Building a prediction model with the dpois function in R - r

Question

Hello! I am in the beginning stages of building (and learning!) how to build prediction models for sports, specifically using NHL statistics.
I have all the game outcomes of the NHL since 1990, and I want to use # goals to predict outcomes in future games (just based on goals, for now)
Below is an excerpt of my data set, but the full data set can be found in this Git link:
https://github.com/papelr/nhldatar/blob/master/nhldatar/data/NHL_outcomes.rda
Date Visitor GVisitor Home GHome Att.
1 1990-10-04 Philadelphia Flyers 1 Boston Bruins 4 <NA>
2 1990-10-04 Montreal Canadiens 3 Buffalo Sabres 3 <NA>
3 1990-10-04 Vancouver Canucks 2 Calgary Flames 3 <NA>
4 1990-10-04 New York Rangers 3 Chicago Blackhawks 4 <NA>
5 1990-10-04 Quebec Nordiques 3 Hartford Whalers 3 <NA>
6 1990-10-04 New York Islanders 1 Los Angeles Kings 4 <NA>
7 1990-10-04 St. Louis Blues 3 Minnesota North Stars 2 <NA>
8 1990-10-04 Detroit Red Wings 3 New Jersey Devils 3 <NA>
9 1990-10-04 Toronto Maple Leafs 1 Winnipeg Jets 7 <NA>
10 1990-10-05 Pittsburgh Penguins 7 Washington Capitals 4 <NA>
11 1990-10-06 Quebec Nordiques 1 Boston Bruins 7 <NA>
12 1990-10-06 Toronto Maple Leafs 1 Calgary Flames 4 <NA>
13 1990-10-06 Winnipeg Jets 3 Edmonton Oilers 3 <NA>
14 1990-10-06 New York Rangers 4 Hartford Whalers 5 <NA>
15 1990-10-06 Vancouver Canucks 6 Los Angeles Kings 3 <NA>
16 1990-10-06 New York Islanders 2 Minnesota North Stars 4 <NA>
17 1990-10-06 Buffalo Sabres 5 Montreal Canadiens 6 <NA>
18 1990-10-06 Philadelphia Flyers 1 New Jersey Devils 3 <NA>
19 1990-10-06 Chicago Blackhawks 5 St. Louis Blues 2 <NA>
20 1990-10-06 Detroit Red Wings 4 Washington Capitals 6 <NA>
21 1990-10-07 New York Islanders 4 Chicago Blackhawks 2 <NA>
22 1990-10-07 Toronto Maple Leafs 2 Edmonton Oilers 3 <NA>
23 1990-10-07 Detroit Red Wings 2 Philadelphia Flyers 7 <NA>
24 1990-10-07 New Jersey Devils 4 Pittsburgh Penguins 7 <NA>
25 1990-10-07 Boston Bruins 5 Quebec Nordiques 2 <NA>
26 1990-10-08 Hartford Whalers 3 Montreal Canadiens 5 <NA>
27 1990-10-08 Minnesota North Stars 3 New York Rangers 6 <NA>
28 1990-10-08 Calgary Flames 4 Winnipeg Jets 3 <NA>
29 1990-10-09 Minnesota North Stars 2 New Jersey Devils 5 <NA>
30 1990-10-09 Pittsburgh Penguins 3 St. Louis Blues 4 <NA>
31 1990-10-09 Los Angeles Kings 6 Vancouver Canucks 2 <NA>
32 1990-10-10 Calgary Flames 5 Detroit Red Wings 6 <NA>
33 1990-10-10 Buffalo Sabres 3 Hartford Whalers 4 <NA>
34 1990-10-10 Washington Capitals 2 New York Rangers 4 <NA>
35 1990-10-10 Quebec Nordiques 8 Toronto Maple Leafs 5 <NA>
36 1990-10-10 Boston Bruins 4 Winnipeg Jets 2 <NA>
37 1990-10-11 Pittsburgh Penguins 1 Chicago Blackhawks 4 <NA>
38 1990-10-11 Edmonton Oilers 5 Los Angeles Kings 5 <NA>
39 1990-10-11 Boston Bruins 3 Minnesota North Stars 3 <NA>
40 1990-10-11 New Jersey Devils 4 Philadelphia Flyers 7 <NA>
This is the prediction model that I have come up with so far, and I have failed to get the matrix that should come with my simulate match line below. Any help would be great.
# Using number of goals for prediction model
model_one <-
rbind(
data.frame(goals = outcomes$GHome,
team = outcomes$Home,
opponent = outcomes$Visitor,
home = 1),
data.frame(goals = outcomes$GVisitor,
team = outcomes$Visitor,
opponent = outcomes$Home,
home = 0)) %>%
glm(goals ~ home + team + opponent,
family = poisson (link = log), data = .)
summary(model_one)
# Probability function / matrix
simulate_game <- function(stat_model, homeTeam, awayTeam, max_goals =
10) {
home_goals <- predict(model_one,
data.frame(home = 1,
team = homeTeam,
opponent = awayTeam),
type ="response")
away_goals <- predict(model_one,
data.frame(home = 0,
team = awayTeam,
opponent = homeTeam),
type ="response")
dpois(0: max_goals, home_goals) %>%
dpois(0: max_goals, away_goals)
}
simulate_game(model_one, "Nashville Predators", "Chicago Blackhawks",
max_goals = 10)
I totally understand that a Poisson model isn't the best for sports predictions, but I am rebuilding a model I found for the EPL for learning/practice reasons, and adapting it to the NHL (from David Sheehan's model, https://dashee87.github.io/data%20science/football/r/predicting-football-results-with-statistical-modelling/).
Any tips would be great, because currently, this model returns a bunch of warnings:
There were 11 warnings (use warnings() to see them)
> warnings()
Warning messages:
1: In dpois(., 0:max_goals, away_goals_avg) : non-integer x = 0.062689
2: In dpois(., 0:max_goals, away_goals_avg) : non-integer x = 0.173621