Where do they come from: a look at the geographic distribution of D1 players
One of the reasons that we enjoy being part of the lacrosse community is that it is so small. Like an up-and-coming band, the bond between sport and fan is stronger precisely because so few others share it. This is amplified by the fact that your author grew up in Baltimore, one of, if not the sport’s ancestral homeland. I still do not understand the “crab cakes and football” reference from Wedding Crashers; we didn’t even have a professional team for 13 years!
But the downside of this intimate relationship is that we effectively trade intimacy for resources. A larger sport won’t feel as personal, but it is stronger because size brings attention, attention breeds interest, interest raises participation rates, which drives competition and a better sport for all of us. So on net, I’d rather see more people get into lacrosse. We can welcome our new co-fans, comfortable in the knowledge that we’ve been here, enjoying lacrosse all along.
And whether you take the same view of expansion or not, this is a stats site, and we can’t end the discussion without applying some objective perspective to it. So how does one measure interest and the spread of lacrosse more generally. One way, which gets cited a lot, is the size of the crowds for championship weekend. More people come to see the finals, so the sport is growing. But anyone who cares about sample size knows that to put too much emphasis on a yearly event that accounts for < 1% of all games is misguided.
A good measure is youth participation, but this is very time intensive data to collect accurately and while there are groups that have done so, I’ve not seen enough granularity in the data sets. And anyway, how many kids play soccer in the U.S.? Millions. And how many people care about pro soccer. Um, less than that.
So for this post, we’ve gone somewhere in the middle: the distribution of men’s and women’s D1 players by state/country. By looking at where players come from, we can, by proxy, gauge participation and interest. After all, it’s going to be hard for a singular talent to develop in an area where there are relatively few players. But since we are looking at D1 players, we’ve let their coaches do some vetting for us. An entire survey of youth lacrosse will capture gross numbers, but since these are the top players, we can be sure that what we are looking at is the distribution of talent, not just the growth. I could stimulate more growth in Montana by building a lacrosse-only complex, buying everyone a stick, and hoping back in my hypothetical Gulfstream. But that is very unlikely to develop a D1 player; that is a more organic process.
Envelope please…
So what does a geographic look at D1 lacrosse show us? The tables below show the top movers by state/region in terms of the percentage of players in D-1 that hail from that location. I excluded any state that didn’t have a clear pattern (though they are available at the end in full tables). This allows us to distill the data down to just the places that are seeing significant gains or losses.
In general, what we found is consistent with a story of lacrosse filtering from the traditional strongholds toless traditionally interested areas. For example, Maryland, long punching above its weight, appears to be losing that grip on prep stars. (Note: the pct change values were calculated by taking the average of the 2014/2015 shares, then subtracting the average of the 2016/2017 shares.) I’ll use Maryland to explain the data below:
- In 2014, 11.4% of the men’s D-1 players listed Maryland as their home state (thanks to Inside Lacrosse for having such clean roster tables…).
- In 2015, that number actually rose slightly to 12%.
- The big drop off came recently with the 2017 rosters, where only 10.4% of the men’s players were from Maryland.
New York experienced a more consistent decline: 26.5% in 2014, then 25.8%, 23.7% and 23.5%. On the flip side, California, Massachusetts, Minnesota, Georgia, and Colorado experienced the largest gains. The top five gaining states saw an increase of 3%. This exactly offsets the loss of 3% for Maryland and New York.
State/Region | Share ’14 | Share ’15 | Share ’16 | Share ’17 | Change in Share |
---|---|---|---|---|---|
CA | 3.3% | 3.3% | 4.4% | 4.6% | 1.2% |
MA | 5.1 | 5.7 | 6.1 | 5.9 | 0.6 |
MN | 0.5 | 0.7 | 0.9 | 1.3 | 0.5 |
GA | 1.1 | 1.1 | 1.5 | 1.5 | 0.4 |
CO | 1.8 | 1.8 | 2.0 | 2.2 | 0.3 |
WA | 0.4 | 0.6 | 0.7 | 0.9 | 0.3 |
NC | 1.7 | 1.2 | 1.4 | 1.9 | 0.2 |
NJ | 11.2 | 10.9 | 11.3 | 11.2 | 0.2 |
VA | 3.9 | 3.8 | 3.6 | 3.6 | -0.2 |
OH | 2.3 | 2.3 | 2.2 | 1.9 | -0.2 |
PA | 9.9 | 9.7 | 9.8 | 9.3 | -0.3 |
TN | 0.6 | 0.6 | 0.3 | 0.2 | -0.4 |
CT | 5.2 | 4.9 | 4.6 | 4.7 | -0.4 |
MD | 11.4 | 12.0 | 11.9 | 10.4 | -0.5 |
NY | 26.5 | 25.8 | 23.7 | 23.5 | -2.5 |
On the women’s side, we see a very similar story. Ohio, New York, Pennsylvania, and Maryland lost share in women’s D1 players, as they did for the men. About the only noticeable difference is MA and VA. Massachusetts gained players on the men’s side, but lost players on the women’s side. Virginia gained the most on the women’s side, but lost share on the men’s side. Pure speculation, but VCU added women’s lacrosse for the 2015-16 season; perhaps the addition of another local team helped spur more girls to pursue a college career? Indeed, in 2016, 7 out of 23 players on the roster were listed as from Virginia, a 30% clip, but hardly enough to account for the entire change.
