Who Will Score? Part III: The Leading Candidates

In our first two parts, we dug into the history books to determine whether or not the need to replace volume scoring had a negative impact on offensive efficiency going forward. While the general conclusion seems to be that other than at the extremes there is very little correlation between scoring lost and offensive efficiency, what fun would it be to throw up our hands and say "well, hopefully someone will score, let's be done with it!"

Now before you dig in too far, please keep the following in mind. This has been expanded to a five-part series, and while some of the parts may have less satisfying takeaways than readers (and, frankly, the author) expected, to fully understand the goal of the team and the overall final projections, you will need to read the series all the way to the end.

Who might carry the scoring lead after Justin Lewis & Darryl Morsell?
 Photo by Charles Fox | Philadephia Inquirer

When projecting who will lead a team in scoring, there are really three main factors:

• Minutes Played: If you aren't on the court, you aren't going to score. However, because simply being on the court doesn't guarantee you will score, it can't be considered alone.
• Percent of Shots Taken: Usage rate alone doesn't tell the story because it factors in possessions that end in ways other than with a shot taken. Looking at the percentage of shots a player gets while on the floor indicates how many scoring chances they will have.
• Effective Field Goal Percentage: Stat nerds (and I imagine most readers here) have long preferred eFG% to other measures of shot efficiency. The easiest explanation is that it is field goal percentage with a 50% boost given to made three point shots because 3 is 50% more than 2.

To approximate next year's performance, we looked at players with similar past profiles to Marquette's returnees and weighed those past seasons against their future results. When you look at the charts, the portion above the break is that player's comparison player average (comps listed at the end of each player's synopsis) and the player's past and projected future numbers are below the break.

After breaking those down, we will be able to project 2022-23 expected minutes played, percent of shots taken, and effective field goal percentage. Those numbers will be balanced against 60 shots per game to produce an expected points per game average, with a slight adjustment for free throw rate and percentage using last year's numbers.

We will also provide expected best and worst case scenarios by using the three top and bottom comps from individual samples. For all players, we took the three biggest single-year comparable jumps and smallest comparable jumps (or biggest declines) and applied the average of those three to each player's 2021-22 season at Marquette. Let's count down the three most likely candidates to lead the team in scoring.

#3 - Tyler Kolek

Photo from espn.com

In his first year at Marquette, Kolek became far more of a creator than he was at George Mason as his percent shots and eFG% both dropped. While that seems like a negative harbinger for his scoring, it's worth noting that the comps we found of players moving up a level often went through similar situations. Looking at Kolek's comparable players, when you counted their pre-transfer seasons twice and their first season at the new program once, then averaged those three, it had a near perfect second-year post-transfer correlation. The respective percentages were accurate to 1.6% of minutes, 0.2% of percent shots, and 0.02% of eFG%. We used that transfer correlation for Kolek only (it didn't fare the same with O-Max's comps). Let's check the numbers:

	%Min	%Shot	eFG%	PPG
Pre-Transfer	76.8	25.0	50.3
Transfer Year 1	60.5	19.2	49.3
Transfer Year 2	73.5	23.0	50.0
Tyler Kolek (PT)	75.5	19.5	53.1	10.8
Tyler Kolek (TY1)	72.3	16.7	40.0	6.7
Tyler Kolek (22-23)	74.4	18.6	48.7	9.3
Tyler Kolek (Worst)	76.6	18.2	38.4	7.7
Tyler Kolek (Best)	80.4	22.4	48.7	12.2

The first thing to note is that based on his comparable players, Kolek is highly likely to bounce back in terms of eFG%. Most of the comparable players that saw an eFG dip in their first post-transfer year improved that in their next year. With an expected increase in minutes and usage, Kolek will almost certainly increase his scoring as well. I was a little surprised by the 12.2 ppg best case comparison. That will likely depend on his role in 2022-23. If he continues to primarily play point guard and run the offense, that number is probably the best case scenario, while if he moves off the ball his percent of shots taken and eFG% could both be higher.

It's worth noting we have already seen improvement with Kolek in his first year. He shot just 22% from deep in non-conference games but improved that to 33.3% in Big East play. He also hit 51.4% of his catch-and-shoot threes, so if others are creating for Kolek rather than him creating for himself (he hit a dismal 14.7% on threes off the dribble) he could even exceed his best case scenario. In addition, the early reports out of camp is that Kolek looks like the most improved player on the team and has been scorching the nets after apparently taking the criticisms of his shooting last season personally. Expecting him to be around double-digit scoring is a relatively safe assumption.

