VGAMdata (version 1.1-9)

wffc: 2008 World Fly Fishing Championships Data

Description

Capture records of the 2008 FIPS-MOUCHE World Fly Fishing Championships held in Rotorua, New Zealand during 22--30 March 2008.

Usage

data(wffc)

Format

A data frame with 4267 observations on the following 8 variables. Each row is a recorded capture.

length

a numeric vector; length of fish in mm.

water

a factor with levels Waihou, Waimakariri, Whanganui, Otamangakau, Rotoaira. These are known as Sectors IV, V, I, II, III respectively, and are also represented by the variable sector.

session

a numeric vector; a value from the set 1,2,...,6. These are time ordered, and there were two sessions per competition day.

sector

a numeric vector; a value from the set 1,2,...,5. Ideally these should be converted to a factor.

beatboat

a numeric vector; beat or boat number, a value from the set 1,2,...,19. Ideally these should be converted to a factor. For a river though, they are contiguous whereas on a lake it is less so.

comid

a numeric vector; the competitor's ID number. Uniquely identifies each competitor. These ID numbers actually correspond to their rankings in the individual level.

iname

a character vector; the individual competitor's name.

country

a character vector; what country the competitors represented. The countries represented were Australia (AUS), Canada (CAN), Croatia (CRO), Czech Republic (CZE), England (ENG), Finland (FIN), France (FRA), Holland (NED), Ireland (IRE), Italy (ITA), Japan (JPN), Malta (MAL), New Zealand (NZL), Poland (POL), Portugal (POR), South Africa (RSA), Slovakia (SVK), USA (USA), Wales (WAL).

Details

Details may be obtained at Yee (2010) and Yee (2014). Here is a brief summary. The three competition days were 28--30 March. Each session was fixed at 9.00am--12.00pm and 2.30--5.30pm daily. One of the sessions was a rest session. Each of 19 teams had 5 members, called A, B, C, D and E (there was a composite team, actually). The scoring system allocated 100 points to each eligible fish (minimum length was 18 cm) and 20 points for each cm of its length (rounded up to the nearest centimeter). Thus a 181mm or 190mm fish was worth 480 points. Each river was divided into 19 contiguous downstream beats labelled 1,2,...,19. Each lake was fished by 9 boats, each with two competitors except for one boat which only had one. Each competitor was randomly assigned to a beat/boat.

Competitors were ranked according to their placings at each sector-session combination, and then these placings were summed. Those with the minimum total placings were the winners, thus it was not necessarily those who had the maximum points who won. For example, in Session 1 at the Waihou River, each of the 19 competitors was ranked 1 (best) to 19 (worst) according to the point system. This is the ``placing'' for that session. These placings were added up over the 5 sessions to give the ``total placings''.

All sectors have naturally wild Rainbow trout (Oncorhynchus mykiss) while Lake Otamangakau and the Whanganui River also holds Brown trout (Salmo trutta). Only these two species were targetted. The species was not recorded electronically, however a post-analysis of the paper score sheets from the two lakes showed that, approximately, less than 5 percent were Brown trout. It may be safely assumed that all the Waihou and Waimakariri fish were Rainbow trout. The gender of the fish were also not recorded electronically, and anyway, distinguishing between male and female was very difficult for small fish.

Although species and gender data were supposed to have been collected at the time of capture the quality of these variables is rather poor and furthermore they were not recorded electronically.

Note that some fish may have been caught more than once, hence these data do not represent individual fish but rather recorded captures.

Note also that a few internal discrepancies may be found within and between the data frames wffc, wffc.nc, wffc.indiv, wffc.teams. This is due to various reasons, such as competitors being replaced by reserves when sick, fish that were included or excluded upon the local judge's decision, competitors who fished two hours instead of three by mistake, etc. The data has already been cleaned of errors and internal inconsistencies but a few may remain.

References

Yee, T. W. (2010). VGLMs and VGAMs: an overview for applications in fisheries research. Fisheries Research, 101, 116--126.

Yee, T. W. (2014). Scoring rules, and the role of chance: analysis of the 2008 World Fly Fishing Championships. Journal of Quantitative Analysis in Sports. 10, 397--409.

See Also

wffc.indiv, wffc.teams, wffc.nc, wffc.P1, lakeO.

Examples

summary(wffc)
with(wffc, table(water, session))

# Obtain some simple plots
waihou <- subset(wffc, water == "Waihou")
waimak <- subset(wffc, water == "Waimakariri")
whang  <- subset(wffc, water == "Whanganui")
otam   <- subset(wffc, water == "Otamangakau")
roto   <- subset(wffc, water == "Rotoaira")
minlength <- min(wffc[, "length"])
maxlength <- max(wffc[, "length"])
nwater <- c("Waihou"    = nrow(waihou),
            "Waimakariri" = nrow(waimak),
            "Whanganui" = nrow(whang),
            "Otamangakau" = nrow(otam),
            "Rotoaira"  = nrow(roto))
if (FALSE) {
par(mfrow = c(2, 3), las = 1)
# Overall distribution of length
with(wffc, boxplot(length/10 ~ water,
                   ylim = c(minlength, maxlength)/10,
                   border = "blue", main = "Length (cm)",
                   cex.axis = 0.5))

# Overall distribution of LOG length
with(wffc, boxplot(length/10 ~ water,
                   ylim = c(minlength, maxlength)/10,
                   border = "blue", log = "y", cex.axis = 0.5,
                   main = "Length (cm) on a log scale"))

# Overall distribution of number of captures
pie(nwater, border = "blue", main = "Proportion of captures",
    labels = names(nwater), density = 10, col = 1:length(nwater),
    angle = 85+30* 1:length(nwater))

# Overall distribution of number of captures
with(wffc, barplot(nwater, main = "Number of captures",
                   cex.names = 0.5, col = "lightblue"))

# Overall distribution of proportion of number of captures
with(wffc,
     barplot(nwater / sum(nwater), cex.names = 0.5,
             col = "lightblue",
             main = "Proportion of captures"))
# An interesting lake
with(roto,
     hist(length/10, xlab = "Fish length (cm)", col = "lightblue",
          breaks = seq(18, 70, by = 3), prob = TRUE,
          ylim = c(0, 0.08), border = "blue", ylab = "",
           main = "Lake Rotoaira", lwd = 2))
}