State/Region | Share ’14 | Share ’15 | Share ’16 | Share ’17 | Change in Share |
---|---|---|---|---|---|
VA | 4.5% | 4.0% | 4.7% | 5.2% | 0.6% |
NH | 0.9 | 1.0 | 1.3 | 1.5 | 0.5 |
CA | 3.8 | 4.0 | 3.5 | 5.3 | 0.5 |
GA | 1.3 | 1.4 | 1.6 | 1.9 | 0.4 |
FL | 2.2 | 2.7 | 2.9 | 2.6 | 0.3 |
NC | 0.8 | 1.2 | 1.4 | 1.3 | 0.3 |
IL | 1.2 | 1.1 | 1.1 | 1.6 | 0.2 |
MN | 0.6 | 0.8 | 0.8 | 1.0 | 0.2 |
IN | 0.1 | 0.1 | 0.2 | 0.4 | 0.2 |
OH | 1.8 | 1.6 | 1.4 | 1.4 | -0.3 |
NY | 23.4 | 23.9 | 24.0 | 22.7 | -0.3 |
MA | 5.8 | 6.1 | 5.8 | 4.7 | -0.7 |
PA | 10.5 | 9.5 | 9.4 | 8.6 | -1.0 |
MD | 21.2 | 19.5 | 18.8 | 18.5 | -1.7 |
So in conclusion, this data tells a story that probably wouldn’t surprise you if you follow the sport. Quality players are coming to college programs from farther afield than the traditional power regions. Frankly, I was a bit surprised to see that the pace of the change has not been faster. Whether it’s the budgets and resources available to recruiters or the slow pace of improvement in non-traditional areas, the pace has not been fast, but it’s hard to argue that it is happening. And barring some large change in the sport, I’d expect to see a few more Californias and Montanas showing up on college rosters over the coming years.
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In case you want to dig deeper
The following tables show the gains and losses in terms of player share for every state. Provinces in Canada are split out separately, as are Asia/Europe. Data was pulled from Inside Lacrosse rosters from 2014 through 2017.
Men’s Full Detail
State/Region | Share ’14 | Share ’15 | Share ’16 | Share ’17 | Change in Share |
---|---|---|---|---|---|
CA | 3.3% | 3.3% | 4.4% | 4.6% | 1.2% |
MA | 5.1 | 5.7 | 6.1 | 5.9 | 0.6 |
MN | 0.5 | 0.7 | 0.9 | 1.3 | 0.5 |
GA | 1.1 | 1.1 | 1.5 | 1.5 | 0.4 |
CO | 1.8 | 1.8 | 2.0 | 2.2 | 0.3 |
WA | 0.4 | 0.6 | 0.7 | 0.9 | 0.3 |
NC | 1.7 | 1.2 | 1.4 | 1.9 | 0.2 |
NJ | 11.2 | 10.9 | 11.3 | 11.2 | 0.2 |
DC | 0.2 | 0.2 | 0.4 | 0.5 | 0.2 |
Canada – ON | 2.9 | 3.4 | 3.4 | 3.3 | 0.2 |
UT | 0.0 | 0.2 | 0.2 | 0.3 | 0.2 |
NH | 0.6 | 0.6 | 0.7 | 0.8 | 0.1 |
SC | 0.0 | 0.0 | 0.1 | 0.2 | 0.1 |
OR | 0.1 | 0.1 | 0.2 | 0.3 | 0.1 |
DE | 0.5 | 0.5 | 0.6 | 0.5 | 0.1 |
Canada – CANAD | 0.0 | 0.0 | 0.2 | 0.0 | 0.1 |
Canada – QB | 0.0 | 0.0 | 0.1 | 0.1 | 0.1 |
ME | 0.1 | 0.2 | 0.2 | 0.2 | 0.1 |
FL | 1.8 | 1.6 | 1.5 | 2.0 | 0.1 |
VT | 0.3 | 0.2 | 0.2 | 0.3 | 0.0 |
AL | 0.1 | 0.1 | 0.1 | 0.2 | 0.0 |
NV | 0.2 | 0.2 | 0.3 | 0.2 | 0.0 |
Asia | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
IN | 0.3 | 0.3 | 0.2 | 0.4 | 0.0 |
Canada – Six Nations | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Canada – SK | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
MS | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 |