Tyler Kolek Comparisons: Jared Bynum, Donald Carey, Torin Dorn, Elijah Harkless, Ithiel Horton, Koby McEwen, Quincy McKnight, Marcquise Reed, Andrew Rowsey, Eric Williams

Worst Case Comparisons: Ithiel Horton, Quincy McKnight, Eric Williams

Best Case Comparisons: Jared Bynum, Elijah Harkless, Koby McEwen 

#2 - Olivier-Maxence Prosper

Photo from Marquette Athletics

Already showing up on some of the 2023 NBA Draft boards, O-Max seems like the safest bet to make a jump in 2022-23. Our comparisons back that up, as even his worst-case options project to improve his percent of shots and eFG%. Quite simply, similar statistical players that played limited minutes in their first collegiate year, then transferred and saw big minute jumps like Prosper did in their second year tended to continue ascending in year three. There was no equivalent comparison like Kolek that incorporated the pre-transfer year, so we strictly did transfer year one to year two improvement percentages. With Justin Lewis gone, it seems likely Prosper will get every chance to increase his scoring.

	%Min	%Shot	eFG%	PPG
Pre-Transfer	21.8	16.3	45.2
Transfer Year 1	51.7	17.8	51.8
Transfer Year 2	60.2	20.2	56.4
O-Max Prosper (PT)	22.3	17.3	37.5	2.5
O-Max Prosper (TY1)	51.2	16.8	51.8	6.6
O-Max Prosper (22-23)	59.5	19.1	56.4	9.4
O-Max Prosper (Worst)	47.1	19.5	53.7	7.3
O-Max Prosper (Best)	77.6	18.2	62.3	12.7

In all honesty, the best-case scenario might be the most realistic for Prosper, and it's possible he could even exceed that. 80% of the comparable players improved in percent of shots taken, 80% improved in eFG%, and 90% increased their minutes. Double-digit scoring seems highly likely as he will get all the shots he previously got and many that Justin would've taken last year. Though while the gut feel is that the best case scenario is attainable, it did seem a bit surprising that the second highest scoring projection was still under 10 ppg.

Olivier-Maxence Prosper Comparisons: Nick Babb, Jemarl Baker, Colin Castleton, Luke Fischer, Dan Fitzgerald, Anton Gill, Myke Henry, Tariq Owens, Jonathan Tchamwa Tchatchouwa, Jamil Wilson

Worst Case Comparisons: Jemarl Baker, Colin Castleton, Myke Henry

Best Case Comparisons: Nick Babb, Anton Gill, Tariq Owens

#1 - Kam Jones

Photo from jsonline.com

I imagine it's no surprise to see Kam Jones as the expected leader on this list. His three point shooting ability, high usage, and a long but productive comparable list really lead to high expectations. However, there are some rather unencouraging comparisons that keep us from ruling out a sophomore slump and while his best case scenario is lofty, it isn't the highest best case scenario we could see, but that will come in the next part. Let's break out the numbers:

	%Min	%Shot	eFG%	PPG
Freshmen Sample	43.8	20.7	48.7
Sophomore Sample	64.1	21.9	49.8
Kam Jones (Fr)	44.5	22.9	55.9	7.4
Kam Jones (22-23)	65.1	24.2	57.2	11.3
Kam Jones (Worst)	47.8	23.0	51.1	7.1
Kam Jones (Best)	84.6	25.9	68.9	18.9

The average improvements for Kam's comps come up favorable, but considering how far he was ahead of the average eFG%, it seems unlikely he will jump far (almost certainly not to the best case scenario). This admittedly includes some players who saw precipitous eFG% drops, such as Markus Howard and Steve Novak, who mostly fell because they were otherworldly in terms of shooting the ball as freshmen.

I would caution those excited by the big numbers in Jones' best case scenario, a guard reaching 68.9% eFG% is highly unlikely. Not impossible, but his three best case scenario comps all came from players who had freshman year eFG% in the 40s, so they had significantly more room to grow and it was easier for them to have large percentage jumps because of their initial low shooting percentages, unlike Jones for whom it will be harder to improve on 55.9%. I think Jones is the most likely player to lead the team in scoring and reach double-digits but he might also be the least likely to hit his best case scenario.

