Grant Golden320.439.71
Nathan Cayo275.358.34
Jake Wojcik224.126.79
Andre Gustavson151.244.88
Noah Yates125.203.79
Julius Johnson103.573.34
Nick Sherod*58.349.72
Matt Grace52.691.70
Souleymane Koureissi35.191.35
Bryce Schneider4.411.10
Keith Oddo3.260.36
Jordan Gaitley0.350.12
Sullivan Kulju0.300.10
Tomas Verbinskis-2.24-2.24

2019-2020

PlayerRPIMRPIM/Game
Jacob Gilyard436.4514.08
Nick Sherod316.8310.22
Grant Golden287.549.92
Nathan Cayo220.127.34
Blake Francis169.936.80
Andre Gustavson116.723.77
Jake Wojcik96.723.12
Tyler Burton94.133.14
Matt Grace26.510.91
Souleymane Koureissi23.290.78
Tomas Verbinskis9.553.18
Jordan Gaitley2.800.35
Gabe Arizin0.000.00
Sullivan Kulju-7.90-0.99

2020-2021 (Covid Shortened Season)

PlayerRPIMRPIM/Game
Jacob Gilyard302.5413.15
Grant Golden214.2110.20
Tyler Burton206.909.00
Blake Francis150.397.52
Nathan Cayo146.386.36
Matt Grace85.293.71
Andre Gustavson76.574.25
Connor Crabtree25.926.48
Souleymane Koureissi14.920.65
Dji Bailey13.871.54
Isiah Wilson5.960.30
Sullivan Kulju4.732.37
Gabe Arizin0.300.15
Quentin Southall0.200.20
Jordan Gaitley0.02140.0107

(* = Key Injury)

Let me know if this fits with your observations!
Blake is surprisingly low. I think Blake impacted our games positively as much as anyone. Sorry, I am probably being too critical. It could be because I am not a big "dive deeper into stats" analytics guy. Though many on here will tell you I love stats, and I do often use them, I am more of a simple stats guy combined with the eye test. My eyes told me Blake was outstanding and carried us at times, and also told me Nelson impacted the game positively as much as anyone for us Monday. I am probably the wrong guy to ask for suggestions.
 

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Thanks @Section9.RowD, unfortunately I'm one of those New England implants who made their way back North after graduating, though I was able to snag a Section 5 seat for the home opener and $80 round trip tickets! My career has nothing to do with stats and spreadsheets, but I'm just a big fan of them on the side and thought about doing this for a while. At Richmond, you could find me at every game in a headset on the court, so let's just say all the malfunctions on Monday night hurt me personally. Staff has had a lot of turnover
I’m in Boston if you ever want to watch a game. I push our alumni office to get game watches together, but they’re usually only open to it for the VCU games. I had to strong arm them last year to host one for the Tourney!
 
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flyder19

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Blake is surprisingly low. I think Blake impacted our games positively as much as anyone. Sorry, I am probably being too critical. It could be because I am not a big "dive deeper into stats" analytics guy. Though many on here will tell you I love stats, and I do often use them, I am more of a simple stats guy combined with the eye test. My eyes told me Blake was outstanding and carried us at times, and also told me Nelson impacted the game positively as much as anyone for us Monday. I am probably the wrong guy to ask for suggestions.
Yeah, at first glance I thought so as well @VT4700. Thing is, looking into it further, I think it's clear that Blake was a streaky player. He had plenty of games at the top of both the scoreboard and RPIM while here, showing his exciting play style and its impact on our team, but he also had games where he was a detractor, and still impactful in that way. When we played West Virginia, as an example, his line was 12 points, 5/17 Shooting, 1/10 from 3, 1/5 at the line, 3 TO, 0 Assists amongst others. Cumulative RPIM rewards high quality play but also consistency of all aspects of play. Blake had the former but not the latter.
 
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VT4700

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I hear you about consistent play, but if you only have average players on your team, you won't win a lot. You have impact in the title, not consistency. You can look at a tough game against WVU and say, see my formula shows this, but when looking at the total year, should one or maybe a few games drop a guy who was clearly one of our main, high impact players all year so low? Your final numbers had Blake as close to Wojcik on the low end as he was to Nick on the high end. That is pretty much my point about I think your positives are not rated highly enough and your negatives are ready way too low. But, as I said before, just my opinion.
 

flyder19

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I hear you about consistent play, but if you only have average players on your team, you won't win a lot. You have impact in the title, not consistency. You can look at a tough game against WVU and say, see my formula shows this, but when looking at the total year, should one or maybe a few games drop a guy who was clearly one of our main, high impact players all year so low? Your final numbers had Blake as close to Wojcik on the low end as he was to Nick on the high end. That is pretty much my point about I think your positives are not rated highly enough and your negatives are ready way too low. But, as I said before, just my opinion.
Valid input and thanks for that, I'll keep that in mind as the season progresses!
 

spiderman

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focusing on the VMI game, I think your formula still needs adjusting.
Nelson should slot in at 4th. you can't tell me Grace's stat line in 27 minutes was more impactful. or Goose's.
 

flyder19

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focusing on the VMI game, I think your formula still needs adjusting.
Nelson should slot in at 4th. you can't tell me Grace's stat line in 27 minutes was more impactful. or Goose's.
FT Shooting was a factor here. I'll keep my eyes out on weighting for it, but you also can't go 25% from the stripe 🤷‍♂️
 

VT4700

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FT Shooting was a factor here. I'll keep my eyes out on weighting for it, but you also can't go 25% from the stripe 🤷‍♂️
I think your formula is probably way too negative on missed FTs. Why should it be way better to just be in the game doing nothing than drawing a foul on someone and missing FTs? What would Nelson's numbers had been had he gone 2-2 at the line and missed 3 more shots? Because 2 missed FTs is no different than a missed 2 point shot. Both cost you 2 points. Impact wise, it is actually better because with FTs, you draw a foul on someone and get closer to the bonus. Sure, you want to knock down FTs, but impact wise, I think your negatives with them are way too negative. An accurate impact formula can't have Nelson barely above Noyes.
 

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