Europe | 0.1 | 0.1 | 0.1 | 0.0 | -0.0 |
Canada – MB | 0.0 | 0.1 | 0.0 | 0.1 | -0.0 |
AZ | 0.4 | 0.4 | 0.4 | 0.4 | -0.0 |
Canada – BC | 1.2 | 1.1 | 1.1 | 1.2 | -0.0 |
Canada – AB | 0.5 | 0.5 | 0.5 | 0.5 | -0.0 |
MT | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 |
KS | 0.0 | 0.1 | 0.1 | 0.0 | -0.0 |
TX | 1.4 | 1.6 | 1.3 | 1.6 | -0.0 |
HI | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 |
RI | 0.3 | 0.5 | 0.3 | 0.4 | -0.0 |
IL | 1.3 | 1.3 | 1.2 | 1.2 | -0.1 |
MO | 0.4 | 0.2 | 0.2 | 0.2 | -0.1 |
MI | 1.8 | 1.6 | 1.5 | 1.6 | -0.1 |
WI | 0.2 | 0.2 | 0.1 | 0.2 | -0.1 |
KY | 0.3 | 0.4 | 0.3 | 0.2 | -0.1 |
VA | 3.9 | 3.8 | 3.6 | 3.6 | -0.2 |
OH | 2.3 | 2.3 | 2.2 | 1.9 | -0.2 |
PA | 9.9 | 9.7 | 9.8 | 9.3 | -0.3 |
TN | 0.6 | 0.6 | 0.3 | 0.2 | -0.4 |
CT | 5.2 | 4.9 | 4.6 | 4.7 | -0.4 |
MD | 11.4 | 12.0 | 11.9 | 10.4 | -0.5 |
NY | 26.5 | 25.8 | 23.7 | 23.5 | -2.5 |
Women’s Full Detail
State/Region | Share ’14 | Share ’15 | Share ’16 | Share ’17 | Change in Share |
---|---|---|---|---|---|
VA | 4.5% | 4.0% | 4.7% | 5.2% | 0.6% |
NH | 0.9 | 1.0 | 1.3 | 1.5 | 0.5 |
CA | 3.8 | 4.0 | 3.5 | 5.3 | 0.5 |
GA | 1.3 | 1.4 | 1.6 | 1.9 | 0.4 |
FL | 2.2 | 2.7 | 2.9 | 2.6 | 0.3 |
NC | 0.8 | 1.2 | 1.4 | 1.3 | 0.3 |
IL | 1.2 | 1.1 | 1.1 | 1.6 | 0.2 |
MN | 0.6 | 0.8 | 0.8 | 1.0 | 0.2 |
IN | 0.1 | 0.1 | 0.2 | 0.4 | 0.2 |
Canada – BC | 0.2 | 0.3 | 0.4 | 0.6 | 0.2 |
Canada – ON | 0.7 | 0.9 | 0.9 | 1.1 | 0.2 |
CO | 1.2 | 1.5 | 1.5 | 1.5 | 0.2 |
DC | 0.0 | 0.1 | 0.2 | 0.3 | 0.1 |
KY | 0.0 | 0.0 | 0.1 | 0.2 | 0.1 |
UT | 0.1 | 0.0 | 0.1 | 0.2 | 0.1 |
SC | 0.1 | 0.2 | 0.2 | 0.2 | 0.1 |
WI | 0.0 | 0.0 | 0.1 | 0.0 | 0.1 |
MI | 0.8 | 0.9 | 0.9 | 0.9 | 0.0 |
AL | 0.0 | 0.0 | 0.1 | 0.1 | 0.0 |
Canada – AB | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
ME | 0.1 | 0.2 | 0.2 | 0.2 | 0.0 |
KS | 0.0 | 0.1 | 0.1 | 0.1 | 0.0 |
AZ | 0.1 | 0.1 | 0.1 | 0.1 | 0.0 |
MISSO | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
NJ | 10.8 | 11.5 | 11.0 | 11.3 | 0.0 |
VT | 0.2 | 0.1 | 0.2 | 0.2 | 0.0 |
TN | 0.3 | 0.4 | 0.3 | 0.4 | 0.0 |
WA | 0.3 | 0.3 | 0.4 | 0.3 | 0.0 |
AK | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 |
Australia | 0.2 | 0.1 | 0.2 | 0.1 | -0.0 |
NV | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 |
MS | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 |
WV | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 |
CT | 4.0 | 3.4 | 3.9 | 3.5 | -0.0 |
OR | 0.2 | 0.3 | 0.2 | 0.3 | -0.0 |
MO | 0.2 | 0.2 | 0.1 | 0.2 | -0.0 |
RI | 0.3 | 0.6 | 0.5 | 0.3 | -0.1 |
Europe | 0.2 | 0.2 | 0.2 | 0.0 | -0.1 |
TX | 0.8 | 0.9 | 0.7 | 0.8 | -0.1 |
DE | 0.6 | 0.8 | 0.7 | 0.5 | -0.1 |
OH | 1.8 | 1.6 | 1.4 | 1.4 | -0.3 |
NY | 23.4 | 23.9 | 24.0 | 22.7 | -0.3 |
MA | 5.8 | 6.1 | 5.8 | 4.7 | -0.7 |
PA | 10.5 | 9.5 | 9.4 | 8.6 | -1.0 |
MD | 21.2 | 19.5 | 18.8 | 18.5 | -1.7 |