Kam Jones Player Comps: Brendan Bailey, Justin Blake, Vander Blue, Sandy Cohen, Eric Davis, Jase Febres, Lazar Hayward, Markus Howard, Ryan Kreklow, Justin Lewis, Dameon Mason, Wesley Matthews, Shemiye McLendon, Steve Novak, Kerwin Roach

Worst Case Scenarios: Justin Blake, Eric Davis, Shemiye McLendon

Best Case Scenarios: Brendan Bailey, Jase Febres, Justin Lewis

Rapid Takeaways

 

At a glance, I felt like these numbers, at least the most likely projections, felt low. Of the six returning players with the highest minutes, these were indeed the three that projected to have the highest points per game output. That said, there is more encouraging news on the way. While scoring won't likely be as consolidated as it was last year (remember, Justin Lewis' 16.8 ppg is the highest ever for a Shaka player) it seems likely that the scoring will be more spread out. For instance, these top scorers all have an expected 2022-23 baseline of over 9.0 ppg, whereas in 2021-22 only two players (Lewis & Morsell) exceeded 8.0 ppg.

Who Will Score? Part II: Shaka Smart

Shaka Smart will say goodbye to leading scorer Justin Lewis
 Photo by Mike de Sisti | Milwaukee Journal-Sentinel

In our last edition, Cracked Sidewalks looked at Marquette's history when it comes to the loss of volume points per game scoring and whether that has an impact on subsequent offensive efficiency. Because Marquette is losing four of the top seven points per game scorers, the obvious question we are trying to answer is "Who Will Score" in 2022-23.

Today, Cracked Sidewalks has gone back and looked at the entire coaching career of Shaka Smart. Due to relevance, we are also looking at the final seasons of the coaches that preceded him: Anthony Grant at VCU, Rick Barnes at Texas, and Steve Wojciechowski at Marquette. Using the same method as the last article, we are starting with the total number of points scored. We are then looking at the number of significant points lost, which were points scored by players that averaged 5.0 ppg or more. Using those two numbers, we could establish the percentage of significant points lost and match that up with the team's Adjusted Offensive Efficiency Rank as well as the Rank Change for the following year once they lost that percentage of points.

These seasons include Smart's entire career, with the "VCU/TX/MU" designations indicating the years before Coach Smart took over so we can see what impact his hiring had. We will again start with the raw data and then break it down into smaller bits to look at trends.

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rank	Rk Change
2021-22	2369	1329	56.1	64	??
2020-21 MU	1883	1450	77.0	94	30
2020-21	2008	1069	53.2	28	2
2019-20	1989	0	0.0	153	125
2018-19	2628	1375	52.3	29	-124
2017-18	2450	802	32.7	89	60
2016-17	2215	1084	48.9	177	88
2015-16	2355	1226	52.1	49	-128
2014-15 TX	2290	675	29.5	47	-2
2014-15	2609	934	35.8	58	0
2013-14	2624	749	28.5	106	48
2012-13	2770	680	24.5	20	-86
2011-12	2448	484	19.7	96	76
2010-11	2864	1671	58.3	47	-39
2009-10	2737	598	21.8	28	-19
2008-09 VCU	2440	937	38.4	64	36

While Smart's 2021-22 team sees 56.1% of the significant scoring depart, his team last year had more to replace, as did his 2010-11 Final Four team, with nearly opposite results. Last year they replaced 77.0% of the scoring and saw the Adjusted Offensive Efficiency improve by 30 spots while in 2011 he lost 58.3% of the scoring and saw the Adjusted Offensive Efficiency decline by 39 spots. Let's group it out to see if there are any meaningful trends.

Major Point Losses: 60+%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rank	Rk Change
2020-21 MU	1883	1450	77.0	94	30

Compared to Marquette's own history, Smart has quite the short list. The only time he had to replace more than 60% of his scoring was last year when he took over Marquette from Steve Wojciechowski and saw a significant Offensive Efficiency improvement. Bear in mind the only number here that is actually Smart's responsibility is the "Rank Change" improvement. If this says anything, it might be that Smart is better at balancing classes and retaining players so that the only time he's ever been in position to replace so much was taking over a new program.

Moderate Point Losses: 40-59%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rank	Rk Change
2010-11	2864	1671	58.3	47	-39
2021-22	2369	1329	56.1	64	??
2020-21	2008	1069	53.2	28	2
2018-19	2628	1375	52.3	29	-124
2015-16	2355	1226	52.1	49	-128
2016-17	2215	1084	48.9	177	88

Hard to look at this and not see those two massive declines. The -124 and -128 are the two biggest drops in the 37 total seasons we reviewed between Smart's career and Marquette's history. And yet Smart's second greatest single-season improvement is also in this category. It's worth noting the 2 point improvement was made by Chris Beard as that was Smart's last season at Texas. The data here indicates Smart has at times struggled replacing significant scoring, though the small sample size and the 2017 outlier definitely shows it's not a definitive struggle.

