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Of Lacrosse and Efficiency

[Preface]
Unlike America's primary three sports, lacrosse has received little attention in terms of statistical development and methodology. Those statistics that have dominated the game since the inception of its recordation are still at the forefront of examining production and value.

Unfortunately, those traditional methods have become dated and I think there are better methods for determining production. The methodology I am proposing in this essay is similar to much of the material I have presented on football and basketball, where an eye is turned toward possession-based statistics rather than game or season-based averages.

Possession-based statistics, as opposed to traditional statistical approaches, provide a truer examination of efficiency, whether offensive or defensive. Analyzing team or player efficiency is preferable to traditional "averages" analysis because efficiency illustrates an individual's or team's consistency. Traditional statistics, however, tend to reward an entity for a particularly impressive performance and having that output residually imputed to underachieving performances. This kind of inaccuracy is unacceptable.

[Methodology]
As noted above, I am proposing in this essay the use of a possession-based method to examine a team's offensive and defensive efficiency. However, the implementation of this system is not without difficulty.

Unlike many college basketball teams, there are not, currently, any college lacrosse teams that chart possessions. Consequently, to determine the number of possessions a team generates in a contest, we need to find those events in the boxscore that mark the end or beginning of a given possession. As it turns out, there are essentially two ways for a possession to end or begin:

1. On the Face-Off
Every possession following a goal or the start of a new period begins with a center face-off. When any player successfully corralls the loose ball following the face-off, possession is awarded to that team.

Thus, the first element in the equation is: (Face-offs Won)

2. Clearing Attempts
Defining when a possession begins or ends on a clearing attempt is not as easy to recognize as it is on a face-off. Because a clearing attempt may or may not be successful, there is actually the opportunity for two possessions to begin and two possessions to end. To illustrate this point, and example is necessary.

Let's say Team A wins the face-off against Team B and advances the ball into Team B's defensive zone. This simple action - collecting the ground ball and advancing it into the attack zone - results in one possession for Team A.

As Team A works the ball around Team B's defensive zone looking for an opportunity, Team B intercepts an errant pass. Consequently, Team B now has a clearing opportunity as a result of the turnover. This clearing opportunity marks a change of possession, no matter how many shots Team A took on change, so long as none of Team A's shot tickled the twine. Thus, the possessions at this point are each 1 and 1, despite the fact that Team B has yet to advance the ball out of their own defensive side of the field.

Now, this is where the possession analysis gets tricky. Given the fact that once Team B creates a clearing opporunity a new possession occurs, every clearing attempt must be considered a team possession, regardless of whether the team is successful in clearing the ball from their defensive zone. Because all clearing attempts are considered possessions, Team A actually has the opportunity to create two possessions without the ball leaving Team B's defensive zone.

So, say Team B intercepts a Team A pass as noted earlier. On the clearing attempt, Team B fails to clear the ball either by an errant pass, a Team A interception, or a failure to proceed in the required amount of time. At that point, Team A will gain possession.

Thus, from the face-off to Team B's failed clear, three separate possessions have taken place - two for Team A and one for Team B.

If you are asking yourself why clearing attempts are considered as marking the end or beginning of a possession instead of turnovers, you're asking a very valid question. However, turnovers, unlike in basketball, are not effective means for defining when a change of possession takes place in lacrosse. This is for two reasons.

First, very few college lacrosse teams track turnovers. To formulate an equation that takes into account a statistic that appears in only a handful of boxscores is not an effective means for determining the number of possessions a team has.

Second, clearing attempts naturally take into account turnovers, and to consider turnovers as a separate category would "double count" the statistic. In other words, a turnover naturally leads to either a clearing attempt or a failed clearing attempt. Thus, all "turnovers for" are counted for in "total clearing attempts" and "failed opponent clearing attempts."

As a consequence of all of this, the formula for possessions now looks as follows:

Face-offs Won + Total Team Clearing Attempts + Number of Failed Opponent Clearing Attempts

[Example]
To illustrate how the possession formula works, a brief look at Syracuse's 2005 statistics may be helpful.

Face-Offs Won:
Syracuse - 175
Opponents - 158

Total Clearing Opportunities:
Syracuse - 286
Opponents - 283

Total Failed Clearing Opportunities:
Syracuse - 45
Opponents - 56

Thus, with this material, we can determine the number of possessions Syracuse had in 2005 by using the formula above:

175+286+56 = 517 = Number of Syracuse Possessions
158 + 283 + 45 = 486 = Number of Syracuse Opponent Possessions

This data indicates that Syracuse averaged somewhere around 38 possessions per game last season. The Orange's opponents averaged about 36, which makes sense, given the fact that Syracuse was stronger on the ride and at the face-off "x" than its opponents, thus resulting in more possessions per contest.

