NEWxSFC - Interim Summary…as of 15 FEB 2010					AVG SUMSQ				AVG STP					AVG Total Absolute				AVG Absolute				Mean RSQ
Previous Ranks	Rank	Forecaster	Class	Total STN 4casts	Error (")	Error Z	% MPRV over AVG	Rank	4cast (")	Error	Error Z	% MPRV over AVG	Rank	Error (")	Error Z	% MPRV over AVG	Rank	Error (")	Error Z	%MPRV over AVG	Rank	RSQ	RSQ Z	% MPRV over AVG	Rank	Forecaster
1	1	ilibov	Senior	100	317	-0.983	48%	5	133.6	9.9	-1.080	72%	3	54.45	-1.014	25%	5	2.17	-1.139	32%	4	63.7%	1.269	38%	7	ilibov
2	2	Shillelagh	Senior	83	434	-0.864	30%	6	105.6	30.9	0.194	-12%	13	57.66	-0.928	21%	6	2.70	-0.554	14%	8	61.3%	0.898	27%	7	Shillelagh
3	3	donsutherland1	Chief	100	320	-0.835	51%	3	155.8	19.8	-0.547	43%	7	57.50	-0.998	31%	3	2.32	-0.985	31%	3	68.0%	0.866	29%	2	donsutherland1
6	4	herb@maws	Senior	97	354	-0.738	45%	5	154.5	20.4	-0.583	42%	8	62.36	-0.774	25%	4	2.60	-0.683	23%	6	63.5%	0.493	19%	6	herb@maws
4	5	Raven	Senior	91	518	-0.726	36%	6	167.0	19.2	-0.425	37%	10	70.33	-0.506	17%	9	3.13	-0.367	14%	10	69.6%	0.686	23%	6	Raven
5	6	millersville_bauers	Journeyman	93	431	-0.704	28%	7	130.9	28.8	0.027	2%	11	62.82	-0.461	13%	9	2.63	-0.614	18%	7	59.3%	0.626	22%	6	millersville_bauers
7	7	wxfox51	Journeyman	96	512	-0.574	38%	6	149.5	22.0	-0.171	15%	8	62.27	-0.771	25%	4	2.65	-0.784	26%	5	68.9%	0.523	21%	7	wxfox51
8	8	Newa2010	Journeyman	94	567	-0.538	30%	8	146.1	20.0	-0.346	33%	10	71.26	-0.421	15%	9	3.06	-0.402	15%	9	68.0%	0.552	20%	7	Newa2010
10	9	Donald Rosenfeld	Senior	100	432	-0.490	33%	6	125.4	21.8	-0.209	14%	8	57.60	-0.808	24%	4	2.33	-0.874	26%	4	55.2%	0.451	19%	5	Donald Rosenfeld
9	10	weatherT	Rookie	99	365	-0.358	20%	7	107.3	44.0	0.268	-19%	12	63.15	-0.180	9%	8	2.51	-0.417	14%	7	52.3%	0.492	17%	7	weatherT
12	11	TQ	Senior	91	414	-0.073	8%	10	104.2	33.2	-0.098	3%	11	67.16	-0.042	4%	9	2.92	0.108	-1%	10	42.2%	-0.305	-5%	10	TQ
11	12	Mitchel Volk	Senior	92	852	0.041	-2%	15	159.8	37.9	0.342	-23%	15	82.38	-0.423	7%	11	3.53	-0.273	4%	12	53.4%	-0.133	-6%	15	Mitchel Volk
15	13	Roger Smith	Senior	104	779	0.305	-22%	12	218.6	71.1	0.992	-90%	14	106.37	0.632	-23%	13	4.07	0.429	-18%	12	55.4%	0.063	2%	10	Roger Smith
13	14	snowman	Intern	92	1033	0.708	-22%	17	135.4	30.7	0.380	-25%	13	100.93	0.417	-14%	15	4.39	0.620	-18%	15	40.9%	-1.014	-28%	18	snowman
14	15	nnjwxguy78	Journeyman	90	930	0.802	-39%	15	162.5	19.2	-0.612	41%	8	101.80	0.878	-25%	15	4.34	0.977	-26%	16	42.8%	-0.791	-17%	15	nnjwxguy78

There have been six (6) snowstorm forecasting Contests to as of 15-FEB-10. Under the ‘two-thirds’ rule…forecasters who have entered at least four (4) forecasts are included in this interim summary.

To qualify for ranking in the Interim and final ‘End-of-Season’ standings…a forecaster must enter at least two-thirds of all Contests.  If a forecaster has made more than enough forecasts to qualify for ranking…only the lowest SUMSQ Z-scores necessary to qualify are used in the computing the average.  IOW…if you made nine forecasts…only your six best SUMSQ Z-scores are used to evaluate your season-to-date performance.  You can think of it as dropping the worse quiz score before your final grade is determined.  The reason we have this rule is to 1) make it possible to miss entering a forecast or two throughout the season and still be eligible for Interim and ‘End-of Season’ ranking and 2) encourage forecasters to take on difficult and/or late-season storms without fear about how a bad forecast might degrade their overall 'season-to-date' performance score(s).

The mean normalized ‘SUMSQ error’ is the Contest/s primary measure of forecaster performance.  This metric measures how well the forecaster/s expected snowfall 'distribution and magnitude' for _all_ forecast stations captured the 'distribution and magnitude' of _all_ observed snowfall amounts.  A forecaster with a lower average SUMSQ Z Score has made more skillful forecasts than a forecaster with higher average SUMSQ Z Score.

The 'Storm Total Precipitation error’ statistic is the absolute arithmetic difference between a forecaster/s sum-total snowfall for all stations and the observed sum-total snowfall. This metric…by itself…is not a meaningful measure of skill…but can provide additional insight of forecaster bias.

The 'Total Absolute error' statistic is the average of your forecast errors regardless of whether you over-forecast or under-forecast. This metric measures the magnitude of your errors.

The 'Average Absolute Error' is the forecaster/s ‘Total Absolute Error’ divided by the number of stations where snow was forecast or observed.

The ‘RSQ error’ statistic is a measure of the how well the forecast captured the variability of the observed snowfall. Combined with the SUMSQ error statistic…RSQ provides added information about how strong the forecaster/s ‘model’ performed.