Minor Point Losses: 20-39%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rank	Rk Change
2008-09 VCU	2440	937	38.4	64	36
2014-15	2609	934	35.8	58	0
2017-18	2450	802	32.7	89	60
2014-15 TX	2290	675	29.5	47	-2
2013-14	2624	749	28.5	106	48
2012-13	2770	680	24.5	20	-86
2009-10	2737	598	21.8	28	-19

This brings us back to the essential "nothing matters" conclusion. Three seasons where most of the scoring is retained end up in improvements, three end up in declines (including bizarrely the two that kept the most), and one had no change (though that was in a coaching change to Will Wade).

Minimal Point Losses: 0-19%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rank	Rk Change
2011-12	2448	484	19.7	96	76
2019-20	1989	0	0.0	153	125

Another small sample size, but retaining 80+% of his scoring led to big improvements in the rare events when it's happened. The general takeaway seems to be that while losing scoring won't necessarily hurt you, retaining scoring seems likely to help. Though all one has to do to question that is look at the two entries immediately above these minimal loss results.

Summary

In total, there were 37 past seasons reviewed between Marquette's history and Smart's career. When looking at the most extreme outliers, there were four seasons classified as minimal loss (less than 20% of significant scoring lost) and four seasons classified as major loss (60% or greater significant scoring lost). With last year's 77% loss resulting in a 30-spot improvement with the transition from Wojciechowski to Smart being the outlier, the other seven results all resulted in improvement or decline as would be expected. So at the extremes, keeping scoring is good and losing scoring is bad.

The scatter plot below supports that. When you look at the seasons where the Percent of Points Lost (X-Axis) is below 20%, it always yields positive results in the AORtg Rank Change (Y-Axis). When you look at seasons where the Percent of Points Lost is greater than 60%, it usually yields negative results (2021-22 was the 77% outlier).

However in the minor and moderate ranges, highlighted yellow on the plot, the results were all over the place. In 17 seasons of minor loss (20-39%), there were 8 teams that improved, 8 teams that declined, and one team that stayed the same, with the range being anywhere from an 86 spot decline to a 108 spot improvement. In 12 seasons of moderate loss (40-59%), there were 6 teams that improved and 6 teams that declined, with the range being anywhere from a 128 spot decline to an 88 spot improvement.

Trivia Answer: Justin Lewis' 16.8 ppg is the most ever for a player under Shaka Smart
Photo by Aaron Gash | AP Photo

Back to our trivia question from our preview article, Justin Lewis' 16.8 ppg is the most ever scored by a player on a Shaka Smart team. If anything, that should be reassuring to fans as typically, Smart simply doesn't have offenses that heavily revolve around one player. Replacing scoring is always going to be a team effort. Treveon Graham (16.2 ppg in 2014-15, 15.8 ppg in 2013-14, 15.1 ppg in 2012-13), Jamie Skeen (15.7 ppg in 2010-11), and Isaiah Taylor (15.0 ppg in 2015-16) are the only other players to reach the 15 ppg mark. In general, the scoring load for Smart is spread among a number of players rather than centered on one or two individual talents like we've sometimes seen at Marquette in recent years.

If there's any takeaway, it's that when you lose between 20-60% of your scoring, there's virtually no correlation between an offensive efficiency improvement or decline. Statistically speaking, replacing scoring is not something fans should get worked up about.

Who Will Score? Part I: Marquette

Justin Lewis has his eyes on the NBA Draft

Photo from @jusbuckets on Instagram

With Marquette losing four of their top seven points per game scorers from the 2021-22 season, Cracked Sidewalks is going to comb the history of Marquette offenses to see what happened when teams lost significant scoring as we try to answer the question of "Who Will Score" in 2022-23.

To answer this, Cracked Sidewalks went back and looked at the past 24 seasons of Marquette Basketball. We started by looking at the total number of points scored. We then looked at the number of significant points lost, which were points scored by players that averaged 5.0 ppg or more. Using those two numbers, we could establish the percentage of significant points lost and match that up with the team's Adjusted Offensive Efficiency Rank as well as the Rank Change for the following year once they lost that percentage of points.