[Data]
The data produced below represents Offensive Efficiency (goals/possession), Defensive Efficiency (opponent goals/possession), and Efficiency Margin (Offensive Efficiency - Defensive Efficiency).

Note: This data does not include Vermont because I have not been able to uncover data from its games against Duke or St. Michael's.

* = Reclassifying/Provisional Division I member

Offensive Efficiency
RankTeamOEff
1Duke.3499
2Cornell.3313
3Johns Hopkins.3169
4Bellamarine*.3157
5Massachusetts.314
6Bucknell.3034
7Syracuse.2998
8Albany.2934
9Colgate.2906
10Delaware.2875
11Princeton.2812
12Notre Dame.2799
13Maryland.2796
14UMBC.2791
15Stony Brook.2783
16Lehigh.274
17Penn State.2718
18Manhattan.2701
19Navy .2684
20Denver.268
21Mt. St. Mary's.2677
22Dartmouth.265
23Virginia.2641
24Army.2639
25Holy Cross.2623
26Yale.2582
27VMI.2577
28Ohio State.2573
29Fairfield.2564
30Drexel.2552
31North Carolina.2546
32Hofstra.2546
33Brown.25
34Georgetown.2488
35Sacred Heart.2457
36Towson.2426
37Rutgers.2415
38Hobart.2404
39Air Force.2383
40Providence.2332
41Loyola (Md).2304
42Pennsylvania.227
43Harvard.2227
44Marist.2206
45Quinnipiac.219
46Hartford.2144
47Siena.214
48Canisius.2103
49Villanova.2074
50Butler.2027
51St. Joseph's.1891
52Binghamton.1869
53Robert Morris.1845
54Wagner.1724
55St. John's.1605
56Lafayette.1404


Defensive Efficiency
RankTeamDEff
1Bellamarine*.1843
2Virginia.1878
3Duke.1963
4Denver.1966
5Navy.2035
6Drexel.2101
7Villanova.211
8Cornell.2155
9Notre Dame.2156
10Brown.2194
11Georgetown.2206
12Binghamton.2241
13Bucknell.2244
14Dartmouth.2287
15Johns Hopkins.2298
16Loyola (Md.).2304
17North Carolina.2343
18Marist.2354
19Canisius.2367
20Hofstra.2377
21Stony Brook.2388
22Towson.2428
23Albany.2441
24Massachusetts.2455
25Lehigh.2474
26Maryland.2487
27Princeton.2493
28Fairfield.2516
29Air Force.253
30Wagner.2576
31St. John's.2583
32Delaware.259
33Army.2625
34UMBC.2631
35Harvard.2645
36St. Joseph's.2647
37Providence.265
38Manhattan.2747
39Hobart.2751
40Siena.2786
41VMI.2788
42Yale.2802
43Syracuse.2819
44Rutgers.2826
45Mt. St. Mary's.2838
46Butler.2849
47Sacred Heart.287
48Colgate.2871
49Lafayette.2887
50Quinnipiac.2932
51Holy Cross.294
52Penn State.2942
53Ohio State.2971
54Pennsylvania.3189
55Robert Morris.3216
56Hartford.3263


Efficiency Margin
RankTeamEffMar
1Duke.1536
2Bellamarine*.1314
3Cornell.1158
4Johns Hopkins.0871
5Bucknell.07897
6Virginia.0763
7Denver.0715
8Massachusetts.0685
9Navy.0649
10Notre Dame.0643
11Albany.0493
12Drexel .0451
13Stony Brook.0395
14Dartmouth.0363
15Princeton.0318
16Maryland.0309
17Brown.0306
18Delaware.0285
19Georgetown.0282
20Lehigh.0266
21North Carolina.0204
22Syracuse.0179
23Hofstra.0169
24UMBC.0160
25Fairfield.0048
26Colgate.0035
27Army.0014
28Loyola .0000
29Towson-.0002
30Villanova-.0036
31Manhattan-.0046
32Air Force-.0147
33Marist-.0148
34Mt. St. Mary's-.0161
35VMI-.0211
36Yale-.02199
37Penn State-.0225
38Canisius-.0264
39Holy Cross-.0317
40Providence-.0318
41Hobart-.0347
42Binghamton-.0372
43Ohio State-.0398
44Rutgers-.0411
45Sacred Heart-.0413
46Harvard-.0418
47Siena-.0646
48Quinnipiac-.0742
49St. Joseph's-.0756
50Butler-.0822
51Wagner-.0852
52Pennsylvania-.0919
53St. John's-.0978
54Hartford-.1118
55Robert Morris-.1371
56Lafayette-.1483

[Closing Remarks]
Unlike much of the efficiency material I have previously written about in this notebook, the formulae and data derived for this particular essay has been developed by yours truly. Therefore, I am interested in fielding comments as to whether the information I have used to develop possession data is sound.

So, if you feel the urge to comment on any of the methods used above, you're more than welcome to leave a comment below.

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