The reason for that number was because we wanted to include Kuath as a floor, but if we included everyone, we would be looking at walk-ons and garbage time players who don't usually factor heavily into results. Apologies to the Duane Wilsons (4.8 ppg in 2016-17) of the Marquette world, but you didn't have enough offensive output to be a major factor in most games in your final Marquette season, even if that Villanova hesi will live forever in Marquette lore. Using those numbers, we were able to determine the percentage of significant points lost, compare that to the Adjusted Offensive Efficiency rank on Kenpom, and evaluate if losing volume scoring equated to a loss in team offensive quality.

Duane Wilson vs Villanova, a little Marquette basketball porn
 GIF courtesy of Anonymous Eagle

Why 24 seasons? It allowed us to capture the complete Marquette careers of Tom Crean, Buzz Williams, and Steve Wojciechowski, as well as the last year of Mike Deane and the first year of Shaka Smart. We didn't go further because, well, kenpom doesn't go back much further that. But it does seem like a pretty solid sample size. We'll start with the raw data, but since it's a lot to digest, we will break that down into smaller bits to look for trends.

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rk	Rk Change
2021-22	2369	1329	56.1	64	??
2020-21	1883	1450	77.0	94	30
2019-20	2333	1413	60.6	14	-80
2018-19	2629	836	31.8	32	18
2017-18	2846	757	26.6	12	-20
2016-17	2631	1034	39.3	8	-4
2015-16	2517	561	22.3	116	108
2014-15	2083	1094	52.5	154	38
2013-14	2310	1631	70.6	97	-57
2012-13	2382	1045	43.9	24	-73
2011-12	2638	1237	52.2	40	16
2010-11	2782	900	32.3	22	-18
2009-10	2485	1142	46.0	21	-1
2008-09	2739	1652	60.3	9	-12
2007-08	2658	193	7.3	20	11
2006-07	2443	0	0.0	62	42
2005-06	2325	872	37.5	27	-35
2004-05	2080	1006	48.4	62	35
2003-04	2207	546	24.7	44	-18
2002-03	2589	1219	47.1	2	-42
2001-02	2413	999	41.4	30	28
2000-01	1902	544	28.6	68	38
1999-00	1820	422	23.2	104	36
1998-99	1823	427	23.4	193	89

The first takeaway is that while Marquette is losing 56.1% of last year's points from significant scorers, that isn't the high-water mark. 2021, 2014, 2020, and 2009 all saw teams lose more than 60% of their scoring. And while 56.1% is in the upper range, that is just one of 12 totals where teams lost 40+% of their scoring from significant scorers, so there's plenty of comparable company. To make this easier to digest, let's group these out a bit.

Major Point Losses: 60+%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rk	Rk Change
2020-21	1883	1450	77.0	94	30
2013-14	2310	1631	70.6	97	-57
2019-20	2333	1413	60.6	14	-80
2008-09	2739	1652	60.3	9	-12

The first thing that jumps out here is that three of the four teams in this group saw declines in the subsequent years. Despite that, the team that lost the most in 2020-21, when Wojo was fired and the top-5 scorers left, was the one that saw significant improvement. Shaka's new system, player improvement, and smart roster additions made up for those departures. The biggest falloff came when Markus Howard left, joined by Sacar Anim and Brendan Bailey. The problem there, however, was not so much a lack of quantity (Dawson Garcia, DJ Carton, and Koby McEwen all averaged 10+ ppg) and more one of quality as no one could replicate Howard's efficiency at that usage rate.

One thing that stands out the most might be 2008-09, which was when the Amigos left Marquette. Despite their departure, the 9th ranked offense only fell to 21st thanks to players like Lazar Hayward, Jimmy Butler, and Maurice Acker providing efficient offense and scoring volume. In this case, I would point to smart coaching as the reason the decline was relatively minimal. In 2009-10 Buzz Williams focused on shooting (5th nationally in 3PFG%) and turnover rate (7th lowest) while also slowing the pace (from 67.5 to 62.3 possessions per game) in order to maximize the impact of his shooters. What this (and 2020-21) tells you is that you can lose a ton of scoring and still maintain an efficient offense if the coach is good enough to overcome the loss of even efficient scorers.

It's also worth noting that the 2021 and 2014 teams represent two of just three times that Marquette lost five players who averaged 5+ ppg, though with radically different next season results.

Moderate Point Losses: 40-59%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rk	Rk Change
2021-22	2369	1329	56.1	64	??
2014-15	2083	1094	52.5	154	38
2011-12	2638	1237	52.2	40	16
2004-05	2080	1006	48.4	62	35
2002-03	2589	1219	47.1	2	-42
2009-10	2485	1142	46.0	21	-1
2012-13	2382	1045	43.9	24	-73
2001-02	2413	999	41.4	30	28

If ever there was a chart that shows how meaningless retaining scoring volume is, this is probably it. We don't know the fate of the 2022 departures, but four of the other seven teams actually improved their offensive rank. If you add up the previous seven, the +/- rank comes out to 1, which means the average rank change of teams losing between 40-59% of their scoring over this period was 0.14. There were certainly some big swings in there, but by and large the average change is effectively zero.

It also seems worth noting that while there are some great departing classes on this list, such as Crowder and DJO in 2012 (16 spot improvement), Diener and Mason in 2005 (35 spot improvement), and Wade and Jackson in 2003 (42 spot decline), the biggest decline in the group came from the second smallest percentage of significant points lost when Vander Blue, Junior Cadougan, and Trent Lockett left in 2013.

Minor Point Losses: 20-39%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rk	Rk Change
2016-17	2631	1034	39.3	8	-4
2005-06	2325	872	37.5	27	-35
2010-11	2782	900	32.3	22	-18
2018-19	2629	836	31.8	32	18
2000-01	1902	544	28.6	68	38
2017-18	2846	757	26.6	12	-20
2003-04	2207	546	24.7	44	-18
1998-99	1823	427	23.4	193	89
1999-00	1820	422	23.2	104	36
2015-16	2517	561	22.3	116	108

The overall +/- rank for these 10 seasons comes out to +194, which initially might seem like it supports there being a big benefit to returning players, but I would point to the circumstances around those seasons as well. How much of that massive 1998-99 to 1999-2000 jump was personnel change and how much was it having a flat out better offensive coach as that was the year Tom Crean replaced Mike Deane. How much was 2015-16 a product of not losing much (really just Henry Ellenson) and how much was adding Markus Howard, Andrew Rowsey, Sam Hauser, and Katin Reinhardt? And why would half of the seasons in this category see the offense get worse?

Minimal Point Losses: 0-19%

Year	Total Pts	Sig Pts Lost	% Pts	AdjO Rk	Rk Change
2007-08	2658	193	7.3	20	11
2006-07	2443	0	0.0	62	42

Again, this might indicate some support about returning scorers, but the numbers here are in line with the improvement seasons in the 40-59% category, so maybe the takeaway is that the Amigos got better the longer they were here. Further, two seasons is a pretty small sample size, so it's hard to take much away from this. What this really shows is that losing volume scoring doesn't tell you much about what will happen the next season.

Players step up into scoring roles because the game demands it. When Dwyane Wade left, it was Travis Diener and Steve Novak. When the Amigos left, it was Hayward and Butler. When Crowder and DJO left, it was Blue, Jamil Wilson, and Gardner. When Ellenson left, it was Howard and Rowsey. And when Garcia, Carton, and McEwen left, it was Justin Lewis, who improved his 7.8 ppg with a 93.8 Adjusted Offensive Rating as a freshman to 16.8 ppg with a 101.9 Adjusted Offensive Rating in an NBA-caliber season.

Summary

Ultimately, at Marquette there has been virtually no correlation between losing volume scoring and a comparable decline in offensive efficiency. Some teams that lost a lot, like 2004-05 with Travis Diener and Dameon Mason departing or 2011-12 with Jae Crowder and Darius Johnson-Odom graduating, actually improved the next year in terms of offensive efficiency. Last year's team had to replace more significant scoring than any other season in 24 years and not only didn't get worse, they got significantly better on the offensive end.

Crowder & DJO left in 2012, but Vander Blue & Jamil Wilson led a better 2013 offense

Photo by Christian Peterson | Getty Images

At the other end, some teams that lost relatively little, such as the 2003-04 team with Scott Merritt and Terry Sanders or the 2017-18 team that really only lost Andrew Rowsey still took steps back despite retaining most of their scoring. And sometimes these do go to expectation, such as the 2019-20 team losing Markus Howard and Sacar Anim as the team took a big step back or the 2006-07 team retaining all of their significant scoring and improving significantly with that continuity. The bottom line is that the simple loss of volume scoring is not a guarantee that a team will step back offensively, so Marquette fans concerned about the loss of Lewis and Morsell may want to pump the brakes before worrying about next season's offense.